Claude Mythos 5.1 vs Mistral Large 3
At a Glance
| Compare | Claude Mythos 5.1Anthropic |  Mistral Large 3Mistral AI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $10.00Anthropic ↗ · Sep 2, 2026 | $0.25Openrouter ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $50.00Anthropic ↗ · Sep 2, 2026 | $0.75Openrouter ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,000K | 262K |
| Model facts checked | Sep 2, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Claude Mythos 5.1 | Mistral Large 3 |
|---|---|---|
| Developer | Anthropic | Mistral AI |
| Family | Claude 5 1 | Mistral Large 3 |
| Model | Claude Mythos 5.1 | Mistral Large 3 |
| Version | Claude Mythos 5.1 | Mistral Large 3 |
| Lifecycle | active | active |
| Released | 2026-09-01 | 2025-12-02 |
| Knowledge cutoff | 2026-06-01 | Unknown |
| Input modalities | Text, Image | Text, Image, Document |
| Output modalities | Text | Text |
| Context window | 1,000K | 262K |
| Total parameters | Unknown | 675B |
| Active parameters | Unknown | 41B |
| License | Unknown | Apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Project Glasswing) | Mistral AI (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | agents, chat, generation, structured_outputs, tools, vision |
Claude Mythos 5.1 Capabilities
Mistral Large 3 Capabilities
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Claude Mythos 5.1Anthropic | vs | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Mythos 5.1 vs Mistral Large 3 FAQs
Is Claude Mythos 5.1 or Mistral Large 3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Mythos 5.1 and Mistral Large 3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Mythos 5.1 or Mistral Large 3?+
Claude Mythos 5.1 is $10.00 and Mistral Large 3 is $0.25 per million tokens, so Mistral Large 3 is cheaper on this metric. Claude Mythos 5.1 is $50.00 and Mistral Large 3 is $0.75 per million tokens, so Mistral Large 3 is cheaper on this metric.
Which has a larger context window, Claude Mythos 5.1 or Mistral Large 3?+
Claude Mythos 5.1 has the larger sourced context window. Claude Mythos 5.1 supports 1,000K and Mistral Large 3 supports 262K.
Which performs better in benchmarks, Claude Mythos 5.1 or Mistral Large 3?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Mythos 5.1 or Mistral Large 3 be self-hosted?+
Mistral Large 3 is the only model in this pair currently marked as self-hostable. Claude Mythos 5.1 is not marked open weight; Mistral Large 3 is open weight.
Can Claude Mythos 5.1 and Mistral Large 3 understand images?+
Claude Mythos 5.1 is documented with image input; Mistral Large 3 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Mythos 5.1 or Mistral Large 3?+
Neither has a larger sourced maximum output. Claude Mythos 5.1 is 128K and Mistral Large 3 is —.
Do Claude Mythos 5.1 and Mistral Large 3 support reasoning and tool use?+
Claude Mythos 5.1: reasoning, tool calling, and image input. Mistral Large 3: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Mythos 5.1 or Mistral Large 3?+
Claude Mythos 5.1 has 1 sourced provider route; Mistral Large 3 has 2, so Mistral Large 3 has broader tracked availability.
Which offers better value, Claude Mythos 5.1 or Mistral Large 3?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.