OpenAI launched GPT-5.5 on April 23 as what it calls \u201ca new class of intelligence for real work and powering agents,\u201d and the framing is deliberate. OpenAI says it\u2019s the most capable agentic AI model to date, built from the ground up to plan, use tools, check its own output, and work through tasks independently.
\nGPT-5.5 is the first retrained base model since GPT-4.5, co-designed with NVIDIA\u2019s GB200 and GB300 NVL72 rack-scale systems. The company says the practical difference is that when using GPT5.5, tasks that previously required multiple prompts and human \u2018course-correction\u2019 can now be handed off more completely. The model is rolling out to Plus, Pro, Business, and Enterprise users in ChatGPT and Codex. API access followed on April 24.
\nThe benchmarks
\nOpenAI\u2019s strongest performance claim is on Terminal-Bench 2.0, a benchmark that tests command-line workflows requiring planning and tool coordination in a sandboxed environment. GPT-5.5 scores 82.7%, against GPT-5.4\u2019s 75.1% and Claude Opus 4.7\u2019s 69.4%.
\nOn SWE-Bench Pro, which evaluates GitHub issue resolution, GPT-5.5 reaches 58.6%, solving more issues in a single pass than previous versions. OpenAI also introduced Expert-SWE, an internal benchmark where tasks carry a median estimated human completion time of 20 hours. GPT-5.5 scores 73.1%, up from GPT-5.4\u2019s 68.5%.
\nIn long-context reasoning, MRCR v2 at one million tokens, a retrieval benchmark testing whether a model can locate a specific answer buried in a large document, GPT-5.5 scores 74.0%, against GPT-5.4\u2019s 36.6%.
\nHowever, on MCP Atlas, Scale AI\u2019s Model Context Protocol tool-use benchmark, Claude Opus 4.7 leads at 79.1% and no score is recorded by GPT-5.5. OpenAI included that absence in its own benchmark table, which at least signals its confidence in the overall picture.
\nToken efficiency, pricing reality
\nAPI access is priced at US$5 per million input tokens and US$30 per million output tokens, exactly twice the rates for GPT-5.4. OpenAI\u2019s defence is that GPT-5.5 completes the same Codex tasks with fewer tokens than GPT-5.4, making effective costs roughly 20% higher once its efficiency is factored in, a claim that independent testing lab Artificial Analysis validated.
\nGPT-5.5 Pro, available to Pro, Business, and Enterprise users, is priced at US$30 per million input tokens and US$180 per million output tokens. It applies additional parallel test-time compute on harder problems and leads the list of publicly-available models on BrowseComp, OpenAI\u2019s agentic web-browsing benchmark, at 90.1%.
\nToken efficiency is worth stress-testing against actual workloads before committing to a model switch. At 10 million output tokens per month, GPT-5.5 standard costs US$300 against Claude Opus 4.7\u2019s US$250, a 20% that only pays off if the model\u2019s superior agentic performance means fewer task iterations and fewer retries, with the maths varying by use case.
\nIn practice
\nOpen AI says more than 85% of employees now use Codex weekly in their departments, including engineering and marketing. In one example, the communications team used GPT-5.5 to process six months of speaking request data, where the model was able to build a scoring and risk framework to help automate low-risk approvals.
\nGreg Brockman described the release as \u201ca real step forward towards the kind of computing that we expect in the future,\u201d and chief scientist Jakub Pachocki noted the last two years of model progress had felt \u201csurprisingly slow.\u201d
\nOpenAI says GPT-5.5 matches GPT-5.4\u2019s per-token latency in production serving while performing at a higher level of intelligence; larger, more capable models are often slower to serve, but that trade-off was avoided here.
\nWhether the benchmark leads translate into production gains for teams running real agentic pipelines is the question that will take the next few weeks to answer properly. The Terminal-Bench score is promising for unattended terminal agents and DevOps automation. The MCP Atlas gap is worth watching for anyone building heavily on tool-use orchestration.
\nSee also: OpenAI brings GPT-5.5 to Codex for coding taskse<\/p>\n
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\nThe post GPT-5.5 is OpenAI\u2019s most capable agentic AI model yet\u2013at twice the API price appeared first on AI News.<\/p>\n","protected":false},"excerpt":{"rendered":"
OpenAI launched GPT-5.5 on April 23 as what it calls \u201ca new class of intelligence for real work and powering agents,\u201d and the framing is deliberate. OpenAI says it\u2019s the most capable agentic AI model to date, built from the ground up to plan, use tools, check its own output, and work through tasks independently. [\u2026]<\/p>\n
The post GPT-5.5 is OpenAI\u2019s most capable agentic AI model yet\u2013at twice the API price<\/a> appeared first on AI News<\/a>.<\/p>\n<\/div>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-container-style":"default","site-container-layout":"default","site-sidebar-layout":"default","disable-article-header":"default","disable-site-header":"default","disable-site-footer":"default","disable-content-area-spacing":"default","footnotes":""},"categories":[1074,1,24,6,57],"tags":[3],"class_list":["post-2771","post","type-post","status-publish","format-standard","hentry","category-agentic-workflows","category-ai-and-ml","category-chatgpt","category-openai","category-world-of-work","tag-ai"],"yoast_head":"\n