Short answer: The available comparable evidence does not establish an overall winner for production work. Choose GPT-5.4 when its Responses API tools—especially computer use—fit your application. Consider Claude Opus 5.5 for long-running agentic coding or knowledge work. Then test both against your own acceptance criteria. Their published API rates differ, but actual workload cost depends on token use, caching, context length, and tool charges.
This comparison is between API models, not ChatGPT and a Claude subscription, or coding products such as Codex and Claude Code. As of November 10, 2026, Anthropic marks Opus 4.6 as legacy and recommends considering a move to Opus 5.5. (Anthropic Opus 4.6 documentation; Anthropic Opus 5.5 documentation)
Quick comparison
| OpenAI GPT-5.4 | Anthropic Claude Opus 5.5 | |
|---|---|---|
| API model ID | gpt-5.4 (snapshot: gpt-5.4-2026-03-05) |
claude-opus-5-5 |
| Context window | 1.05 million tokens | 1 million tokens |
| Maximum output | 128,000 tokens | 128,000 tokens |
| Standard input price | $2.50 per million tokens | $4 per million tokens |
| Standard output price | $15 per million tokens | $20 per million tokens |
| Relevant documented features | Text and image input; Responses API tools include computer use, web search, file search, and code interpreter | Text and image input; Anthropic describes Opus 5.5 for long-running agentic coding and knowledge work |
These are provider-listed specifications and rates, not a performance ranking. OpenAI documents a long-context pricing condition for GPT-5.4; Anthropic’s model and pricing details are on its own documentation pages. (OpenAI GPT-5.4 documentation; Anthropic Opus 5.5 documentation; Anthropic pricing)
Which model is better for your workload?
Choose GPT-5.4 when its API tools match the job
GPT-5.4 supports computer use and other tools through OpenAI’s Responses API, alongside function calling and structured outputs. That makes it a candidate when your application needs the model to work with screenshots or use supported tools—not merely generate text. Whether it is the better choice still depends on task success, reliability, and the cost of the complete tool workflow. (OpenAI GPT-5.4 documentation)
Evaluate Opus 5.5 for sustained coding or knowledge work
Anthropic describes Opus 5.5 as built for long-running agentic coding and knowledge work. That is the provider’s intended-use description, not independent proof that it will outperform GPT-5.4 on your repository or application. (Anthropic Opus 5.5 documentation)
Don’t treat an older head-to-head as a current verdict
A March 2026 reviewer compared GPT-5.4 with Claude Opus 4.6, not Opus 5.5. In one one-shot world-clock app test, the reviewer reported that GPT-5.4 produced more polished visuals but had drifting time synchronization, while Claude handled synchronization correctly with less polished visuals. The same reviewer recommended routing coding tasks by type. This is one author’s anecdote—not a controlled, repeatable API evaluation—and it does not establish how GPT-5.4 compares with Opus 5.5. The reviewer’s benchmark table also reported different leaders across measures, but the article did not provide the original benchmark links or methodology. (Thomas Wiegold’s review)
Practical verdict: Start with the API model whose documented tools and operating pattern best fit your use case, but don’t choose a production winner from a single anecdote or an unattributed benchmark table. For coding, run both on the same real task and compare verified results, review effort, latency, and cost.
Production API pricing: a worked example
The provider-listed standard rates are $2.50 per million input tokens and $15 per million output tokens for GPT-5.4, compared with $4 per million input tokens and $20 per million output tokens for Opus 5.5. Prices are in USD. This is API usage pricing; it is not a ChatGPT or Claude subscription price. (OpenAI GPT-5.4 documentation; Anthropic pricing)
Illustrative calculation: Suppose the workload totals 1 million input tokens and 100,000 output tokens in a billing period, split across separate requests so that each GPT-5.4 request has no more than 272,000 input tokens. Assume uncached standard pricing, with no tools or other charges:
- GPT-5.4:
(1 × $2.50) + (0.1 × $15) = $4.00 - Opus 5.5:
(1 × $4) + (0.1 × $20) = $6.00
This example applies each provider’s listed per-token rate to the same assumed token counts. It is not a forecast for a real application: models can use different numbers of tokens for equivalent work, and actual input/output usage may differ. Anthropic notes that models from Opus 4.7 onward use a tokenizer that produces approximately 30% more tokens for the same text than earlier Claude models, with the exact difference depending on the workload. Measure billed usage from real requests before treating a token-based estimate as a budget. (Anthropic pricing)
GPT-5.4 long-context caveat: OpenAI says prompts with more than 272,000 input tokens are priced at 2× input and 1.5× output for the full session. The threshold applies to the request’s input length, not the billing-period aggregate: many separate requests below the threshold do not trigger that condition just because their monthly input total exceeds 272,000 tokens. (OpenAI GPT-5.4 documentation)
API identifiers and capabilities to check before launch
- OpenAI lists
gpt-5.4and the pinned snapshotgpt-5.4-2026-03-05. Its model page lists text and image input, a 1.05-million-token context window, and 128,000 maximum output tokens. It also lists Responses API support for tools including computer use, web search, file search, and code interpreter. (OpenAI GPT-5.4 documentation) - Anthropic lists the Claude API ID
claude-opus-5-5. Its model page lists a one-million-token context window, 128,000 maximum output tokens, text and image input, and text output. Anthropic describes the model as built for long-running agentic coding and knowledge work. (Anthropic Opus 5.5 documentation) - If you specifically need to reproduce the earlier GPT-5.4 vs Opus 4.6 comparison, Anthropic lists Opus 4.6 as
claude-opus-4-6and marks it legacy. Its listed standard rates are $5 per million input tokens and $25 per million output tokens. Don’t substitute those Opus 4.6 figures or review findings for Opus 5.5 without saying so. (Anthropic Opus 4.6 documentation)
Provider features can depend on API, platform, and request configuration. Confirm the documentation for the integration you intend to deploy rather than assuming a feature in one provider’s tool stack is directly equivalent to another’s.
How to make the production choice
Run a small, controlled evaluation before routing real traffic:
- Select representative requests. Include the tasks that matter to your product—such as a normal request, a difficult case, and a failure-prone edge case.
- Set the same success criteria. Define what an acceptable answer or completed task looks like before comparing outputs.
- Keep test conditions consistent. Use comparable context, instructions, and tool access where the APIs allow it; note differences you cannot equalize.
- Repeat the test. A single successful or failed response is not enough to estimate reliability.
- Record the outcomes that affect your decision: task success, factual or code errors, human review and correction time, latency, billed input/output tokens, and any tool charges.
- Verify independently. Run tests, inspect outputs, and check side effects yourself. A model’s claim that it completed a task is not proof that it did.
If one model wins on a high-volume, well-defined task while the other performs better on a distinct complex workflow, routing by task may be more useful than forcing a single provider choice. Base that split on your measured results, not on the model names alone.
Bottom line
For a production API decision, GPT-5.4 has the lower published standard token rates and documented Responses API computer-use support; Claude Opus 5.5 is Anthropic’s Opus model positioned for long-running agentic coding and knowledge work. Those facts help shortlist models, but they do not prove which will produce better results for your workload. Compare the exact API models on your own tasks, include actual billed usage and review effort, and make the final choice from those results.
Sources
- OpenAI GPT-5.4 API model documentation
- Anthropic Claude Opus 5.5 model documentation
- Anthropic Claude Opus 4.6 model documentation
- Anthropic API pricing documentation
- Thomas Wiegold, “I Tested GPT 5.4 Against Every Rival” — author-reported, single-test comparison with Opus 4.6; not an official or controlled evaluation.
Sources
Claude Opus 5.5 | Claude Platform Docs
Claude Opus 4.6 | Claude Platform Docs
Pricing | Claude Platform Docs
I Tested GPT 5.4 Against Every Rival — Here's My Honest Review