Claude vs OpenAI for coding: the short answer
There is no independent, like-for-like result in the available evidence that establishes a universal coding winner. A sensible first comparison is Claude Sonnet 5.5 (claude-sonnet-5-5) against GPT-6.1 Sol (gpt-6.1-sol): both list standard input rates of $2 and output rates of $10 per million tokens. Their published context windows are 1 million tokens for Sonnet 5.5 and 1.05 million for GPT-6.1 Sol. These are standard rates—not a promise of equal pricing across both models’ full context windows. In particular, Sol requests exceeding 272,000 input tokens have a different rate for the full request (see below). These specifications are not proof of equal coding quality. (Anthropic’s Sonnet 5.5 model documentation; OpenAI’s GPT-6.1 Sol API documentation.)
For more demanding coding work, you could also test Claude Opus 5.5 and GPT-6 Astra, but their standard listed rates differ: $4/$20 and $10/$50 per million input/output tokens, respectively. The available evidence does not compare those models on the same coding tasks and conditions. (Anthropic’s Opus 5.5 model documentation; OpenAI’s GPT-6 model guide.)
A third-party comparison suggests Claude for ambiguous requests and GPT for precise specifications. Treat that as a hypothesis to test—not a verified finding about these API models. (Morph’s Claude vs ChatGPT comparison.)
This article compares production API models, not Claude and ChatGPT subscriptions, Claude Code, or Codex. Coding-agent workflow claims are not evidence that one provider’s underlying API model is better.
Which models are worth comparing?
The official model documentation identifies Sonnet 5.5 and GPT-6.1 Sol as directly callable API models. Their model IDs are claude-sonnet-5-5 and gpt-6.1-sol. Anthropic describes Sonnet 5.5 as intended for coding, agent workloads, and tool use; OpenAI positions GPT-6.1 Sol for complex coding and says tool calling requires the Responses API. These are provider descriptions, not independent comparative results. (Anthropic’s Sonnet 5.5 model documentation; OpenAI’s GPT-6.1 Sol API documentation.)
| API model | Model ID | Standard input / output price per 1M tokens | Context window | Relevant API condition |
|---|---|---|---|---|
| Claude Sonnet 5.5 | claude-sonnet-5-5 |
$2 / $10 | 1M tokens | API model; supports tool use. Forced tool choice is unsupported and returns an error. |
| GPT-6.1 Sol | gpt-6.1-sol |
$2 / $10 | 1.05M tokens | API model; tool calling requires the Responses API. |
| Claude Opus 5.5 | claude-opus-5-5 |
$4 / $20 | 1M tokens | Anthropic describes it as built for long-running agentic coding and knowledge work. |
| GPT-6 Astra | Not specified here | $10 / $50 | Not specified here | OpenAI positions it as its most capable model. |
The rates above are the providers’ standard API token prices, with input and output billed separately. Pricing snapshot: checked November 12, 2026. OpenAI’s GPT-6 rates were checked against its model guide, dated October 2, 2026. Anthropic’s listed rates come from provider documentation captured earlier in this research and could not be rechecked in this pass; confirm their current applicability and your account terms before budgeting. Anthropic explicitly identifies its model prices as USD. (Anthropic’s pricing documentation; OpenAI’s GPT-6 model guide.)
The context figures are maximum model windows, not a promise that every request at that size has the same price or behavior. OpenAI documents that GPT-6.1 Sol API prompts exceeding 272,000 input tokens are charged at 2× the input and cached-input rates and 1.5× the output rate for the full request. At the listed standard uncached rates, that makes Sol’s rates for such a request equivalent to $4 per million input tokens and $15 per million output tokens. (OpenAI’s GPT-6.1 Sol API documentation.)
Anthropic documents Sonnet 5.5’s context window and notes that forced tool choice returns an error. Check the model-specific API documentation before carrying settings or tool-use patterns over from another model. (Anthropic’s Sonnet 5.5 model documentation; Sonnet 5.5 release notes.)
What do the coding benchmarks actually show?
The available results do not settle Claude versus OpenAI coding performance across the board. The supplied evidence includes provider-reported claims about different models and tasks, but not an independent, controlled comparison of the same Claude and OpenAI API models on the same coding workload.
OpenAI reports that GPT-6.1 Sol matches GPT-6 Astra on its DeepSWE v1.1 evaluation at roughly one-fifth the cost. That is an OpenAI-reported comparison between two OpenAI models, not a Claude-versus-OpenAI result. (OpenAI’s GPT-6.1 Sol announcement.) Anthropic’s Opus 5.5 announcement reports a web-app optimization example in which the model reduced load times across the app in 39 of 40 attempts. That is an Anthropic-reported example, not a head-to-head test against GPT. (Anthropic’s Opus 5.5 announcement.)
Morph separately reports DeepSWE results for Opus 5 and GPT-5.6 Sol. Those are older model versions and cannot establish the relative performance or task cost of Opus 5.5 and GPT-6.1 Sol. Likewise, comparisons of Claude Code and Codex concern coding-agent products and workflows, not a direct API-model comparison. (Morph’s comparison; AIThinkerLab’s Claude Code vs OpenAI Codex article.)
Keep the model version, task set, evaluation date, agent scaffold, and source attached to every score. Vendor-reported results and third-party observations are not interchangeable, and scores from different setups may not be comparable. Use benchmark claims to decide what to test—not as a guarantee of results in your repository.
What does API use cost in a worked example?
Suppose a request uses 100,000 input tokens and produces 10,000 output tokens, before any cached-input discount. This input amount is below Sol’s 272,000-token pricing threshold. Using the listed standard rates:
- Sonnet 5.5 or GPT-6.1 Sol: 0.1 × $2 + 0.01 × $10 = $0.30.
- Opus 5.5: 0.1 × $4 + 0.01 × $20 = $0.60.
- GPT-6 Astra: 0.1 × $10 + 0.01 × $50 = $1.50.
This is arithmetic from published token rates, not a measured coding-task cost. It assumes those token counts and excludes retries, cached input, and other applicable charges. A lower token price does not necessarily mean a lower cost per accepted fix: token volume, retries, and success rate matter too. (Anthropic’s pricing documentation; OpenAI’s API pricing documentation.)
How to choose for your production workload
Run a small, controlled evaluation before routing production work:
- Choose representative tasks. Include the work your system actually handles—for example, a clearly specified function change, an underspecified bug report, and a change spanning multiple files.
- Keep inputs and tools consistent. Use the same repository state, context, task instructions, and tool permissions. Record the exact model IDs and settings.
- Set acceptance criteria first. Check whether tests pass, the requested behavior is present, unrelated files remain unchanged, and a reviewer accepts the patch.
- Track the whole cost of a useful result. Record accepted changes, correction and review time, retries, latency, and input/output tokens. Estimate cost per accepted result from your own runs.
- Repeat tasks. One successful attempt is a demonstration, not a reliable estimate of production performance.
Start with Sonnet 5.5 and GPT-6.1 Sol if you want to compare models with equal listed standard token rates. Add Opus 5.5 or GPT-6 Astra if the work is difficult enough to justify testing a higher-priced model. If one model performs better on certain task types, route by task—or keep both available—rather than forcing a universal winner. OpenAI’s production guide similarly recommends measuring task success and latency against the workload. (OpenAI’s GPT-6 model guide.)
Bottom line: compare named API models against your own code and acceptance criteria. Sonnet 5.5 and GPT-6.1 Sol are a practical first pair to test based on their listed standard rates, but the available evidence does not establish that either Claude or OpenAI produces better coding results overall.
Model specifications and prices can change. Confirm current availability, features, rates, and applicable terms in the linked provider documentation before deployment or budgeting.
Sources
Claude Sonnet 5.5 — Claude Platform Docs
What's new in Claude Sonnet 5.5 — Claude Platform Docs
Claude Opus 5.5 — Claude Platform Docs
Pricing — Claude Platform Docs
GPT-6.1 Sol Model — OpenAI API