Mistral Large 2 (2407) vs Qwen3.5-397B-A17B
Mistral Large 2 (2407) (2024) and Qwen3.5-397B-A17B (2026) are frontier reasoning models from MistralAI and Alibaba. Mistral Large 2 (2407) ships a 128K-token context window, while Qwen3.5-397B-A17B ships a 256K-token context window. On MMLU PRO, Qwen3.5-397B-A17B leads by 21.9 pts. On pricing, Qwen3.5-397B-A17B costs $0.39/1M input tokens versus $0.50/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Qwen3.5-397B-A17B is safer overall; choose Mistral Large 2 (2407) when provider fit matters.
Decision scorecard
Local evidence first| Signal | Mistral Large 2 (2407) | Qwen3.5-397B-A17B |
|---|---|---|
| Best for | tool-calling agents and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 128K | 256K |
| Cheapest output | $1.50/1M tokens | $2.34/1M tokens |
| Provider routes | 7 tracked | 4 tracked |
| Shared benchmarks | 1 shared | MMLU PRO leader |
Decision tradeoffs
- Mistral Large 2 (2407) has the lower cheapest tracked output price at $1.50/1M tokens.
- Mistral Large 2 (2407) has broader tracked provider coverage for fallback and route flexibility.
- Local decision data tags Mistral Large 2 (2407) for Coding, RAG, and Agents.
- Qwen3.5-397B-A17B holds a shared-benchmark lead on MMLU PRO, ahead by 21.9 points.
- Qwen3.5-397B-A17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-397B-A17B uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Qwen3.5-397B-A17B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mistral Large 2 (2407)
$775
Cheapest tracked route/tier: Chutes AI
Qwen3.5-397B-A17B
$897
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $122. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3.5-397B-A17B is $0.84/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.5-397B-A17B adds Vision, Multimodal, and Reasoning in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Mistral Large 2 (2407) is $0.84/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-24 | 2026-02-16 |
| Context window | 128K | 256K |
| Parameters | 123B | 397B |
| Architecture | Decoder Only | Mixture of Experts |
| License | Mistral License | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Not permitted | Permitted |
| Knowledge cutoff | 2024-03 | - |
Pricing and availability
| Pricing attribute | Mistral Large 2 (2407) | Qwen3.5-397B-A17B |
|---|---|---|
| Input price | $0.50/1M tokens | $0.39/1M tokens |
| Output price | $1.50/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Large 2 (2407) | Qwen3.5-397B-A17B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| JSON / Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Mistral Large 2 (2407) | Qwen3.5-397B-A17B |
|---|---|---|
| MMLU PRO | 65.9 | 87.8 |
Deep dive
On shared benchmark coverage, MMLU PRO has Mistral Large 2 (2407) at 65.9 and Qwen3.5-397B-A17B at 87.8, with Qwen3.5-397B-A17B ahead by 21.9 points. The largest visible gap is 21.9 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Qwen3.5-397B-A17B, multimodal input: Qwen3.5-397B-A17B, reasoning mode: Qwen3.5-397B-A17B, and JSON / Tool use: Qwen3.5-397B-A17B. Both models share JSON / Tool use and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Mistral Large 2 (2407) lists $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider, while Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Large 2 (2407) lower by about $0.17 per million blended tokens. Availability is 7 providers versus 4, so concentration risk also matters.
Choose Mistral Large 2 (2407) when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-397B-A17B when reasoning depth, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Mistral Large 2 (2407) or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B supports 256K tokens, while Mistral Large 2 (2407) supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Mistral Large 2 (2407) or Qwen3.5-397B-A17B?
Mistral Large 2 (2407) is cheaper on tracked token pricing. Mistral Large 2 (2407) costs $0.50/1M input and $1.50/1M output tokens. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large 2 (2407) or Qwen3.5-397B-A17B open source?
Mistral Large 2 (2407) is listed under Mistral License. Qwen3.5-397B-A17B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Mistral Large 2 (2407) or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Mistral Large 2 (2407) or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Mistral Large 2 (2407) and Qwen3.5-397B-A17B?
Mistral Large 2 (2407) is available on Microsoft Foundry, IBM watsonx, OpenRouter, AWS Bedrock, and Chutes AI. Qwen3.5-397B-A17B is available on OpenRouter, Together AI, Alibaba Cloud PAI-EAS, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-10-17. Data sourced from public model cards and provider documentation.