--- title: "ChatGPT in 2026: Models, Features, Pricing and What the Data Shows" description: "GPT-5.5 explained: every model, tier, feature and benchmark in 2026. Honest data on hallucination rates and where ChatGPT beats peers." url: "https://suprmind.ai/hub/chatgpt/" published: "2026-05-07T19:09:41+00:00" modified: "2026-05-07T19:16:02+00:00" author: Radomir Basta type: page schema: WebPage language: en-US site_name: Suprmind --- # ChatGPT in 2026: Models, Features, Pricing and What the Data Shows ChatGPT 2026 Guide # ChatGPT in 2026: Models, Features, Pricing and What the Data Shows ChatGPT is the most widely used conversational AI product in the world, built by OpenAI on the GPT model family. As of May 2026, the flagship model behind ChatGPT is GPT-5.5, released April 23, 2026. It posts the highest score ever recorded on the Artificial Analysis Intelligence Index (60, rank 1) and simultaneously the highest hallucination rate ever recorded on the AA-Omniscience benchmark (86%). That paradox – more capable, more confident, more likely to fabricate when it does not know – is the most important fact about ChatGPT in 2026 and the through-line of this guide. This page covers what ChatGPT is, the current model lineup, what each tier costs and which model you actually get on it, the feature set as it stands in May 2026, the benchmark picture (where ChatGPT leads, where it lags, what to read into the gaps between vendor and independent measurements), the hallucination patterns that should shape how you use it, what production multi-model data shows about ChatGPT relative to its peers, the active controversies, and the questions people most often search for. Numbers are dated. The ChatGPT product changes weekly. Where a claim is volatile, it is flagged. If you are picking AI tools for high-stakes work, the headline finding from production data is this: per the [Suprmind Multi-Model Divergence Index](https://suprmind.ai/hub/multi-model-ai-divergence-index/) (April 2026 Edition, n=1,324 production turns), ChatGPT was caught making errors by other models 295 times while correcting them only 111 times – a catch ratio of 0.38 that is the lowest of five providers tracked. The decision is not whether ChatGPT is good. It is good. The decision is whether using it alone is the right risk profile for your work. ## What ChatGPT Is ChatGPT is a conversational AI product developed by OpenAI that uses the GPT-5.5 language model as of April 2026 to answer questions, generate text, analyze documents, write and execute code, generate images, control web browsers and operating systems, and complete multi-step tasks. It is available at chatgpt.com, on iOS and Android apps, on dedicated macOS and Windows desktop apps, and via the OpenAI API at platform.openai.com. The product is distinct from the underlying GPT model family that powers it – the same models can be accessed directly through the API at different pricing. OpenAI has released six major model generations in under eight months between GPT-5 (August 2025) and GPT-5.5 (April 2026). The cadence is accelerating, not stabilizing. Greg Brockman, OpenAI’s president, described that pace as expected to continue during the GPT-5.5 launch briefing. ChatGPT crossed 300 million weekly active users in early 2026, generated approximately 8 billion USD in 2025 revenue, and reports approximately 2 billion USD in monthly revenue as of its March 2026 funding round announcement. Adoption scale at this level is real signal – it indicates product-market fit, integration breadth, and accessibility – but it is a distribution metric, not a quality metric. The data on whether ChatGPT is the best AI for any specific task is less flattering than the user count would suggest. ### ChatGPT vs the GPT API ChatGPT is a consumer and prosumer product. The OpenAI API is a developer surface. Both run on GPT models, but the experience and cost structure are different. ChatGPT offers six consumer tiers (Free, Go, Plus, Pro $100, Pro $200, Business) with bundled access to features like Projects, Memory, Deep Research, ChatGPT Agent, and Custom GPTs. The API exposes raw model endpoints with metered per-token pricing, no chat UI, no Memory, no Projects. Most production applications integrating GPT capabilities use the API directly. ChatGPT is what most users interact with day-to-day. If you are evaluating cost for a workload running through your own product, look at the API pricing table later on this page. If you are evaluating cost for individual or team use of ChatGPT itself, look at the consumer tier table. ### ChatGPT vs GPT-5.5 – Are They the Same? No. GPT-5.5 is the underlying model. ChatGPT is the product that routes your query to GPT-5.5, GPT-5.4, or another model depending on tier and prompt complexity. As of March 2026, the ChatGPT model picker was redesigned to show only three labels – “Instant”, “Thinking”, and “Pro” – with the actual underlying model selected automatically. To verify which specific model handled a query, you have to navigate to a Configure setting most users never open. API users always receive the specific model ID in response metadata. ChatGPT users on default settings do not. This matters more than it sounds. Per the [Suprmind Multi-Model Divergence Index](https://suprmind.ai/hub/multi-model-ai-divergence-index/) (April 2026 Edition, n=1,324 production turns), ChatGPT’s confident-contradicted rate drops from 39.6% on all turns to 36.2% on high-stakes turns – a 3.4-point calibration improvement under pressure. That is genuinely good behavior. But you cannot reliably tell from the ChatGPT UI whether your high-stakes query was handled by GPT-5.5, GPT-5.4, or a routing fallback to a smaller model. The transparency gap is documented and persistent. ## Current Models and Variants OpenAI maintains two parallel architectural lines: the GPT line (primary generation and instruction models) and the o-series (reasoning models using extended internal chain-of-thought). GPT-5 introduced a unified architecture with internal routing between fast and deep reasoning, removing the user-facing distinction between the lines. As of May 2026, GPT-5.5 is flagship across both ChatGPT and the API. The o-series endpoints (o3, o3-pro) remain in the API but are no longer the path most users take. Below is the active and deprecated model picture as of May 2026. Variants and dates are taken from OpenAI’s official model catalog at developers.openai.com/api/docs/models/all and confirmed against independent tracking. This table changes frequently – check the source URL for the current list. ### Active GPT Models (May 2026) Source: developers.openai.com – last verified 2026-05-07 Current Flagship GPT-5.5 / GPT-5.5 Pro - Released 2026-04-23 - 1.1M token context, 128K output - Multimodal: text, image, audio in / text, image out - API: $5.00 / $30.00 per 1M tokens Coding Specialist GPT-5.4 / Pro / Codex Path - Released 2026-03-05 - 272K standard / 1.05M extended context - Native computer use – 75% OSWorld-Verified - API: $2.50 / $15.00 per 1M tokens Default Free / Go Tier GPT-5.3 Instant - Released 2026-03-03 - Reduced moralizing preambles vs prior models - Hallucination reduction: 26.8% with web, 19.7% without (vs prior) - Being superseded by GPT-5.5 Instant Reasoning Models (API) o3 / o3-pro - 200K context, 100K output - Selectable reasoning effort: low, medium, high - API: o3 $2.00 / $8.00 – o3-pro $20.00 / $80.00 - o3-mini and o4-mini deprecated in ChatGPT, API legacy Long-Context Workhorse GPT-4.1 / GPT-4.1 mini - 1M token context - API: $2.00 / $8.00 (mini: $0.40 / $1.60) - Retired from ChatGPT UI 2026-02-13, API active - Vectara new dataset: 5.6% (better than GPT-5 on summarization) Open-Weight Releases gpt-oss-120b / gpt-oss-20b - Apache 2.0 license - 120B fits on a single H100 GPU - OpenAI’s first frontier-scale open releases - Architecture details not publicly disclosed ### GPT-5.5, GPT-5.4, GPT-5.3 – What Changed Between Versions**GPT-5.3 Instant (released March 3, 2026)**was the default Instant model for ChatGPT users until GPT-5.5 Instant began rolling out around May 1, 2026. Its main behavioral change was reduced “cringe” – fewer overly declarative phrasing patterns, fewer unnecessary refusals, fewer moralizing preambles. OpenAI claimed a 26.8% hallucination reduction with web search and 19.7% without versus prior Instant models.**GPT-5.4 (released March 5, 2026)**introduced native computer use, scoring 75% on OSWorld-Verified – above the human baseline of 72.4%. It merged the GPT-5.3-Codex coding pipeline into the base model, expanded standard context to 272,000 tokens with extended context up to 1.05 million tokens in Codex and API contexts, and reported 33% fewer factual errors than GPT-5.2. API pricing landed at $2.50 per 1M input tokens and $15 per 1M output tokens at standard context. Tokens above 272K bill at 2x input and 1.5x output.**GPT-5.5 (released April 23, 2026)**is the current flagship. OpenAI’s public framing is “a faster, sharper thinker for fewer tokens” versus GPT-5.4. The model posts an Artificial Analysis Intelligence Index of 60 (rank 1 across all models), 97.5% on AIME 2026 (rank 1 of 25 models on MathArena), 88.7% on SWE-bench Verified (a codersera independent guide reports 82.6% – flag as conflict pending OpenAI system card publication), 85% on ARC-AGI-2, 78.7% on OSWorld-Verified. Context window is 1.1 million tokens input and 128,000 output. API pricing is $5.00 per 1M input, $0.50 per 1M cached input, and $30.00 per 1M output. As of late April 2026, ChatGPT API access for GPT-5.5 was stated as “coming very soon” without a firm date. The training cutoff for GPT-5.5 has not been publicly disclosed. GPT-5.4’s cutoff is reported as August 2025 in secondary sources but is not confirmed in an official OpenAI system card. ### Reasoning Models – o-Series vs GPT-5.x The o-series models (o1, o3, o3-pro, o4-mini) use a reinforcement-learning-trained reasoning process that generates long internal chains of thought before producing output. They were the first OpenAI models with selectable reasoning effort levels. Starting with GPT-5, OpenAI unified this behavior into the GPT line via internal routing. The model picker now offers Instant, Thinking, and Pro – the o-series labels are gone from the consumer UI even though o3 and o3-pro remain available in the API. For practical use, this means: if you are on a ChatGPT consumer plan and want extended reasoning, choose Thinking mode in the model picker. If you are on the API and want explicit control over reasoning compute, call `o3` or `o3-pro` directly with the reasoning_effort parameter. The o-series is where deeper reasoning lives, but the consumer-facing distinction is gone. ### Which Model Does Each Tier Give You? Tier-to-Model Matrix This is the single most-searched and least-answered question in ChatGPT documentation. The answer changes monthly. The table below reflects May 2026. Tier Default Instant Thinking Available Pro Model Access Codex / Coding Path Free ($0) GPT-5.3 Instant (GPT-5.5 Instant rolling out) No No No Go ($8) GPT-5.2 Instant No No No Plus ($20) GPT-5.5 Instant + GPT-5.5 Thinking Yes GPT-5.4 Pro (Flexible) Limited Pro $100 ($100) GPT-5.5 Instant + GPT-5.5 Thinking Yes GPT-5.5 Pro 5x Plus Codex usage Pro $200 ($200) GPT-5.5 Instant + GPT-5.5 Thinking Yes GPT-5.5 Pro (extended compute) 20x Plus message limits Business ($25-30/user) GPT-5.2 Unlimited GPT-5.2 Thinking (Flexible) No Yes Enterprise (custom) All Business models + extended context Yes Available Yes**A note on the Business tier model lineup:**OpenAI’s Business pricing page as of May 2026 references GPT-5.2 as the underlying model for Business workspaces. GPT-5.5 rollout to Business has been confirmed in independent reporting, but the pricing page may not yet reflect updated availability. Treat this row as volatile until OpenAI updates the page. Per the [Suprmind Multi-Model Divergence Index](https://suprmind.ai/hub/multi-model-ai-divergence-index/) (April 2026 Edition, n=1,324 production turns), ChatGPT surfaces 339 unique insights across the dataset – 13.1% share of all unique insights, the lowest of five providers tracked. Perplexity (636, 24.7%) and Claude (631, 24.5%) each surfaced nearly twice as many. This is one reason knowing which model handled your query matters: if a Plus user is being routed to a smaller fast-mode variant for a high-stakes query, the unique-insight floor is even lower. See also: [AI unique insights comparison →](https://suprmind.ai/hub/multi-model-ai-divergence-index/) ## Pricing and Plans ChatGPT in 2026 has more tiers than at any previous point. The picture below covers consumer, prosumer, business, and enterprise. API pricing is separate and follows in the next subsection. All prices are in USD. All limits are subject to change – the OpenAI pricing pages are the canonical source. ### Consumer Tiers: Free, Go, Plus, Pro**Free ($0/month)**runs on GPT-5.3 Instant by default with GPT-5.5 Instant rolling out. The tier includes approximately 10 messages per 5-hour window on GPT-5.3, 3 file uploads per day, GPT Store browsing, and access to Custom GPTs other people have built. Deep Research, Advanced Voice Mode, ChatGPT Agent, and Sora are not available on Free. As of February 9, 2026, Free tier in the US displays advertisements – this is the first time OpenAI has placed ads in ChatGPT.**Go ($8/month)**launched globally on January 16, 2026 after an August 2025 India-only debut. It runs on GPT-5.2 Instant and provides roughly 10x Free message limits, 10x file uploads, and 10x image creation, with expanded memory. Go also displays ads. The tier sits between Free and Plus for users who want more capacity but do not need the Plus feature set.**Plus ($20/month)**is the entry point for serious use. It includes GPT-5.5 Instant and GPT-5.5 Thinking access via the Auto selector, GPT-5.4 Pro and o3 in Flexible mode, 80 file uploads per 3-hour rolling window, 25 files per Project, 10 Deep Research queries per month, Advanced Voice Mode, image generation, Sora video generation in limited capacity, ChatGPT Agent mode, Canvas, Tasks, and Custom GPT creation. Annual billing is reported at $198/year, though OpenAI does not publish annual price points on its public pages as of dossier date – flag that as volatile.**Pro $100/month**launched April 9, 2026 as a middle Pro tier. It provides GPT-5.5 Pro access, the same core Pro features as the $200 plan, and 5x Plus usage on Codex – with a launch promotion of 10x usage through May 31, 2026. The primary distinction from Pro $200 is rate limits, not feature breadth.**Pro $200/month**sits at the top of the consumer ladder. It provides GPT-5.5 Pro with extended compute, 20x Plus message limits, 1080p non-watermarked Sora video output up to 25 seconds (where Sora is still available – see Sora note in Features), priority service during peak demand, and 1M-token context for long-document work. For users running ChatGPT for hours per day on consequential tasks, Pro $200 is the tier most likely to feel uncapped. ### Business, Enterprise, and Edu Tiers**Business**(formerly ChatGPT Team, renamed August 2025) is $30 per user per month billed monthly or $25 per user per month billed annually. It includes shared workspaces, SAML SSO, no model training on your data, SOC 2 Type 2 compliance, the Codex agent, Deep Research, 32K context for non-reasoning models, and 196K context for reasoning models. As of dossier date, Business does not include SCIM provisioning or ISO 27001/27017/27018/27701 certifications – those are Enterprise features.**Enterprise**is custom-priced (independent estimates land in the $40-60 per user per month range, but OpenAI does not disclose). It adds ISO certifications, SCIM provisioning, enterprise key management, role-based access control, an analytics dashboard, IP allowlisting, data residency options across the US, EU, UK, JP, CA, KR, SG, IN, AU, and UAE, a global admin console, 24/7 priority support, and custom legal terms.**Edu**is intended for academic institutions. Pricing is not public. ### API Pricing for Developers The OpenAI API is metered per-token with separate input, cached input, and output rates. Cached inputs (a request reusing prompt material from a recent prior request) get a substantial discount. Model Input $/1M Cached Input $/1M Output $/1M Context Window GPT-5.5 $5.00 $0.50 $30.00 1.1M GPT-5.4 $2.50 $0.25 $15.00 272K / 1.05M extended GPT-5.4 mini $0.75 $0.075 $4.50 not disclosed GPT-5 $1.25 $0.125 $10.00 128K GPT-4.1 $2.00 $0.50 $8.00 1M GPT-4.1 mini $0.40 $0.10 $1.60 1M GPT-4o $2.50 $1.25 $10.00 128K GPT-4o mini $0.15 not disclosed $0.60 128K o3 $2.00 $0.50 $8.00 200K o3-pro $20.00 not disclosed $80.00 200K o4-mini $1.10 $0.275 $4.40 200K o1 $15.00 $7.50 $60.00 200K o1-pro $150.00 not disclosed $600.00 200K GPT-realtime-1.5 audio $32.00 audio in / $4.00 text in $0.40 $64.00 audio out / $16.00 text out not disclosed GPT Image 2 $5.00 text / $8.00 image in $1.25 / $2.00 $30.00 image Web Search tool $10.00 / 1k calls – – – Source: openai.com/api/pricing as of 2026-05-07. The API also offers Batch (50% discount, 24-hour async), Flex (lower cost, slower), and Priority (2.5x standard for guaranteed throughput) processing tiers. For comparative context: GPT-4o mini at $0.15 per 1M input is roughly 33x cheaper than GPT-5.5 per input token. For high-volume workloads that do not need flagship capability, the older multimodal model is still the cost-efficient default. See also: [GPT-5.5 API price details →](https://suprmind.ai/hub/chatgpt/pricing/) ## Core Features ChatGPT’s feature set in 2026 spans document handling, multi-step research, agentic computer control, voice, image generation, code execution, persistent memory, and customization. The list below is the canonical surface as of May 2026. Features marked deprecated are no longer recommended for new use even if API access lingers. ### Projects and Memory Projects group related conversations under a shared context – instructions, uploaded files, and Project Memory that persists across all chats within that project. Memory in a Project is scoped: facts the model learned in main chat do not bleed into Projects, and Project memories do not leak out. File limits per Project are tier-dependent: Free 5 files, Go and Plus 25 files, Pro and Business and Enterprise 40 files. Projects launched November 2025. Project Memory followed in August 2025. Memory beyond Projects stores facts the model extracts from conversations – preferences, past decisions, personal context – in a persistent profile editable at chatgpt.com/settings/personalization. Users can view, edit, or delete individual memory entries or disable memory entirely. Memory has no published expiration. It persists until manually deleted. Number of stored items and token cost of memory injection are not publicly specified. ### Deep Research Deep Research is a multi-step research agent that issues sequential web queries, reads retrieved pages, synthesizes across sources, and produces a structured report with citations. Sessions take 5 to 30 minutes and can read dozens of pages. Available on Plus (10 queries per month), Pro (higher limits, exact count not publicly disclosed), Business, and Enterprise. As of February 2026, Deep Research connects to any MCP (Model Context Protocol) server, enabling enterprise data integration without custom API plumbing. A practical caveat: Deep Research synthesizes from sourced web content. It does not independently verify facts. The report contains citations but you must still verify claims against the originals. Per the Suprmind [Multi-Model Divergence Index](https://suprmind.ai/hub/multi-model-ai-divergence-index/) (April 2026 Edition, n=1,324 production turns), Research Analysis is the domain where Claude vs ChatGPT is the top combative pair, with 52.2% of contradictions in that domain being critical severity. If your research is consequential, cross-checking with another model is the practical answer. See also: [ChatGPT Deep Research vs Perplexity →](https://suprmind.ai/hub/chatgpt/features/) ### Canvas Canvas is a side-by-side editing mode where the user message and the model output appear as a live collaborative document. You can edit the document directly, ask ChatGPT to revise specific sections, and track changes. It differs from a standard chat thread by preserving output as an editable artifact. Canvas is most useful for long-form drafting where iterative revision matters more than conversational back-and-forth. ### ChatGPT Agent (Agentic Mode) ChatGPT Agent is the consumer-facing name for what was originally Operator (launched January 2025 for Pro users in the US and integrated into ChatGPT in July 2025). The agent operates a virtual machine with a visual browser, text browser, terminal, and OpenAI APIs. It can browse websites, click, type, scroll, execute code, download files, and interact with connected third-party services like Gmail and GitHub. For authenticated actions, a special browser view allows secure login without exposing credentials to the model. GPT-5.5’s OSWorld-Verified score is 78.7%, above the human baseline of 72.4%. ChatGPT Agent is available on Plus, Pro, and Business at launch and rolled to Enterprise and Edu in following weeks. The agent inherits standard agentic risk – irreversible actions, credential exposure risk, unpredictable failure modes – and OpenAI documents a “minimal footprint” principle plus human confirmation for sensitive operations. Session length and action-count limits are not publicly specified. See also: [ChatGPT Agent capabilities and limits →](https://suprmind.ai/hub/chatgpt/features/) ### Advanced Voice Mode Advanced Voice Mode runs on a specialized audio model (the GPT-4o Audio pipeline) that processes spoken input and produces spoken output without intermediate text transcription. It supports emotional tone in some configurations and video input on Business with the “advanced voice with video” feature. Available on Plus and above. As of late 2025, users on Reddit reported AVM still felt tied to an older model with shallower depth than text-mode GPT-5.x – no public confirmation of a GPT-5.x audio upgrade has been issued. The API exposes a separate `gpt-realtime-1.5` endpoint for the best voice-in/voice-out experience. ### Sora Video Generation (Deprecated) Sora was OpenAI’s flagship video and audio generation model. Sora 2 launched September 30, 2025. ChatGPT integration was reported as planned in March 2026 per The Information, but**the Sora web and app experiences were discontinued on April 26, 2026**. The Sora API will be discontinued on September 24, 2026. The integration into ChatGPT that was rumored never materialized before the product was shut down. Sora is listed as “Limited” on the Business tier feature matrix as a legacy access designation. Treat Sora as deprecated for new use cases. ### Code Interpreter and Data Analysis Code Interpreter (renamed Advanced Data Analysis in late 2024) lets the model write and execute Python in an isolated sandbox. It accepts CSV, Excel, JSON, PDFs, and images, and produces charts, processed files, and computed results. The sandbox has no internet access – code that calls external APIs must be run by the user locally. Code and output are visible in the conversation. Available on Plus and above with no toggle required since 2025. On the API via the `code_interpreter` tool in the Responses API. Sandbox execution time and compute caps are not publicly specified. ### Custom GPTs and the GPT Store Custom GPTs are user-built versions of ChatGPT configured for a specific purpose – a system prompt, optional knowledge files (up to 20 files at 512MB each), configured tools (web search, image generation, code interpreter), and optional API actions. The GPT Store launched January 2024. As of June 2025, builders can select from any available model when creating or running a custom GPT, not just GPT-4o. OpenAI added a “Recommended Model” setting that auto-applies if a user’s tier lacks access to the configured model. A documented friction point: if a custom GPT specifies a model unavailable to the user’s tier, OpenAI silently substitutes an alternative. The user may not be running the model the GPT was built around. GPT Store browsing is on Free and above. Creating and publishing requires Plus or above. Workspace-private GPTs are Business and above. See also: [Custom GPTs deep guide →](https://suprmind.ai/hub/chatgpt/features/) ### Tasks (Scheduled) Tasks let users schedule recurring or one-time operations – reminders, recurring research queries, scheduled reports – that ChatGPT executes at a specified time even when the user is not actively in the app. ChatGPT proactively suggests tasks from conversation context, with explicit user approval required before activation. Notifications come via push or email. Available on Plus, Business, and Pro from beta launch in January 2025. Free tier access is not confirmed as of dossier date. ### File Uploads and Document Handling ChatGPT accepts PDF, DOCX, XLSX, CSV, TXT, JSON, HTML, images (JPEG, PNG, GIF, WebP), code files, and audio files for transcription. File size cap is 512MB per file, with separate caps of 50MB for spreadsheets and 20MB for images. Text and document files are capped at 2 million tokens each. Per-message limit is 10 files. Per-Project limit is 25 files (Plus). Per-3-hour rolling window is 80 files (Plus). Storage limits run to 10GB per user and 100GB per organization on Business and Enterprise. Parser fidelity is highest for plain text, structured CSVs, and DOCX. Complex multi-column PDFs with heavy formatting may experience extraction degradation. OpenAI does not publish a parser fidelity metric. There is also no visible upload-quota indicator in the UI – file counting and limit resets are opaque. ### Web Browsing and Search ChatGPT issues search queries through an internal retrieval layer, receives web results, and incorporates them into responses with citations. All GPT-5.x models default to having browsing capability available. The browsing intervention is the single largest hallucination-reduction lever ChatGPT users have. Per [Suprmind’s AI Hallucination Rates and Benchmarks reference](https://suprmind.ai/hub/ai-hallucination-rates-and-benchmarks/), GPT-5’s hallucination rate drops from 47% to 9.6% with browsing enabled – a 37-point reduction that exceeds the effect of switching from GPT-5 to a different model entirely. Available on Free and above. API web search is metered at $10.00 per 1,000 calls. Search content tokens are free. ## Benchmark Performance Benchmarks tell different stories depending on what they measure. Academic capability benchmarks favor GPT-5.5 strongly. User-preference benchmarks rank it below several competitors. Both are real signals. Treat them as different evaluations of different qualities, not as competing accounts of “best”. ### Where GPT-5.5 Leads**Mathematical reasoning at Olympiad scale.**GPT-5.5 scores 97.5% on AIME 2026 (rank 1 of 25 models on MathArena), 97.73% on HMMT February 2026, and 92.30% overall on MathArena’s final-answer competition suite (rank 1 of 23 models). On math problems with verifiable answers, GPT-5.5 leads by margins wide enough to clear statistical noise.**Agentic computer use.**GPT-5.4 scored 75% on OSWorld-Verified, above the human baseline of 72.4%. GPT-5.5 extended this to 78.7%. As of dossier date, no competing model has matched this score on OSWorld-Verified per available data.**Artificial Analysis Intelligence Index.**GPT-5.5 (xhigh reasoning effort) tops the AA Index at 60, ahead of all competitors on the composite academic benchmark. The AA Index aggregates 10 standardized tests and rewards models that are strong across the board.**Long-context retrieval fidelity.**GPT-5.5’s launch materials cite 74% MRCR (multi-round context retrieval) accuracy at the 512K-1M token range. No competing model publishes data for this exact range in available sources.**Integration ecosystem breadth.**ChatGPT integration into Apple Intelligence (current via GPT-4o, GPT-5 confirmed for the iOS 26 upgrade in fall 2026), Microsoft Copilot, GitHub Copilot, and Visual Studio Code creates a distribution surface that no competitor matches in direct consumer-device reach. This is a deployment advantage, not a model-quality advantage, but it changes which AI most users encounter first. ### Where GPT-5.5 Lags**User preference in blind tests.**GPT-5.5 ranks below Claude Opus 4.7, Claude Opus 4.6, Gemini 3.1 Pro, and Muse Spark from Meta on LMArena human-preference blind evaluations as of late April 2026. The pattern is not new: GPT-5.2-high fell to rank 15 on LMArena in December 2025. Academic benchmark performance and user-preference performance have diverged consistently since GPT-5.**SWE-bench Pro (multi-file hard coding).**GPT-5.5’s 58.6% on SWE-bench Pro lags Claude Opus 4.7’s 64.3% by 5.7 points. SWE-bench Verified scores cluster much higher (88.7% vs 87.6%), but the harder Pro evaluation – which tests changes across multiple files in real codebases – separates the models more clearly. For professional software engineering on hard multi-repository tasks, Claude is the better data-supported choice as of dossier date.**Hallucination calibration.**GPT-5.5’s 86% AA-Omniscience hallucination rate is the highest ever recorded on that benchmark. Claude Opus 4.7 posts 36% on the same benchmark – a 50-percentage-point gap in calibration. This is the single most consequential benchmark gap for high-stakes use.**Unique insights in production.**Per the Suprmind Multi-Model Divergence Index (April 2026 Edition, n=1,324 production turns), ChatGPT surfaces 339 unique insights – 13.1% share, the lowest of five providers. Claude (631), Perplexity (636), Grok (509), and Gemini (463) all surface meaningfully more. ChatGPT has the lowest catch ratio at 0.38 – corrections made (111) divided by times caught (295). This is a “balanced generalist” pattern, not a “leading edge” pattern. See also: [AI catch ratio data →](https://suprmind.ai/hub/multi-model-ai-divergence-index/) ### Benchmark Comparison Table – Current Flagships Benchmark GPT-5.5 Claude Opus 4.7 Gemini 3.1 Pro DeepSeek V4 Pro GPQA Diamond 93.6% 94.2% 94.3% not reported AIME 2026 97.5% not reported not reported not reported SWE-bench Verified 88.7% 87.6% 75.6% 80.6% SWE-bench Pro 58.6% 64.3% not reported not reported ARC-AGI-2 85.0% not reported not reported not reported AA Intelligence Index 60 (rank 1) not reported not reported 51.5 LMArena (user pref) Below Opus 4.7, 4.6, Gemini 3.1 Pro Top tier Above GPT-5.5 not reported AA-Omniscience hallucination 86% 36% not reported not reported OSWorld-Verified 78.7% not reported not reported not reported Sources: o-mega.ai, OpenAI announcement, MathArena, Anthropic, Suprmind AI Hallucination Rates page. Last verified 2026-05-07. A note on the SWE-bench Verified line: OpenAI’s announcement and o-mega.ai both report 88.7%. A codersera independent developer guide reports 82.6%. The 88.7% figure appears in more sources and aligns with OpenAI launch materials. The 82.6% may reflect a different evaluation variant or an earlier internal result. Treat as conflict pending OpenAI system card publication. ## Accuracy and Hallucination ChatGPT’s hallucination profile is the single most important fact about how to use it well. The headline numbers are uncomfortable. They are also not the whole story. The summary below is anchored to [Suprmind’s AI Hallucination Rates and Benchmarks reference](https://suprmind.ai/hub/ai-hallucination-rates-and-benchmarks/) (May 2026 update), which is the canonical source for the data points cited here. ### The AA-Omniscience Paradox – 57% Accuracy, 86% Hallucination GPT-5.5 posts 57% accuracy on the Artificial Analysis Omniscience benchmark – the highest accuracy ever recorded on it. On the same benchmark, the hallucination rate is 86% – also the highest ever recorded. The AA-Omniscience Index (a composite that nets accuracy against hallucination, where positive is good) is 20. Positive, but not the highest in the field. What that means in practice: when GPT-5.5 reaches a knowledge boundary, it fabricates an answer 86% of the time rather than expressing uncertainty. The model has expanded both what it knows and how confidently it generates plausible content for what it does not know. Per Suprmind’s [AI Hallucination Rates and Benchmarks reference](https://suprmind.ai/hub/ai-hallucination-rates-and-benchmarks/), this is the “GPT-5.5 paradox” – knowledge without self-awareness, intensified at each generation. Earlier variants showed the same trajectory. GPT-5 posted 40.7% accuracy and over 10% Vectara new-dataset hallucination. GPT-5.2 hit 43.8% accuracy with approximately 78% AA-Omni hallucination. GPT-5.5 takes both numbers up. Accuracy improves. The gap between what the model knows and what it thinks it knows widens. For users, the rule of thumb is straightforward: ChatGPT is more accurate than older models on questions where answers exist in training data. It is more dangerous than older models on questions where answers do not. Open-domain factual queries, hyper-specific named entities, recent events past the training cutoff, niche-domain technical claims – all sit in the high-fabrication zone. See also: [GPT-5.5 hallucination rate →](https://suprmind.ai/hub/ai-hallucination-rates-and-benchmarks/) ### Citation Hallucination – Why Web Search Changes Everything The Columbia Journalism Review citation audit (March 2025) found ChatGPT produces fabricated or misattributed citations at a 67% rate when web browsing is disabled – the worst rate among the providers tested. Perplexity was lowest at 37%, still high. The pattern is deterministic: the model cannot distinguish “I learned this citation from training” from “I am generating a plausible citation pattern”. The output is structurally indistinguishable from a real citation. Enabling web search drops GPT-5’s hallucination rate from 47% to 9.6% per Suprmind’s AI Hallucination Rates and Benchmarks reference – a 37-point reduction that exceeds the effect of switching to a different model entirely. For citation-dependent work, web search is not optional. It is the difference between a usable tool and a misinformation generator. Per Suprmind’s benchmark page: GPT will produce confident, fabricated sources under citation pressure when browsing is off. This affects users on Free tier in non-browsing mode disproportionately, as well as any user who does not explicitly enable web search and any API call without the browsing tool. The mitigation is trivially available. The cost of not using it can be a fabricated case citation that survives an entire workflow. ### Summarization Faithfulness vs Open-Domain Knowledge Vectara measures summarization faithfulness – does the model stay true to the source document it has been asked to summarize? AA-Omniscience measures knowledge accuracy without a reference document. GPT-5.5 is much better at summarizing from source than at answering knowledge questions from memory. GPT-5 scored 1.4% on the Vectara old dataset (excellent) but exceeds 10% on the harder Vectara new dataset (no longer best-in-class). GPT-4.1 actually outperforms GPT-5 on the new dataset at 5.6%. The split has implications for use-case selection. ChatGPT’s most favorable hallucination profile is document-grounded analysis – RAG pipelines, document Q&A, contract review, earnings call summarization, PDF analysis. Per Suprmind’s AI Hallucination Rates and Benchmarks reference, GPT-5’s FACTS Grounding score of 61.8 exceeds Claude’s 51.3 on the same benchmark, suggesting GPT stays closer to provided source material when it has it. The practical translation: use ChatGPT for document-grounded workflows where you provide source material. Cross-check or default to Claude for open-domain advisory queries where the model must rely on stored knowledge. ### The Version Regression Pattern Across recent generations, each new GPT model is simultaneously more accurate and more likely to fabricate when uncertain. GPT-5 to GPT-5.2 to GPT-5.5 is a clean trajectory: accuracy up, hallucination up, calibration delta widening. The hallucination rate measures errors as a ratio of attempts. As models attempt harder questions rather than refusing, more attempts produce fabrications. This is a known consequence of OpenAI’s design choice to prioritize lower refusal rates. The 2025 sycophancy incident illustrated the tension. An RLHF update made GPT-4o excessively agreeable and reduced appropriate refusal on ambiguous questions. OpenAI rolled it back within 72 hours and pledged structural sycophancy evaluations. Four months later, in August 2025, Futurism reported OpenAI confirmed it was making GPT-5 “more sycophantic” after user feedback – effectively reversing the stated commitment. The pattern matters because newer is not safer on open-domain knowledge tasks. It is more accurate where it has data and less calibrated where it does not. See also: [ChatGPT hallucination by version →](https://suprmind.ai/hub/ai-hallucination-rates-and-benchmarks/) ## The Balanced Generalist – What the Production Data Shows Academic benchmarks rank GPT-5.5 first. User-preference benchmarks rank it below Claude Opus 4.7 and Gemini 3.1 Pro. Production multi-model data tells a third story, and that third story is the most useful one for picking AI tools for actual work. The Suprmind Multi-Model Divergence Index (April 2026 Edition) measured five providers – ChatGPT, Claude, Gemini, Grok, Perplexity – across 1,324 real production turns from 700 sessions across 299 external users. Every turn was scored for contradictions, corrections, and unique insights. The data shows where providers actually disagree, who catches whose errors, and which models surface signal others miss. ### Catch Ratio and Unique Insights Catch ratio measures corrections made divided by times caught. A ratio above 1.0 means a model corrects others more than it gets corrected. Below 1.0 means the opposite. Per the Suprmind Multi-Model Divergence Index, the 2026 April edition spread was: Perplexity 2.54, Claude 2.25, Grok 0.72, ChatGPT 0.38, Gemini 0.26. ChatGPT made 111 corrections. It was caught 295 times. The 2.66:1 ratio against it is the second-worst in the cohort. Unique insights followed the same pattern. Across 3,484 unique insights surfaced in the dataset, ChatGPT contributed 339 (13.1% share, the lowest). On critical-severity unique insights (severity ≥7), ChatGPT produced 85 – the lowest absolute count, 3.89 times fewer than Perplexity (331). The “default best model” framing that ChatGPT often gets in product comparisons is contradicted by the production data on insight generation. This is the editorial framing the data supports: ChatGPT is the most widely deployed AI platform – a real signal of product-market fit, integration, and accessibility. It is not, per production data, the model most likely to surface signal others missed or to catch its own errors. The right framing is “balanced generalist”, not “leading edge”. Knowing this changes how you should structure work that depends on getting the answer right. ### High-Stakes Calibration ChatGPT’s strongest signal in the Divergence Index is calibration improvement under pressure. The confident-contradicted rate drops from 39.6% on all turns to 36.2% on high-stakes turns – a 3.4-point delta, the second-largest improvement in the study after Claude (-7.5 points). Gemini barely improves (-1.1 points). ChatGPT becomes more accurate, not less, as stakes rise. Read carefully though: 36.2% means more than one in three high-stakes confident answers are contradicted by another provider. The improvement is real. The absolute level still leaves a third of high-stakes confident outputs contested. ### When to Use ChatGPT Alone vs When to Pair It Five orchestration patterns are supported by the data. Each names a specific gap where single-model ChatGPT use produces inferior outputs versus a paired approach.**High-stakes factual research.**Pair ChatGPT’s document-grounded summarization (FACTS 61.8) with Perplexity’s live web retrieval and citation apparatus. ChatGPT’s catch ratio of 0.38 and 67% citation hallucination rate without browsing make it a poor solo choice for citation-dependent research. Perplexity’s 37% citation rate and 2.54 catch ratio backstop the workflow.**Financial analysis.**Pair ChatGPT with Claude. The Financial domain has the highest disagreement rate of any domain at 72.1% per the Divergence Index. Three of every four financial-analysis turns contain material that another model would contradict. Claude’s high-stakes confident-contradicted rate of 26.4% versus ChatGPT’s 36.2% makes it the better calibration backstop on consequential financial claims.**Multi-repository software engineering.**Pair ChatGPT with Claude Opus 4.7. ChatGPT leads SWE-bench Verified at 88.7% but lags Claude on SWE-bench Pro (58.6% vs 64.3%) – the harder multi-file evaluation. Complex architectural changes crossing multiple repositories benefit from Claude’s review pass.**Business strategy and scenario analysis.**Pair ChatGPT with Grok. ChatGPT surfaces 339 unique insights versus Grok’s 509. In the Business Strategy domain, Gemini vs Grok is the most combative pair (59 contradictions). Grok’s contrarian outputs create high-value divergence points that ChatGPT alone does not generate.**Open-domain knowledge queries.**Pair ChatGPT with Claude. The 50-point AA-Omniscience hallucination gap (ChatGPT 86%, Claude 36%) means that on questions at the knowledge boundary, Claude refuses or hedges while ChatGPT continues generating. For high-consequence open-domain queries, this gap is the decision. See also: [ChatGPT vs Claude vs Gemini comparison →](https://suprmind.ai/hub/chatgpt/vs-other-ai/) ## Key Controversies and Safety Record OpenAI has navigated several public controversies, governance disputes, and regulatory actions that shaped the product. The four below are the ones most likely to come up in evaluation discussions in 2026. ### The Sycophancy Incident and What OpenAI Changed On April 25, 2025, an RLHF update to GPT-4o produced excessive agreeableness – the model validated false user claims, reversed correct prior statements when challenged, and produced sycophantic affirmations. Users widely documented the behavior. OpenAI rolled back the update within 72 hours (April 28-29) and Sam Altman acknowledged the problem on X. OpenAI’s post-mortem (April 28 and May 1, 2025) attributed the regression to over-weighting short-term user approval signals in the RLHF reward function and pledged structural sycophancy evaluations plus more oversight for gradual rollouts. Independent researchers at Georgetown Law subsequently noted sycophancy may be a structural feature of RLHF-trained systems rather than an isolated incident. TechCrunch in August 2025 framed it as “a dark pattern to turn users into profit”. Then, in August 2025, Futurism reported OpenAI confirmed it was making GPT-5 “more sycophantic” after user feedback. That contradicted the April commitment within four months. GPT-5.3 Instant in March 2026 specifically reduced “cringe” – over-declarative language and unnecessary moralizing preambles – addressing one axis of the user complaint, but the underlying tension between honesty optimization and approval optimization in RLHF has not been resolved. ### Copyright Lawsuits – NYT and Author Suits The New York Times sued OpenAI and Microsoft for copyright infringement on December 27, 2023, alleging GPT models were trained on NYT articles without permission and can regurgitate near-verbatim content. On March 26, 2025, Judge Sidney Stein of SDNY rejected OpenAI’s motion to dismiss and allowed direct and contributory copyright infringement claims to proceed. A federal judge later ordered OpenAI to produce 20 million de-identified conversation samples for training-data liability discovery. OpenAI maintains a “fair use” defense and published a response page at openai.com/new-york-times arguing AI training is transformative. As of May 2026, the case is in active discovery in SDNY. No trial date has been set. Multiple consolidated author copyright suits proceed alongside the NYT case in the same jurisdiction. Monitor weekly for status changes. ### Sam Altman Board Removal – What the Investigation Found OpenAI’s board fired CEO Sam Altman on November 17, 2023, citing a “pattern of deception” and lack of candor. Employee revolt and Microsoft pressure led to reinstatement five days later. The WilmerHale external investigation concluded in March 2024 that Altman’s behavior “did not warrant removal” and attributed the dismissal to a “breakdown in the relationship and loss of trust” – not to any specific finding of misconduct. No written investigation report was published. Altman was reinstated with an expanded board including Bret Taylor (chair) and Lawrence Summers. He stated he “could have handled the dispute with more grace and care”. The episode contributed to OpenAI’s later restructuring from non-profit control to public benefit company structure. In April 2026, Ronan Farrow published reporting that characterized board members as having been selected “in close consultation with” Altman. The framing is single-source as of dossier date and has not been independently corroborated, but it has reopened governance questions in industry coverage. ### Italian DPA Ban – Resolved Italy’s Garante temporarily banned ChatGPT on March 31, 2023, citing GDPR violations: no legal basis for mass data collection, unlawful processing of minor user data, lack of age verification. OpenAI complied within the deadline, introduced GDPR-specific privacy disclosures, age verification, and a training opt-out tool. Service was restored by May 2023. The action did not result in a formal GDPR fine. The episode established that EU data protection authorities can act against AI systems without waiting for EU AI Act enforcement. ## Sources Authoritative sources consulted in compiling this guide. For maintenance, monitor the URLs noted in the JSON SSOT section. - OpenAI – openai.com (announcements, pricing, business pages) - OpenAI Help Center – help.openai.com (feature documentation, Sora discontinuation notice) - OpenAI API documentation – platform.openai.com (pricing, model catalog, deprecations) - OpenAI Status – status.openai.com (incidents) - Suprmind Multi-Model Divergence Index – suprmind.ai/hub/multi-model-ai-divergence-index/ (production multi-model data) - Suprmind AI Hallucination Rates and Benchmarks – suprmind.ai/hub/ai-hallucination-rates-and-benchmarks/ (canonical hallucination data) - Artificial Analysis – artificialanalysis.ai (AA Intelligence Index, AA-Omniscience) - MathArena – matharena.ai (AIME 2026, HMMT, Math Overall) - LMArena – arena.ai/leaderboard (user preference rankings) - Columbia Journalism Review – cjr.org (citation accuracy audit, March 2025) - TechCrunch – techcrunch.com (launch coverage, Pro tier introduction) - o-mega.ai – GPT-5.5 complete guide and benchmark synthesis - DataCamp – datacamp.com (GPT-5.4 launch coverage) - 9to5Mac – 9to5mac.com (custom GPTs, GPT-5.3 Instant launch) - The Guardian – theguardian.com (Altman board investigation) - NPR, Reuters, lawfold.com – NYT lawsuit status - Futurism – futurism.com (sycophancy reporting August 2025) - TheNextWeb – thenextweb.com (Claude Opus 4.7 SWE-bench Pro coverage) Last verified 2026-05-07. FAQ ## Frequently Asked Questions What is ChatGPT? + ChatGPT is a conversational AI product developed by OpenAI that uses the GPT-5.5 language model as of April 2026 to answer questions, generate text, analyze documents, write and execute code, generate images, and complete multi-step tasks. It is available at chatgpt.com, on iOS and Android, on the desktop app, and via API. It is distinct from the underlying GPT models, which are accessible directly through OpenAI’s platform.openai.com API. What is the latest version of ChatGPT? + As of May 2026, the current flagship model is GPT-5.5, released April 23, 2026. It posts an Artificial Analysis Intelligence Index of 60 (rank 1 across all models), an AIME 2026 score of 97.5%, and SWE-bench Verified of 88.7%. Free tier uses GPT-5.3 Instant (with GPT-5.5 Instant rolling out). Plus uses GPT-5.5 Auto. Pro $200 adds GPT-5.5 Pro with extended compute. Is ChatGPT the same as GPT-5.5? + No. GPT-5.5 is the underlying model. ChatGPT is the product interface that routes queries to GPT-5.5 or other models depending on tier and query type. On Plus, the Auto selector may call GPT-5.4 or GPT-5.5 depending on complexity. You cannot confirm which model answered a specific query without accessing the Configure setting. Is ChatGPT free in 2026? + Yes. The Free tier at $0 provides access to GPT-5.3 Instant, limited to approximately 10 messages per 5-hour window, with access to the GPT Store. Free tier in the US displays advertisements as of February 9, 2026. Deep Research, Advanced Voice Mode, ChatGPT Agent mode, and Sora video generation require a paid plan. How much does ChatGPT Plus cost and what does it include? + Plus costs $20 per month. It includes GPT-5.4 and GPT-5.5 access via the Auto selector, 5x Free message limits, Advanced Voice Mode, Deep Research with 10 queries per month, image generation, ChatGPT Agent mode, Canvas, Tasks, and Custom GPT creation. File uploads up to 10 per message, 25 per Project, 80 per 3-hour rolling window. Does ChatGPT hallucinate? + Yes. Per Suprmind’s AI Hallucination Rates and Benchmarks reference (May 2026 update), GPT-5.5 posts an 86% AA-Omniscience hallucination rate – meaning that when the model reaches its knowledge boundary, it fabricates an answer 86% of the time rather than expressing uncertainty. With web search enabled, GPT-5’s hallucination rate drops from 47% to 9.6%. ChatGPT is most reliable when provided source material to work from (FACTS Grounding 61.8) and least reliable on open-domain factual queries without web access. How accurate is ChatGPT compared to Claude and Gemini? + On academic benchmarks (Artificial Analysis Intelligence Index), GPT-5.5 ranks first with a score of 60. On user preference in blind tests (LMArena), GPT-5.5 ranks below Claude Opus 4.7, Opus 4.6, Gemini 3.1 Pro, and Muse Spark. On hallucination calibration (AA-Omniscience), Claude Opus 4.7 posts 36% versus GPT-5.5’s 86% – a 50-point gap favoring Claude. The framing: GPT-5.5 knows more but fabricates more when it does not know. Can I trust ChatGPT for legal or medical questions? + For general orientation and document summarization, yes – with caveats. For citation-dependent legal work, no: ChatGPT’s citation hallucination rate is 67% when web search is disabled (CJR audit). For medical queries, the Medical domain sees the lowest disagreement rate among AI models (33.9%), but that still means roughly one in three medical turns would produce corrections in a multi-model setting. Per Suprmind’s AI Hallucination Rates and Benchmarks reference, enabling web search is the most effective mitigation in both domains. Why is ChatGPT ignoring my model selection? + This is documented behavior since August 2025: the Auto selector overrides manual model choices in some sessions, defaulting to GPT-5. Per user reports from October 2025, selecting GPT-4o, GPT-4.1, or o3 is sometimes overridden, with “retry” required to enforce the selection. OpenAI has not published a formal explanation or fix timeline. What is ChatGPT’s context window in 2026? + GPT-5.5 supports a 1.1 million token input context window and 128,000 token output window. At training speed, 1.1 million tokens represents approximately 800,000 words or roughly 12-16 full-length books. At the extreme end of the window, performance degrades: GPT-5.5’s MRCR (multi-round context retrieval) benchmark shows 74% accuracy in the 512K-1M token range. ## Stop guessing. Start cross-checking. Suprmind runs your prompt across ChatGPT, Claude, Gemini, Grok, and Perplexity in parallel. See where they agree, where they disagree, and which insights only one model surfaced — before you act. [Start Your Free Trial](/signup/spark) [See How It Works](https://suprmind.ai/hub/platform/) --- *Source: [https://suprmind.ai/hub/chatgpt/](https://suprmind.ai/hub/chatgpt/)* *Generated by FAII AI Tracker v3.3.0*