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. | 1M | 400k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $10.00Verified organizations only | — |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $50.00 | — |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.25 | — |
| $4,500Anthropic list price | — | |
| 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. | — | 45% |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | — | 46% |
Terminal-Bench 4.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Version 4.0 recalibrated how much time, CPU and memory each task gets, removed eight tasks and fixed nineteen, so fewer runs fail for reasons that have nothing to do with the model. Scores are not comparable with earlier versions. Higher is better. | 60.9% | — |
De novo binder design (24 hr)Protein design — de novo protein binder design within a 24-hour budget, as reported by Anthropic | 79.1% | — |
CyScenarioBenchCybersecurity — multi-step cybersecurity scenarios; each lab runs its own unique task set, so scores from different labs do not compare | 61.7% | — |
CVE RediscoveryCybersecurity — Anthropic internal evaluation: share of 1,829 published CVEs a model finds on its own from a snapshot of the project before the fix | 78.3% | — |
BioMysteryBench · hardBiology — Real unsolved-style biology puzzles — the AI has to reason its way to an answer the way a research biologist would. The “hard” split contains the toughest cases. Higher is better. | 44.1% | — |
BioMysteryBench · human solvedBiology — Real biology puzzles that human experts have managed to crack — can the AI reach the same answers? Higher is better. | 90.3% | — |
| Overview | ||
| Company | Anthropic | OpenAI |
| Release date | Sep 1 2026 | Dec 18 2025 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Claude Mythos 5.1vsGemini 4 CarbonGPT-5.2-CodexvsGemini 4 CarbonClaude Mythos 5.1vsMuse EmberGPT-5.2-CodexvsMuse EmberClaude Mythos 5.1vsGrok 4.7GPT-5.2-CodexvsGrok 4.7Claude Mythos 5.1vsDeepSeek-V4.1-Flash-1017GPT-5.2-CodexvsDeepSeek-V4.1-Flash-1017Claude Mythos 5.1vsMistral Large 4GPT-5.2-CodexvsMistral Large 4Claude Mythos 5.1vsKimi K3.1 ProGPT-5.2-CodexvsKimi K3.1 ProFrequently asked questions
Claude Mythos 5.1 and GPT-5.2-Codex don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Claude Mythos 5.1 has a verified first-party price for an available API: $10.00 per million input tokens and $50.00 per million output tokens. No currently available pay-as-you-go API rate is tracked for GPT-5.2-Codex. Claude Mythos 5.1 requires organization verification. GPT-5.2-Codex shipped 257 days before Claude Mythos 5.1, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Mythos 5.1) vs 400k (GPT-5.2-Codex).
Direct benchmark comparisons are unavailable — Claude Mythos 5.1 and GPT-5.2-Codex don't publish scores on any of the same benchmarks.