Claude Mythos 5.1vsKimi K2.7 Code
Claude Mythos 5.1 | Kimi K2.7 Code | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | — | 1T |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 1M | 256k |
| 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. | — | $0.95 |
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. | — | $4.00 |
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. | — | $0.19 |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $0.66Inceptron |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $3.40DeepInfra |
| BenchmarksPublished by one model only | ||
DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | — | 31% |
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. | — | 69% |
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% | — |
| Overview | ||
| Company | Anthropic | Moonshot AI |
| Release date | Sep 1 2026 | Jun 12 2026 |
| Access | Proprietary | Open Weight |
Other comparisons
Frequently asked questions
Claude Mythos 5.1 and Kimi K2.7 Code don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Kimi K2.7 Code has a verified first-party API price: $0.95 per million input tokens and $4.00 per million output tokens. No pay-as-you-go API rate is tracked for Claude Mythos 5.1. Kimi K2.7 Code shipped 81 days before Claude Mythos 5.1, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Mythos 5.1) vs 256k (Kimi K2.7 Code). Claude Mythos 5.1 is proprietary, while Kimi K2.7 Code is open weight.
Direct benchmark comparisons are unavailable — Claude Mythos 5.1 and Kimi K2.7 Code don't publish scores on any of the same benchmarks.
Claude Mythos 5.1 was released by Anthropic on Sep 1 2026.
Kimi K2.7 Code was released by Moonshot AI on Jun 12 2026.
Only Kimi K2.7 Code has a verified first-party API price: $0.95 per million input tokens and $4.00 per million output tokens. No pay-as-you-go API rate is tracked for Claude Mythos 5.1. Rates are pay-as-you-go API prices verified on August 18, 2026.
Claude Mythos 5.1 has a 1M context window; Kimi K2.7 Code has 256k.
Claude Mythos 5.1 is a proprietary model released by Anthropic. Kimi K2.7 Code is an open weight model released by Moonshot AI.