# GPT-5.5: pricing, crowd verdict, pros and cons (2026)

> OpenAI's agentic flagship: 1M context, SOTA ARC-AGI-2 and Terminal-Bench 2.0, $5/$30 per 1M tokens.

Source: [GLAD-AI-TOR](https://glad-ia-tor.com) · Full page: https://glad-ia-tor.com/tool/gpt-5-5
Arena: llm-models · Crowd score: 57% recommend (3 votes, Bayesian-smoothed) · Price: $30/1M out

OpenAI's flagship reasoning model, released April 23, 2026. Built for agentic coding, computer use, and long-horizon knowledge work, with a 1,050,000-token context window and 128K max output. Accepts text and image input, outputs text, with function calling, structured outputs, and hosted agent tools via the Responses API.

## Key facts

- provider: OpenAI
- contextWindow: 1M tokens (1,050,000)
- priceIn: $5/1M in
- priceOut: $30/1M out
- modalities: text, vision (image input, text output)
- openWeights: no

## Ratings (editorial, 1-5)

- reasoning: 5/5
- coding: 4.5/5
- writing: 4/5
- speed: 3.5/5
- valueForMoney: 3/5

## Pros

- 1M-token context window (1,050,000) with 128K max output and reasoning effort tunable from none to xhigh
- State-of-the-art ARC-AGI-2 at 85.0% (vs 73.3% for GPT-5.4) and Terminal-Bench 2.0 at 82.7%
- Strong agentic coding autonomy: devs report it one-shots tasks that took GPT-5.4 multiple turns and fixes its own mistakes; +50 points on Code Arena vs GPT-5.4
- Aggressive discounts: 90% off cached input ($0.50/1M) and 50% off via Batch or Flex ($2.50/$15)
- Fast for a frontier reasoner: devs say it is the first GPT model comfortable to run at medium or low thinking effort

## Cons

- List price doubled vs GPT-5.4 ($5/$30 vs $2.50/$15) for the same 1M-token context window
- Overly literal instruction-following: devs report it fails to infer intent in obvious places where Claude succeeds
- Trails Claude Opus 4.8 on SWE-bench Pro (58.6% vs 69.2%); HN developers still favor Claude roughly 2:1 for coding
- Sometimes too conservative with code changes or skips deep reasoning entirely, answering immediately on complex prompts
- Long-context surcharge: prompts over 272K input tokens are billed 2x input and 1.5x output for the whole session

## Best for

- agentic coding
- long-context analysis
- computer-use agents
- terminal and CLI automation

## Verdict

Pick GPT-5.5 over GPT-5.4 if you need stronger agentic autonomy, terminal-heavy workflows, or SOTA abstract reasoning, but know the list price doubled from GPT-5.4's $2.50/$15 to $5/$30 while the 1M-token context stayed the same. Teams doing high-stakes multi-file refactoring may still prefer Claude Opus, which leads SWE-bench Pro (69.2% vs 58.6%) and infers intent better from loose prompts. Budget-sensitive users should mind the 272K-token surcharge and reports of faster limit burn, and lean on caching, Batch, or Flex to halve costs.

## Pricing note

Standard tier $5/$30 per 1M tokens (cached input $0.50), double GPT-5.4's $2.50/$15; Batch/Flex $2.50/$15; Priority $12.50/$75; GPT-5.5 Pro $30/$180; prompts over 272K input tokens billed 2x in / 1.5x out.

## Alternatives and head-to-heads

- [Claude Haiku 4.5](https://glad-ia-tor.com/tool/claude-haiku-4-5) (crowd score 67%) · [GPT-5.5 vs Claude Haiku 4.5](https://glad-ia-tor.com/vs/gpt-5-5-vs-claude-haiku-4-5)
- [Claude Fable 5](https://glad-ia-tor.com/tool/claude-fable-5) (crowd score 63%) · [GPT-5.5 vs Claude Fable 5](https://glad-ia-tor.com/vs/gpt-5-5-vs-claude-fable-5)
- [Claude Opus 4.7](https://glad-ia-tor.com/tool/claude-opus-4-7) (crowd score 57%) · [GPT-5.5 vs Claude Opus 4.7](https://glad-ia-tor.com/vs/gpt-5-5-vs-claude-opus-4-7)
- [Claude Sonnet 5](https://glad-ia-tor.com/tool/claude-sonnet-5) (crowd score 57%) · [GPT-5.5 vs Claude Sonnet 5](https://glad-ia-tor.com/vs/gpt-5-5-vs-claude-sonnet-5)

Full ranking: https://glad-ia-tor.com/hall-of-fame/llm-models

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