Mistral Large 2 vs Qwen3.5-397B-A17B
Mistral Large 2 (2025) and Qwen3.5-397B-A17B (2026) are compact production models from MistralAI and Alibaba. Mistral Large 2 ships a 128K-token context window, while Qwen3.5-397B-A17B ships a 262K-token context window. On MMLU PRO, Qwen3.5-397B-A17B leads by 18.1 pts. On pricing, Qwen3.5-397B-A17B costs $0.39/1M input tokens versus $0.48/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3.5-397B-A17B is safer overall; choose Mistral Large 2 when vision-heavy evaluation matters.
Specs
| Released | 2025-11-25 | 2026-02-16 |
| Context window | 128K | 262K |
| Parameters | 123B | 397B |
| Architecture | decoder only | MoE |
| License | True | Apache 2.0 |
| Knowledge cutoff | 2025-07 | - |
Pricing and availability
| Mistral Large 2 | Qwen3.5-397B-A17B | |
|---|---|---|
| Input price | $0.48/1M tokens | $0.39/1M tokens |
| Output price | $2.4/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Mistral Large 2 | Qwen3.5-397B-A17B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Mistral Large 2 | Qwen3.5-397B-A17B |
|---|---|---|
| MMLU PRO | 69.7 | 87.8 |
| BFCL | 38.4 | 72.9 |
Deep dive
On shared benchmark coverage, MMLU PRO has Mistral Large 2 at 69.7 and Qwen3.5-397B-A17B at 87.8, with Qwen3.5-397B-A17B ahead by 18.1 points; BFCL has Mistral Large 2 at 38.4 and Qwen3.5-397B-A17B at 72.9, with Qwen3.5-397B-A17B ahead by 34.5 points. The largest visible gap is 34.5 points on BFCL, 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: Mistral Large 2, function calling: Mistral Large 2, and tool use: Mistral Large 2. Both models share multimodal input 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 lists $0.48/1M input and $2.4/1M output tokens, 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 Qwen3.5-397B-A17B lower by about $0.08 per million blended tokens. Availability is 4 providers versus 1, so concentration risk also matters.
Choose Mistral Large 2 when vision-heavy evaluation and broader provider choice are central to the workload. Choose Qwen3.5-397B-A17B when long-context analysis, 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 or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B supports 262K tokens, while Mistral Large 2 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 or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B is cheaper on tracked token pricing. Mistral Large 2 costs $0.48/1M input and $2.4/1M 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 or Qwen3.5-397B-A17B open source?
Mistral Large 2 is listed under True. 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 or Qwen3.5-397B-A17B?
Mistral Large 2 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.
Which is better for multimodal input, Mistral Large 2 or Qwen3.5-397B-A17B?
Both Mistral Large 2 and Qwen3.5-397B-A17B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Mistral Large 2 and Qwen3.5-397B-A17B?
Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Qwen3.5-397B-A17B is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.