Mistral Large 2 (2407) vs Qwen2.5-72B-Instruct
Mistral Large 2 (2407) (2024) and Qwen2.5-72B-Instruct (2024) are compact production models from MistralAI and Alibaba. Mistral Large 2 (2407) ships a 128K-token context window, while Qwen2.5-72B-Instruct ships a 128K-token context window. On pricing, Qwen2.5-72B-Instruct costs $0.12/1M 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.
Qwen2.5-72B-Instruct is ~317% cheaper at $0.12/1M; pay for Mistral Large 2 (2407) only for vision-heavy evaluation.
Specs
| Released | 2024-07-23 | 2024-06-07 |
| Context window | 128K | 128K |
| Parameters | 123B | 72.7B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Mistral Large 2 (2407) | Qwen2.5-72B-Instruct | |
|---|---|---|
| Input price | $0.5/1M tokens | $0.12/1M tokens |
| Output price | $1.5/1M tokens | $0.39/1M tokens |
| Providers |
Capabilities
| Mistral Large 2 (2407) | Qwen2.5-72B-Instruct | |
|---|---|---|
| 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). 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 Qwen2.5-72B-Instruct lists $0.12/1M input and $0.39/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2.5-72B-Instruct lower by about $0.6 per million blended tokens. Availability is 3 providers versus 7, so concentration risk also matters.
Choose Mistral Large 2 (2407) when vision-heavy evaluation are central to the workload. Choose Qwen2.5-72B-Instruct 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 Qwen2.5-72B-Instruct?
Mistral Large 2 (2407) supports 128K tokens, while Qwen2.5-72B-Instruct 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 Qwen2.5-72B-Instruct?
Qwen2.5-72B-Instruct is cheaper on tracked token pricing. Mistral Large 2 (2407) costs $0.5/1M input and $1.5/1M output tokens. Qwen2.5-72B-Instruct costs $0.12/1M input and $0.39/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large 2 (2407) or Qwen2.5-72B-Instruct open source?
Mistral Large 2 (2407) is listed under Apache 2.0. Qwen2.5-72B-Instruct 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 Qwen2.5-72B-Instruct?
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 Qwen2.5-72B-Instruct?
Both Mistral Large 2 (2407) and Qwen2.5-72B-Instruct 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 Qwen2.5-72B-Instruct?
Mistral Large 2 (2407) is available on Microsoft Foundry, Chutes AI, and SiliconFlow. Qwen2.5-72B-Instruct is available on DeepInfra, OpenRouter, Fireworks AI, Novita AI, and Chutes AI. 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.