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. Both ship a 128K-token context window. On HumanEval, Mistral Large 2 (2407) leads by 5.4 pts. On pricing, Qwen2.5-72B-Instruct costs $0.18/1M input tokens versus $0.50/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Qwen2.5-72B-Instruct is ~178% cheaper at $0.18/1M; pay for Mistral Large 2 (2407) only for provider fit.
Decision scorecard
Local evidence first| Signal | Mistral Large 2 (2407) | Qwen2.5-72B-Instruct |
|---|---|---|
| Best for | tool-calling agents and provider-routed production | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Long context |
| Context window | 128K | 128K |
| Cheapest output | $1.50/1M tokens | $0.54/1M tokens |
| Provider routes | 7 tracked | 8 tracked |
| Shared benchmarks | HumanEval leader | 3 shared |
Decision tradeoffs
- Mistral Large 2 (2407) holds a shared-benchmark lead on HumanEval, ahead by 5.4 points.
- Mistral Large 2 (2407) uniquely exposes JSON / Tool use in local model data.
- Local decision data tags Mistral Large 2 (2407) for Coding, RAG, and Agents.
- Qwen2.5-72B-Instruct holds a shared-benchmark lead on Massive Multitask Language Understanding, ahead by 4.2 points.
- Qwen2.5-72B-Instruct has the lower cheapest tracked output price at $0.54/1M tokens.
- Qwen2.5-72B-Instruct has broader tracked provider coverage for fallback and route flexibility.
- Local decision data tags Qwen2.5-72B-Instruct for Coding, RAG, 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 (2407)
$775
Cheapest tracked route/tier: Chutes AI
Qwen2.5-72B-Instruct
$279
Cheapest tracked route/tier: Chutes AI
Estimated monthly gap: $496. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, Chutes AI, and SiliconFlow; start route-level A/B tests there.
- Qwen2.5-72B-Instruct is $0.96/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for JSON / Tool use before moving production traffic.
- Provider overlap exists on OpenRouter, Chutes AI, and SiliconFlow; start route-level A/B tests there.
- Mistral Large 2 (2407) is $0.96/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Large 2 (2407) adds JSON / Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-24 | 2024-06-07 |
| Context window | 128K | 128K |
| Parameters | 123B | 72.7B |
| Architecture | Decoder Only | Decoder Only |
| License | Mistral License | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Not permitted | Permitted |
| Knowledge cutoff | 2024-03 | - |
Pricing and availability
| Pricing attribute | Mistral Large 2 (2407) | Qwen2.5-72B-Instruct |
|---|---|---|
| Input price | $0.50/1M tokens | $0.18/1M tokens |
| Output price | $1.50/1M tokens | $0.54/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Large 2 (2407) | Qwen2.5-72B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| JSON / Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Mistral Large 2 (2407) | Qwen2.5-72B-Instruct |
|---|---|---|
| HumanEval | 92.0 | 86.6 |
| Massive Multitask Language Understanding | 84.0 | 88.2 |
| Chatbot Arena | 1266.0 | 1270.0 |
Deep dive
On shared benchmark coverage, HumanEval has Mistral Large 2 (2407) at 92 and Qwen2.5-72B-Instruct at 86.6, with Mistral Large 2 (2407) ahead by 5.4 points; Massive Multitask Language Understanding has Mistral Large 2 (2407) at 84 and Qwen2.5-72B-Instruct at 88.2, with Qwen2.5-72B-Instruct ahead by 4.2 points; Chatbot Arena has Mistral Large 2 (2407) at 1266 and Qwen2.5-72B-Instruct at 1270, with Qwen2.5-72B-Instruct ahead by 4 points. The largest visible gap is 5.4 points on HumanEval, 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 JSON / Tool use: 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 $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider, while Qwen2.5-72B-Instruct lists $0.18/1M input and $0.54/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2.5-72B-Instruct lower by about $0.51 per million blended tokens. Availability is 7 providers versus 8, so concentration risk also matters.
Choose Mistral Large 2 (2407) when provider fit 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.
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 $0.50/1M input and $1.50/1M output tokens. Qwen2.5-72B-Instruct costs $0.18/1M input and $0.54/1M 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 Mistral License. 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 JSON / Tool use, Mistral Large 2 (2407) or Qwen2.5-72B-Instruct?
Mistral Large 2 (2407) has the clearer documented JSON / Tool use signal in this comparison. If JSON / Tool use 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, IBM watsonx, OpenRouter, AWS Bedrock, and Chutes AI. 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.
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Last reviewed: 2026-10-17. Data sourced from public model cards and provider documentation.