Mistral Large 2 (2407) vs Qwen3.5-235B-A22B
Mistral Large 2 (2407) (2024) and Qwen3.5-235B-A22B (2026) are compact production models from MistralAI and Alibaba. Mistral Large 2 (2407) ships a 128K-token context window, while Qwen3.5-235B-A22B ships a 512k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
Qwen3.5-235B-A22B fits 4x more tokens; pick it for long-context work and Mistral Large 2 (2407) for tighter calls.
Specs
| Released | 2024-07-23 | 2026-02-24 |
| Context window | 128K | 512k |
| Parameters | 123B | 235B |
| Architecture | decoder only | MoE |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Mistral Large 2 (2407) | Qwen3.5-235B-A22B | |
|---|---|---|
| Input price | $0.5/1M tokens | - |
| Output price | $1.5/1M tokens | - |
| Providers | - |
Capabilities
| Mistral Large 2 (2407) | Qwen3.5-235B-A22B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Mistral Large 2 (2407) and structured outputs: Mistral Large 2 (2407). Both models share the core language-model surface, 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.
Pricing coverage is uneven: Mistral Large 2 (2407) has $0.5/1M input tokens and Qwen3.5-235B-A22B has no token price sourced yet. Provider availability is 3 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Mistral Large 2 (2407) when vision-heavy evaluation and broader provider choice are central to the workload. Choose Qwen3.5-235B-A22B when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Mistral Large 2 (2407) or Qwen3.5-235B-A22B?
Qwen3.5-235B-A22B supports 512k 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.
Is Mistral Large 2 (2407) or Qwen3.5-235B-A22B open source?
Mistral Large 2 (2407) is listed under Apache 2.0. Qwen3.5-235B-A22B 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 Qwen3.5-235B-A22B?
Mistral Large 2 (2407) 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 structured outputs, Mistral Large 2 (2407) or Qwen3.5-235B-A22B?
Mistral Large 2 (2407) has the clearer documented structured outputs signal in this comparison. If structured outputs 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 Qwen3.5-235B-A22B?
Mistral Large 2 (2407) is available on Microsoft Foundry, Chutes AI, and SiliconFlow. Qwen3.5-235B-A22B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Mistral Large 2 (2407) over Qwen3.5-235B-A22B?
Qwen3.5-235B-A22B fits 4x more tokens; pick it for long-context work and Mistral Large 2 (2407) for tighter calls. If your workload also depends on vision-heavy evaluation, start with Mistral Large 2 (2407); if it depends on long-context analysis, run the same evaluation with Qwen3.5-235B-A22B.
Continue comparing
Last reviewed: 2026-04-23. Data sourced from public model cards and provider documentation.