Mistral Large 2.1 (2411) vs Qwen2.5-72B
Mistral Large 2.1 (2411) (2024) and Qwen2.5-72B (2025) are compact production models from MistralAI and Alibaba. Mistral Large 2.1 (2411) ships a 128k-token context window, while Qwen2.5-72B ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Qwen2.5-72B is safer overall; choose Mistral Large 2.1 (2411) when provider fit matters.
Decision scorecard
Local evidence first| Signal | Mistral Large 2.1 (2411) | Qwen2.5-72B |
|---|---|---|
| Best for | tool-calling agents | tool-calling agents |
| Decision fit | RAG, Agents, and Long context | RAG, Agents, and Long context |
| Context window | 128k | 128k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Mistral Large 2.1 (2411) uniquely exposes Structured outputs in local model data.
- Local decision data tags Mistral Large 2.1 (2411) for RAG, Agents, and Long context.
- Local decision data tags Qwen2.5-72B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mistral Large 2.1 (2411)
Unavailable
No complete token price in local provider data
Qwen2.5-72B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Mistral Large 2.1 (2411) and Qwen2.5-72B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Qwen2.5-72B and Mistral Large 2.1 (2411); plan for SDK, billing, or endpoint changes.
- Mistral Large 2.1 (2411) adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-11-18 | 2025-10-10 |
| Context window | 128k | 128k |
| Parameters | 123B | 72B |
| Architecture | decoder only | - |
| License | Mistral License | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Non-commercial only | Commercial use allowed |
| Knowledge cutoff | - | 2024-09 |
Pricing and availability
| Pricing attribute | Mistral Large 2.1 (2411) | Qwen2.5-72B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Mistral Large 2.1 (2411) | Qwen2.5-72B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Mistral Large 2.1 (2411). Both models share function calling and tool use, 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 2.1 (2411) has no token price sourced yet and Qwen2.5-72B has no token price sourced yet. Provider availability is 0 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 2.1 (2411) when provider fit are central to the workload. Choose Qwen2.5-72B when provider fit 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 2.1 (2411) or Qwen2.5-72B?
Mistral Large 2.1 (2411) supports 128k tokens, while Qwen2.5-72B 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 2.1 (2411) or Qwen2.5-72B open source?
Mistral Large 2.1 (2411) is listed under Mistral License. Qwen2.5-72B 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 function calling, Mistral Large 2.1 (2411) or Qwen2.5-72B?
Both Mistral Large 2.1 (2411) and Qwen2.5-72B expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for tool use, Mistral Large 2.1 (2411) or Qwen2.5-72B?
Both Mistral Large 2.1 (2411) and Qwen2.5-72B expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for structured outputs, Mistral Large 2.1 (2411) or Qwen2.5-72B?
Mistral Large 2.1 (2411) 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.
When should I pick Mistral Large 2.1 (2411) over Qwen2.5-72B?
Qwen2.5-72B is safer overall; choose Mistral Large 2.1 (2411) when provider fit matters. If your workload also depends on provider fit, start with Mistral Large 2.1 (2411); if it depends on provider fit, run the same evaluation with Qwen2.5-72B.
Continue comparing
Last reviewed: 2026-05-25. Data sourced from public model cards and provider documentation.