Key Takeaways
- GPT-5.5 was released by OpenAI on April 23, 2026, with GPT-5.5 Instant becoming ChatGPT’s default model for free users on May 5, 2026.
- The model scores 93.6% on GPQA Diamond (PhD-level science questions) and 82.7% on Terminal-Bench 2.0, outperforming Claude Opus 4.7 by over 13 points on the latter benchmark.
- API pricing starts at $5 per million input tokens and $30 per million output tokens for the standard tier; GPT-5.5 Pro costs $30/M input and $180/M output.
- GPT-5.5 supports a 1 million token context window via the API and 400K tokens inside the Codex environment.
- The model is designed primarily for agentic and multi-step workflows: coding, research, data analysis, and operating software across tools autonomously.
- Compared to GPT-5.4, GPT-5.5 is more token-efficient, completing the same Codex tasks using significantly fewer tokens while matching per-token latency.
- Known weaknesses include higher hallucination rates than Claude Opus 4.7, reduced quality on Go and Rust compared to Python/TypeScript, and underperformance on casual single-turn chat tasks.
- ChatGPT Plus ($20/month) includes GPT-5.5 access with usage caps; ChatGPT Pro starts at $100/month for heavier personal use.
- SWE-bench Pro score stands at 58.6%, tracking real GitHub issue resolution end-to-end in a single pass.
OpenAI’s model releases have been coming fast. Since GPT-5 debuted in August 2025, the company has iterated through GPT-5.2 (December 2025), GPT-5.4 (early 2026), and now GPT-5.5, released April 23, 2026. Each step has sharpened something specific: reasoning depth, coding reliability, or agentic reach.
GPT-5.5 is marketed as OpenAI’s “smartest and most intuitive” model to date. But that phrase covers a lot of ground. Is it genuinely smarter for everyday tasks, or does it shine mainly in the narrow category of autonomous agent workflows? This review pulls together benchmarks, real-world pricing, user feedback from Reddit and developer forums, and head-to-head comparisons with Claude Opus 4.7 and Gemini 3.1 Pro to give you a clear picture.
If you are a developer building agents, a researcher running complex analysis, or a power user wondering whether the price increase from GPT-5.4 is justified, read on. This covers everything you need to decide.
What Is GPT-5.5?
GPT-5.5 is a large language model from OpenAI, positioned as the successor to GPT-5.4 and the current top of the company’s non-research model lineup. It was released to API users and ChatGPT Plus/Pro subscribers on April 23, 2026. GPT-5.5 Instant, a lighter version optimized for speed and low cost, became the default model for free-tier ChatGPT users on May 5, 2026, replacing GPT-5.3 Instant.
Unlike the “o-series” reasoning models (o3, o4-mini) that OpenAI releases separately, GPT-5.5 is a unified system. It can route tasks internally between fast inference and deeper reasoning without the user having to switch model toggles. The architecture processes text and images as input; it does not natively generate audio or video output, though it integrates with OpenAI’s Realtime API for voice applications.
The model’s design philosophy has shifted compared to earlier GPT-5 versions. Where GPT-5 and GPT-5.2 were built to be broadly excellent across chat, creative writing, and reasoning, GPT-5.5 was optimized heavily for agentic execution: the ability to plan, use external tools, check its own work, and continue a task over many steps without human intervention. According to OpenAI’s announcement, users can hand GPT-5.5 a messy, multi-part task and the model will plan, navigate ambiguity, and keep going until finished.
GPT-5.5 Features
Agentic Execution
GPT-5.5’s most differentiated capability is autonomous task completion. It can write and debug code, run terminal commands, search the web, analyze data, and create documents or spreadsheets in sequence, moving across tools without stopping for step-by-step user instructions. On Terminal-Bench 2.0, which tests complex command-line workflows requiring planning and tool coordination, GPT-5.5 scores 82.7%, compared to Claude Opus 4.7’s 69.4%. This is the first time since GPT-4 that OpenAI has held a clear lead over Anthropic on agentic execution benchmarks.
Long Context Window
The API context window sits at 1 million tokens, sufficient to process entire large codebases, multi-hour conversation logs, or extensive document sets in a single pass. The Codex environment supports up to 400K tokens. According to Vellum’s breakdown, this long-context performance is a qualitative improvement over GPT-5.4 for workflows that involve processing very large inputs.
Multimodal Input
GPT-5.5 accepts both text and images as input within a single unified architecture. It can read and reason about screenshots, diagrams, charts, and documents. Computer-use screen reading is available inside the Codex environment, allowing the model to interact with software interfaces visually. However, the model does not generate images, audio, or video natively; those outputs require separate OpenAI API endpoints.
Token Efficiency
One of the under-reported improvements in GPT-5.5 is token efficiency. The model completes the same Codex tasks using significantly fewer output tokens than GPT-5.4 while matching per-token latency in real-world serving. For high-volume API users, this reduces costs even where the per-token rate is higher, because fewer tokens are used per task completion.
Safety and Reliability
OpenAI states that GPT-5.5 shipped with its strongest set of safeguards to date, having been evaluated across the full suite of internal safety and preparedness frameworks plus external red-teaming. The GPT-5.5 System Card details specific evaluations on challenging prompts. OpenAI also limited GPT-5.5’s access to certain cybersecurity capabilities following external criticism, a step that removed some offensive security functionality present in earlier previews.
MMMU-Pro and Multimodal Reasoning
On MMMU-Pro, a benchmark for multimodal reasoning that requires integrating information across text and images, GPT-5.5 scores 76, compared to 69.2 for GPT-5.4. This is a meaningful step forward for tasks like analyzing research papers with diagrams, understanding UI screenshots, and working with data in non-text formats.
GPT-5.5 Pricing
GPT-5.5 is available through two access paths: ChatGPT subscription plans for end users and the OpenAI API for developers.
ChatGPT Subscription Plans
- Free: Access to GPT-5.5 Instant (the lighter, faster variant), with standard usage limits.
- ChatGPT Plus ($20/month): Access to full GPT-5.5 with usage caps; the most popular subscription tier.
- ChatGPT Pro ($100/month): Higher usage limits for heavy personal use; suitable for professionals running long agent tasks daily.
- ChatGPT Pro ($200/month): Power-user tier with expanded tool access and higher limits for demanding workflows.
- ChatGPT Business and Enterprise: Team and enterprise pricing available; contact OpenAI for details. Includes admin controls and data privacy options.
API Pricing
- GPT-5.5 Standard: $5 per million input tokens, $30 per million output tokens.
- GPT-5.5 Pro: $30 per million input tokens, $180 per million output tokens.
- Batch and Flex pricing: Available at half the standard rate for asynchronous workloads where speed is not critical.
For reference, APIdog’s pricing breakdown confirms that GPT-5.5 is priced higher than GPT-5.4, but OpenAI argues the token efficiency gains offset the rate increase for typical production workloads. Developers running high-volume pipelines should benchmark actual cost per completed task rather than comparing per-token rates alone.
GPT-5.5 Pros and Cons
Pros:
- Best-in-class agentic execution: 82.7% on Terminal-Bench 2.0, outpacing Claude Opus 4.7 by over 13 points.
- Strong PhD-level science reasoning: 93.6% on GPQA Diamond.
- 1 million token context window handles entire codebases or large document sets.
- Token efficiency improvements reduce actual cost per task despite higher per-token rate.
- Real GitHub issue resolution at 58.6% on SWE-bench Pro, completing tasks end-to-end in a single pass.
- Integrated smart routing between fast and deep reasoning without user-side model switching.
- Strong performance on Python and TypeScript with idiomatic, accurate suggestions.
Cons:
- Higher hallucination rate than Claude Opus 4.7: roughly 86% on a long-form factuality test, compared to 36% for Opus 4.7 according to MindStudio’s review.
- Weaker on Go, Rust, and niche frameworks compared to Python and TypeScript.
- Not optimized for casual conversation, creative writing, or single-turn Q&A tasks.
- Pure chat debugging (without code execution access) drops in quality significantly.
- API pricing is approximately double GPT-5.4 rates, which adds up at scale.
- Tendency to make overly conservative code changes, which improves token efficiency but can reduce correctness on complex refactoring tasks.
- Reddit users within the first 10 days of launch reported multiple instances of GPT-5.5 “confidently inventing facts,” a pattern that did not appear as frequently in GPT-5.4 testing.
GPT-5.5 vs Alternatives
The three frontier models at the top of the market in May 2026 are GPT-5.5, Claude Opus 4.7 from Anthropic, and Gemini 3.1 Pro from Google. On the LM Council AI benchmarks, all three sit within three points of each other on aggregate intelligence scores, so the choice comes down to specific strengths.
GPT-5.5 vs Claude Opus 4.7
Claude Opus 4.7 leads on two important dimensions: coding and factual accuracy. It scores 87.6% on SWE-bench Verified, compared to GPT-5.5’s 58.6% on SWE-bench Pro (note: these are different test variants, so direct comparison is imprecise). More importantly, Opus 4.7’s hallucination rate on long-form factuality tests is dramatically lower at 36%, versus GPT-5.5’s roughly 86%. For tasks where a user cannot easily verify the model’s output, Claude Opus 4.7 is the safer choice.
GPT-5.5 wins on agentic execution. Its Terminal-Bench 2.0 score of 82.7% is over 13 points ahead of Opus 4.7’s 69.4%, and on OSWorld (computer use) it scores 78.7%, marking the first time OpenAI has led Anthropic on agentic benchmarks since GPT-4. According to Attainment Labs’ comparison, developers running autonomous agent pipelines should lean toward GPT-5.5, while those who need a reliable research or writing assistant should stay with Claude Opus 4.7.
GPT-5.5 vs Gemini 3.1 Pro
Gemini 3.1 Pro from Google is the most cost-efficient of the three at approximately $12 per million output tokens, less than half the cost of GPT-5.5 or Claude Opus 4.7. It also leads on raw reasoning benchmarks and offers native multimodal support handling text, images, audio, and video simultaneously within one architecture. GPT-5.5 beats Gemini 3.1 Pro on agentic tasks, but for organizations where cost matters and multimodal input variety is important, Gemini 3.1 Pro is a strong alternative. For pure coding agent work, GPT-5.5 holds the performance edge.
| Model | Terminal-Bench 2.0 | GPQA Diamond | Output Cost (per 1M tokens) | Context Window |
|---|---|---|---|---|
| GPT-5.5 | 82.7% | 93.6% | $30 | 1M tokens |
| Claude Opus 4.7 | 69.4% | N/A | ~$30 | 200K tokens |
| Gemini 3.1 Pro | N/A | N/A | ~$12 | 1M tokens |
Who Is GPT-5.5 Best For?
Software developers and DevOps engineers building automated pipelines will get the most value from GPT-5.5. Its Terminal-Bench lead and SWE-bench Pro results show it can resolve real GitHub issues and execute complex command-line workflows autonomously. Python and TypeScript projects benefit most; Go and Rust projects will see more variation in output quality.
Researchers and analysts running complex, multi-step investigations across large document sets will find the 1M token context window and GPQA Diamond score (93.6%) valuable. The model handles long contexts well and reasons through PhD-level science questions more reliably than its predecessors.
Product and operations teams using AI agents to automate workflows across tools (spreadsheets, documents, browser automation) will benefit from GPT-5.5’s stronger agentic architecture. The ability to give the model a messy multi-part task and trust it to plan and complete it reduces the need for detailed step-by-step prompting.
Casual ChatGPT users who mostly chat, write, or ask single questions will not see a meaningful upgrade from GPT-5.5 over GPT-5.4 or even GPT-5.2. GPT-5.5 Instant (available on the free plan) covers basic use cases well. The $20/month Plus plan is sufficient for most individual users.
Users who need high factual reliability in outputs they cannot easily verify, such as medical, legal, or financial research summaries, should be cautious. The hallucination rate data from MindStudio’s review suggests Claude Opus 4.7 is more reliable in these contexts.
Our Verdict
GPT-5.5 is genuinely OpenAI’s most capable model to date for the specific tasks it was built for. If your work involves autonomous agents, long-context processing, or multi-step tool-use pipelines, GPT-5.5 earns its position at the top of the leaderboard. The Terminal-Bench and GPQA numbers are real improvements, not benchmark-chasing.
The caveats matter, though. The hallucination problem documented in early reviews is a real concern for anyone who can’t fact-check outputs. The pricing jump from GPT-5.4 to GPT-5.5 is significant, and the token-efficiency argument needs to be validated for your specific use case before committing to API migration. For chat-based work, creative writing, or straightforward Q&A, GPT-5.5 is not a clear upgrade over what came before.
Rating: 4.2 out of 5 for developers and agent builders. 3.4 out of 5 for general-purpose chat users.
If you’re a developer or researcher who pushes AI into complex multi-step workflows, GPT-5.5 is worth testing on your actual tasks. Start with the API’s Batch pricing at half rate, measure cost-per-completed-task against GPT-5.4, and decide from real data rather than benchmarks alone. Access GPT-5.5 via the OpenAI platform or through ChatGPT Plus.
Frequently Asked Questions
Is GPT-5.5 available to free ChatGPT users?
Yes, GPT-5.5 Instant became the default model for free-tier ChatGPT users on May 5, 2026. Free users get access to this lighter, faster variant with standard usage limits. Full GPT-5.5 with higher capability is available on the Plus plan at $20/month and Pro plans starting at $100/month.
What is GPT-5.5’s context window?
GPT-5.5 supports a 1 million token context window via the API, sufficient to process large codebases or extensive document sets in a single pass. Inside the Codex environment, the context window is 400K tokens. This is a significant expansion over earlier GPT-5 variants.
How does GPT-5.5 compare to Claude Opus 4.7?
GPT-5.5 leads Claude Opus 4.7 on agentic benchmarks: 82.7% vs 69.4% on Terminal-Bench 2.0. Claude Opus 4.7 leads on coding (87.6% on SWE-bench Verified) and has a dramatically lower hallucination rate on long-form factuality tasks. For autonomous agents, GPT-5.5 wins. For research and writing where accuracy matters, Claude Opus 4.7 is safer.
What does GPT-5.5 cost on the API?
Standard GPT-5.5 API pricing is $5 per million input tokens and $30 per million output tokens. GPT-5.5 Pro is priced at $30/M input and $180/M output. Batch and Flex pricing for asynchronous workloads is available at half the standard rate. Source: APIdog’s pricing guide.
Is GPT-5.5 good for creative writing?
GPT-5.5 is not optimized for creative writing or casual conversation. It was built around agentic execution and complex reasoning tasks. For creative writing, GPT-5.4, Claude Opus 4.7, or even GPT-5.2 may produce better results because they were trained with broader conversational and creative objectives.
What are the main limitations of GPT-5.5?
The key limitations are: a higher hallucination rate than Claude Opus 4.7 on factuality-focused tasks, reduced quality on Go and Rust code compared to Python and TypeScript, weaker performance on non-agentic single-turn tasks, and a tendency to make overly conservative code changes in refactoring scenarios. The model is also priced significantly higher than GPT-5.4.
When did GPT-5.5 come out?
GPT-5.5 Thinking and GPT-5.5 Pro were released on April 23, 2026. GPT-5.5 became available in the API on April 24, 2026. GPT-5.5 Instant was released to free-tier ChatGPT users on May 5, 2026.
Is GPT-5.5 multimodal?
GPT-5.5 accepts text and images as input within a unified architecture. It can read screenshots, diagrams, and documents. However, it does not natively generate images, audio, or video; those require separate OpenAI API endpoints. Audio and voice features are available through the Realtime API integration.
Does GPT-5.5 hallucinate more than GPT-5.4?
Early user reports and MindStudio’s independent review flagged a higher rate of confident factual errors in GPT-5.5 compared to GPT-5.4. Reddit’s r/OpenAI community documented 14 separate complaint posts about GPT-5.5 inventing facts within the first 10 days of launch. This appears to be a trade-off tied to the model’s more aggressive agentic planning behavior. For high-stakes fact-dependent tasks, extra verification is recommended.
What is GPT-5.5 best for?
GPT-5.5 is best for developers building autonomous agents, researchers processing large document sets, and teams automating multi-step workflows across tools. It excels at coding in Python and TypeScript, long-context analysis, and complex task planning where the model can use tools and iterate on its own. It is not the best choice for casual chatting, creative writing, or single-question Q&A.
