Mistral Large 2 (2407) vs Qwen3-235B-A22B
Mistral Large 2 (2407) (2024) and Qwen3-235B-A22B (2025) are compact production models from MistralAI and Alibaba. Mistral Large 2 (2407) ships a 128K-token context window, while Qwen3-235B-A22B ships a 128K-token context window. On pricing, Qwen3-235B-A22B costs $0.4/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3-235B-A22B is safer overall; choose Mistral Large 2 (2407) when vision-heavy evaluation matters.
Decision scorecard
Local evidence first| Signal | Mistral Large 2 (2407) | Qwen3-235B-A22B |
|---|---|---|
| Decision fit | RAG, Long context, and Vision | Coding, RAG, and Long context |
| Context window | 128K | 128K |
| Cheapest output | $1.5/1M tokens | $1.2/1M tokens |
| Provider routes | 3 tracked | 4 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Mistral Large 2 (2407) uniquely exposes Vision in local model data.
- Local decision data tags Mistral Large 2 (2407) for RAG, Long context, and Vision.
- Qwen3-235B-A22B has the lower cheapest tracked output price at $1.2/1M tokens.
- Qwen3-235B-A22B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Qwen3-235B-A22B for Coding, RAG, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Mistral Large 2 (2407)
$775
Cheapest tracked route: Chutes AI
Qwen3-235B-A22B
$620
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $155. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Mistral Large 2 (2407) and Qwen3-235B-A22B; plan for SDK, billing, or endpoint changes.
- Qwen3-235B-A22B is $0.3/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision before moving production traffic.
- No overlapping tracked provider route is sourced for Qwen3-235B-A22B and Mistral Large 2 (2407); plan for SDK, billing, or endpoint changes.
- Mistral Large 2 (2407) is $0.3/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Large 2 (2407) adds Vision in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2025-04-29 |
| Context window | 128K | 128K |
| Parameters | 123B | 235B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | 2024-03 | - |
Pricing and availability
| Pricing attribute | Mistral Large 2 (2407) | Qwen3-235B-A22B |
|---|---|---|
| Input price | $0.5/1M tokens | $0.4/1M tokens |
| Output price | $1.5/1M tokens | $1.2/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Large 2 (2407) | Qwen3-235B-A22B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Mistral Large 2 (2407). Both models share 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 $0.5/1M input and $1.5/1M output tokens, while Qwen3-235B-A22B lists $0.4/1M input and $1.2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-235B-A22B lower by about $0.16 per million blended tokens. Availability is 3 providers versus 4, so concentration risk also matters.
Choose Mistral Large 2 (2407) when vision-heavy evaluation are central to the workload. Choose Qwen3-235B-A22B when provider fit, lower input-token cost, and broader provider choice 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 Qwen3-235B-A22B?
Mistral Large 2 (2407) supports 128K tokens, while Qwen3-235B-A22B 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 Qwen3-235B-A22B?
Qwen3-235B-A22B is cheaper on tracked token pricing. Mistral Large 2 (2407) costs $0.5/1M input and $1.5/1M output tokens. Qwen3-235B-A22B costs $0.4/1M input and $1.2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large 2 (2407) or Qwen3-235B-A22B open source?
Mistral Large 2 (2407) is listed under Apache 2.0. Qwen3-235B-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 Qwen3-235B-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 Qwen3-235B-A22B?
Both Mistral Large 2 (2407) and Qwen3-235B-A22B expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Mistral Large 2 (2407) and Qwen3-235B-A22B?
Mistral Large 2 (2407) is available on Microsoft Foundry, Chutes AI, and SiliconFlow. Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, and Venice AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-20. Data sourced from public model cards and provider documentation.