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Mistral Large 2 vs Qwen2.5-72B-Instruct

Mistral Large 2 (2025) and Qwen2.5-72B-Instruct (2024) are compact production models from MistralAI and Alibaba. Mistral Large 2 ships a 128K-token context window, while Qwen2.5-72B-Instruct ships a 128K-token context window. On HumanEval, Qwen2.5-72B-Instruct leads by 7.9 pts. On pricing, Qwen2.5-72B-Instruct costs $0.18/1M input tokens versus $0.48/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Qwen2.5-72B-Instruct is ~167% cheaper at $0.18/1M; pay for Mistral Large 2 only for vision-heavy evaluation.

Decision scorecard

Local evidence first
SignalMistral Large 2Qwen2.5-72B-Instruct
Decision fitCoding, RAG, and AgentsCoding, RAG, and Long context
Context window128K128K
Cheapest output$2.4/1M tokens$0.54/1M tokens
Provider routes4 tracked7 tracked
Shared benchmarks4 rowsHumanEval leader

Decision tradeoffs

Choose Mistral Large 2 when...
  • Mistral Large 2 uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags Mistral Large 2 for Coding, RAG, and Agents.
Choose Qwen2.5-72B-Instruct when...
  • Qwen2.5-72B-Instruct leads the largest shared benchmark signal on HumanEval by 7.9 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 procurement 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 prices on this page.

Lower estimate Qwen2.5-72B-Instruct

Mistral Large 2

$984

Cheapest tracked route: AWS Bedrock

Qwen2.5-72B-Instruct

$279

Cheapest tracked route: Chutes AI

Estimated monthly gap: $705. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Mistral Large 2 -> Qwen2.5-72B-Instruct
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Qwen2.5-72B-Instruct is $1.86/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Qwen2.5-72B-Instruct -> Mistral Large 2
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Mistral Large 2 is $1.86/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Mistral Large 2 adds Vision, Multimodal, and Function calling in local capability data.

Specs

Specification
Released2025-11-252024-06-07
Context window128K128K
Parameters123B72.7B
Architecturedecoder onlydecoder only
LicenseTrueApache 2.0
Knowledge cutoff2025-07-

Pricing and availability

Pricing attributeMistral Large 2Qwen2.5-72B-Instruct
Input price$0.48/1M tokens$0.18/1M tokens
Output price$2.4/1M tokens$0.54/1M tokens
Providers

Capabilities

CapabilityMistral Large 2Qwen2.5-72B-Instruct
VisionYesNo
MultimodalYesNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionNoNo

Benchmarks

BenchmarkMistral Large 2Qwen2.5-72B-Instruct
HumanEval84.892.7
Chatbot Arena1265.01270.0
Massive Multitask Language Understanding84.088.2
HellaSwag93.895.6

Deep dive

On shared benchmark coverage, HumanEval has Mistral Large 2 at 84.8 and Qwen2.5-72B-Instruct at 92.7, with Qwen2.5-72B-Instruct ahead by 7.9 points; Chatbot Arena has Mistral Large 2 at 1265 and Qwen2.5-72B-Instruct at 1270, with Qwen2.5-72B-Instruct ahead by 5 points; Massive Multitask Language Understanding has Mistral Large 2 at 84 and Qwen2.5-72B-Instruct at 88.2, with Qwen2.5-72B-Instruct ahead by 4.2 points. The largest visible gap is 7.9 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 vision: Mistral Large 2, multimodal input: Mistral Large 2, function calling: Mistral Large 2, and tool use: Mistral Large 2. 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 lists $0.48/1M input and $2.4/1M output tokens, 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 $0.77 per million blended tokens. Availability is 4 providers versus 7, so concentration risk also matters.

Choose Mistral Large 2 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.

FAQ

Which has a larger context window, Mistral Large 2 or Qwen2.5-72B-Instruct?

Mistral Large 2 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 or Qwen2.5-72B-Instruct?

Qwen2.5-72B-Instruct is cheaper on tracked token pricing. Mistral Large 2 costs $0.48/1M input and $2.4/1M 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 or Qwen2.5-72B-Instruct open source?

Mistral Large 2 is listed under True. 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 or Qwen2.5-72B-Instruct?

Mistral Large 2 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 multimodal input, Mistral Large 2 or Qwen2.5-72B-Instruct?

Mistral Large 2 has the clearer documented multimodal input signal in this comparison. If multimodal input 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 and Qwen2.5-72B-Instruct?

Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. 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: 2026-05-11. Data sourced from public model cards and provider documentation.