Claude Opus 5 vs GPT-5.2-Codex: which should you choose in 2026?
Claude Opus 5 (by Anthropic) and GPT-5.2-Codex (by OpenAI) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.
No protocol-matched benchmark supports a controlled winner. Looking only at published point scores, Claude Opus 5 is higher on 1 benchmark (LiveBench), while GPT-5.2-Codex is higher on 0 benchmarks.
The evaluation setups are not fully aligned, so these are not controlled head-to-head wins.
GPT-5.2-Codex is about 2.1× cheaper on a blended 3:1 input/output basis ($4.81 vs $10.00 per 1M tokens).
Claude Opus 5 has the larger context window (1,000,000 tokens vs 400,000 tokens).
Choose Claude Opus 5 if…
- • you work with longer documents, transcripts, or codebases
Choose GPT-5.2-Codex if…
- • lower blended API cost matters for your workload
The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.
Performance benchmarks
Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.
| Benchmark | Claude Opus 5 | GPT-5.2-Codex |
|---|---|---|
A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework. Guardrail-aware score | — | — |
A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing. Accuracy | — | — |
A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state. Mean task reward | 83.4% OSWorld | — |
A long-horizon software-engineering benchmark with 113 original tasks graded by hand-written tests. Pass@1 | 74.0%±4.0 DataCurve | — |
A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests. Resolved | — | 72.8% SWE-bench |
Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol. Mean task success | — | — |
The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry. Accuracy | 93.2% Artificial Analysis | — |
A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged. Accuracy | 54.9% Artificial Analysis | — |
A contamination-resistant benchmark refreshed on a fixed release cadence. Scores from different LiveBench releases must never be compared as the same protocol. Mean of category averages Protocols differ or are incompletely disclosed; not counted as a controlled win | 80.1% LiveBench | 74.0% LiveBench |
Benchmark sources
- OSWorld-Verified Results
- DeepSWE 1.1 Leaderboard
- SWE-bench Verified Bash Only Leaderboard
- GPQA Diamond Benchmark Leaderboard
- Humanity's Last Exam Benchmark Leaderboard
- LiveBench 2026-06-25 Leaderboard
Reviewed evidence last updated 2026-08-09.
Pricing, capabilities, and model facts
| Feature | Claude Opus 5 | GPT-5.2-Codex |
|---|---|---|
| Context & model facts | ||
| Developer | Anthropic | OpenAI |
| API provider | Claude Opus 5 | OpenAI |
| Input context | 1,000,000 tokens | 400,000 tokens |
| Maximum output | 128,000 tokens | 128,000 tokens |
| Released | — | — |
| Added to Writingmate | Jul 24, 2026 | Jan 14, 2026 |
| License | — | — |
| Knowledge cutoff | — | — |
| Capabilities | ||
| Inputs | Text, Image, File | Text, Image |
| Outputs | Text | Text |
| Tool use | Yes | Yes |
| Reasoning | Yes | Yes |
| Vision | Yes | Yes |
| Image Generation | No | No |
| Video Generation | No | No |
| API pricing | ||
| Input (per 1M tokens) | $5.00 | $1.75 |
| Output (per 1M tokens) | $25.00 | $14.00 |
| Blended 3:1 input/output | $10.00 | $4.81 |
| API performance | ||
| p95 latency | Not measured | Not measured |
| Output throughput | Not measured | Not measured |
| Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table. | ||
Data sources
- Writingmate model catalog (pricing, limits, and availability)
Catalog data last updated Jul 24, 2026.
Why Pay for Multiple Subscriptions?
Comparing Claude Opus 5 from Anthropic with GPT-5.2-Codex from OpenAI? Instead of managing separate API keys and subscriptions, get both with Writingmate.
| Plan | Price | Claude Opus 5 | GPT-5.2-Codex | AI Images | AI Video |
|---|---|---|---|---|---|
Writingmate Pro Most popular | $20/mo | Ultimate required | Included | Nano Banana Pro, FLUX.2, DALL-E & more | Sora 2, VEO 3.1 |
Writingmate Ultimate Power users | $60/mo | Included | Included | Nano Banana Pro, FLUX.2, DALL-E & more | Sora 2, VEO 3.1 |
Claude Opus 5 vs GPT-5.2-Codex FAQ
Which is better, Claude Opus 5 or GPT-5.2-Codex?
No protocol-matched benchmark supports a controlled winner. Looking only at published point scores, Claude Opus 5 is higher on 1 benchmark (LiveBench), while GPT-5.2-Codex is higher on 0 benchmarks. The evaluation setups are not fully aligned, so these are not controlled head-to-head wins. GPT-5.2-Codex is about 2.1× cheaper on a blended 3:1 input/output basis ($4.81 vs $10.00 per 1M tokens). Claude Opus 5 has the larger context window (1,000,000 tokens vs 400,000 tokens).
Which model is cheaper to use through an API?
GPT-5.2-Codex is about 2.1× cheaper on a blended 3:1 input/output basis ($4.81 vs $10.00 per 1M tokens).
Which model supports more context?
Claude Opus 5 has the larger context window (1,000,000 tokens vs 400,000 tokens).
Can I switch between Claude Opus 5 and GPT-5.2-Codex?
Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.