77.6% SWE-bench Verified — the strongest dense open-weights coding score at release
Single-checkpoint multimodality with function calling and structured outputs
Open weights under a modified MIT license, practical to self-host and fine-tune at 128B dense
Weaknesses
Trails GPT-5.6, Opus-class, and Gemini frontier models on complex multi-step reasoning; sparse published benchmark disclosure
256K context is a quarter of the 1M frontier norm, and $7.50/1M output is dear for the tier
Real-world use cases
What people actually use Mistral Medium 3.5 for.
Coding at 77.6% SWE-bench Verified — within ~2 points of Claude Sonnet 4.6 at roughly half the price
Document Q&A and vision tasks from a single checkpoint with structured outputs
EU-compliant self-hosted deployments — 128B dense is far easier to run than trillion-parameter MoE rivals
How Mistral Medium 3.5 compares
The nearest models people weigh against it, and what actually separates them.
vs Claude Fable 5 — Against Claude Fable 5 (Anthropic), Mistral Medium 3.5 runs about 85% cheaper per token, gives up 3.9x on context and answers faster. Take Mistral Medium 3.5 unless you specifically need what Claude Fable 5 does better.
vs Claude Fable 5.1 — Against Claude Fable 5.1 (Anthropic), Mistral Medium 3.5 runs about 85% cheaper per token, gives up 3.9x on context and answers faster. Take Mistral Medium 3.5 unless you specifically need what Claude Fable 5.1 does better.
vs Claude Opus 4.7 — Against Claude Opus 4.7 (Anthropic), Mistral Medium 3.5 runs about 70% cheaper per token, gives up 3.9x on context and answers faster. Take Mistral Medium 3.5 unless you specifically need what Claude Opus 4.7 does better.
Price History
Mistral Medium 3.5 pricing over time
→0% since Aug 7
37 data points · tracked daily since Aug 7, 2026
Ready to try it?
Start using Mistral Medium 3.5
Self-hostable European multimodal coding. Start free — no card required.
Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.
Verdict
New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses.
Coding leaderSWE-Bench Pro #1Mythos-classParallel subagentsAgenticLong contextPremiumNew
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Anthropic's September 1, 2026 frontier release and the new capability ceiling for coding, agents, and scientific work. Base pricing is unchanged at $10/$50, but cache reads dropped 75% to $0.25/1M — roughly 25% cheaper on typical workloads and up to 45% cheaper on agentic ones. 1M context, 128K output, adaptive thinking always on.
Verdict
New frontier leader — better than Fable 5 on every published benchmark, and cheaper to run.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Released September 1, 2026 alongside Claude Mythos 5.1, the first update to the Mythos-class line since Fable 5 on June 9. API ID claude-fable-5-1; generally available on the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Published launch numbers (Fable 5.1 / Fable 5 / Opus 5 / GPT-5.6 Sol): Terminal-Bench-Science 0.1 52.6 / 24.7 / 29.0 / 22.4; Terminal-Bench 4.0 55.8 / 42.0 / 52.3 / 37.3; CursorBench 3.2.0 73.4 / 70.5 / 70.0 / 67.2; AutomationBench 31.4 / 17.1 / 26.9 / 19.6; OSWorld 2.0 strict 41.7 / 36.1 / 39.6; Humanity's Last Exam (no tools) 60.9 / 57.8 / 56.6; GDPval-AA v2 1853 / 1723 / 1824 / 1711. GDPval-AA v2 is rescaled from the v1 numbers quoted on the Fable 5 page and is not directly comparable to them.
Mistral Medium 3.5 costs $1.5 per million input tokens and $7.5 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $30.00 at list price, before any batch or caching discounts.
What is the context window of Mistral Medium 3.5?
Mistral Medium 3.5 has a 256k tokens context window, with up to 256k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is Mistral Medium 3.5 best for?
Mistral Medium 3.5 is best for self-hostable european multimodal coding. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and balanced speed.
When should I avoid Mistral Medium 3.5?
API price-performance is all that matters — DeepSeek V4-Pro is stronger and cheaper hosted.
What is a cheaper alternative to Mistral Medium 3.5?
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against Mistral Medium 3.5's $1.50/1M/1M. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. Compare it first if Mistral Medium 3.5's pricing is the thing stopping you.
What is a faster alternative to Mistral Medium 3.5?
Claude Fable 5 — deliberate against Mistral Medium 3.5's balanced, with 1M tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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