Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | — | 1.8B/3.25B |
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 | 32k |
| 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. | $8.00Verified 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. | $40.00 | — |
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. | $0.20 | — |
| $3,600Anthropic list price | — | |
| These models have no shared benchmark scores. | ||
Terminal-Bench-Science 0.1Agentic scientific computing — The same command-line setup as Terminal-Bench, pointed at scientific work: the AI has to drive research tooling and computational workflows through to a result, rather than administer a machine. Version 0.1 is the first release of the task set, and scores run lower than on the general board. Higher is better. | 75.3% | — |
De novo binder design (24 hr)Protein design — de novo protein binder design within a 24-hour budget, as reported by Anthropic | 85.1% | — |
CyScenarioBenchCybersecurity — multi-step cybersecurity scenarios; each lab runs its own unique task set, so scores from different labs do not compare | 76.3% | — |
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 | 89.6% | — |
MATHReasoning — accuracy on the original competition mathematics test set | — | 22.8% |
MMLUGeneral knowledge — A 57-subject multiple-choice exam — history, law, medicine, maths — that was the standard measure of how much a model knows from 2020 until roughly 2024, when frontier scores crowded into the high 80s and labs moved on to harder tests. The scores here were published years apart under different testing setups, so read them as a historical record rather than a like-for-like ranking. Higher is better. | — | 55.8% |
MathVistaMultimodal reasoning — mathematical reasoning about visual information | — | 30.6% |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | — | 32.6% |
| Overview | ||
| Company | Anthropic | |
| Release date | Nov 9 2026 | Dec 6 2023 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Claude Mythos 5.2vsGPT-6.1 TerraGemini 1.0 NanovsGPT-6.1 TerraClaude Mythos 5.2vsMuse EmberGemini 1.0 NanovsMuse EmberClaude Mythos 5.2vsGrok 4.7Gemini 1.0 NanovsGrok 4.7Claude Mythos 5.2vsDeepSeek-V4.1-Flash-1017Gemini 1.0 NanovsDeepSeek-V4.1-Flash-1017Claude Mythos 5.2vsMistral Large 4Gemini 1.0 NanovsMistral Large 4Claude Mythos 5.2vsKimi K3.1 ProGemini 1.0 NanovsKimi K3.1 ProFrequently asked questions
Claude Mythos 5.2 and Gemini 1.0 Nano don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Claude Mythos 5.2 has a verified first-party price for an available API: $8.00 per million input tokens and $40.00 per million output tokens. No currently available pay-as-you-go API rate is tracked for Gemini 1.0 Nano. Claude Mythos 5.2 requires organization verification. Gemini 1.0 Nano shipped 1069 days before Claude Mythos 5.2, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Mythos 5.2) vs 32k (Gemini 1.0 Nano).
Direct benchmark comparisons are unavailable — Claude Mythos 5.2 and Gemini 1.0 Nano don't publish scores on any of the same benchmarks.