Compare AI models
| Specifications | ||
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 200k | 400k |
| These models have no shared benchmark scores. | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 39% |
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 33% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 50.4% | — |
| Overview | ||
| Company | Anthropic | OpenAI |
| Release date | Mar 4 2024 | Sep 15 2025 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
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Claude 3 Opus and GPT-5-Codex don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Claude 3 Opus shipped 560 days before GPT-5-Codex, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (Claude 3 Opus) vs 400k (GPT-5-Codex).
Direct benchmark comparisons are unavailable — Claude 3 Opus and GPT-5-Codex don't publish scores on any of the same benchmarks.