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. | — | 24B |
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 | 256k |
| Benchmarks | ||
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. | 95.5% | 68% |
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | 88% | 22.5% |
SWE-Bench MultilingualMultilingual coding — Like SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. | — | 55.7% |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | 88% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 88% | — |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 64.5% | — |
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 85% | — |
| Overview | ||
| Company | Anthropic | Mistral |
| Release date | Jun 9 2026 | Dec 9 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Claude Mythos 5vsGPT-6.1 SolDevstral Small 2 (24B)vsGPT-6.1 SolClaude Mythos 5vsGemini 4 ArgonDevstral Small 2 (24B)vsGemini 4 ArgonClaude Mythos 5vsMuse Spark OpenDevstral Small 2 (24B)vsMuse Spark OpenClaude Mythos 5vsGrok 4.7Devstral Small 2 (24B)vsGrok 4.7Claude Mythos 5vsDeepSeek-V4.1-Flash-1017Devstral Small 2 (24B)vsDeepSeek-V4.1-Flash-1017Claude Mythos 5vsKimi K3Devstral Small 2 (24B)vsKimi K3Frequently asked questions
Claude Mythos 5 leads Devstral Small 2 (24B) on 2 of the 2 benchmarks they both report (SWE-Bench Verified, Terminal-Bench 2.0). Devstral Small 2 (24B) shipped 182 days before Claude Mythos 5, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Mythos 5) vs 256k (Devstral Small 2 (24B)). Claude Mythos 5 is closed, while Devstral Small 2 (24B) is open weight.
On SWE-Bench Verified, Claude Mythos 5 leads at 95.5% vs Devstral Small 2 (24B) at 68%. On Terminal-Bench 2.0, Claude Mythos 5 leads at 88% vs Devstral Small 2 (24B) at 22.5%.