Mistral Large 3 675B Instruct vs Qwen3-Max
Mistral Large 3 675B Instruct (2025) and Qwen3-Max (2025) are compact production models from MistralAI and Alibaba. Mistral Large 3 675B Instruct ships a 128k-token context window, while Qwen3-Max ships a 262k-token context window. On τ-bench, Qwen3-Max leads by 6.6 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Mistral Large 3 675B Instruct is safer overall; choose Qwen3-Max when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Mistral Large 3 675B Instruct | Qwen3-Max |
|---|---|---|
| Best for | multimodal apps and provider-routed production | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 128k | 262k |
| Cheapest output | $1.50/1M tokens | $3.90/1M tokens |
| Provider routes | 5 tracked | 3 tracked |
| Shared benchmarks | 1 rows | τ-bench leader |
Decision tradeoffs
- Mistral Large 3 675B Instruct has the lower cheapest tracked output price at $1.50/1M tokens.
- Mistral Large 3 675B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mistral Large 3 675B Instruct for Coding, RAG, and Agents.
- Qwen3-Max holds a shared-benchmark lead on τ-bench, ahead by 6.6 points.
- Qwen3-Max has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3-Max uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Qwen3-Max for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mistral Large 3 675B Instruct
$775
Cheapest tracked route/tier: AWS Bedrock
Qwen3-Max
$1,599
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $824. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- Qwen3-Max is $2.40/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3-Max adds Function calling and Tool use in local capability data.
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- Mistral Large 3 675B Instruct is $2.40/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-01 | 2025-04-28 |
| Context window | 128k | 262k |
| Parameters | 675B | — |
| Architecture | decoder only | decoder only |
| License | Mistral License | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Non-commercial only | Commercial use allowed |
| Knowledge cutoff | 2024-11 | 2025-12 |
Pricing and availability
| Pricing attribute | Mistral Large 3 675B Instruct | Qwen3-Max |
|---|---|---|
| Input price | $0.50/1M tokens |
|
| Output price | $1.50/1M tokens |
|
| Providers |
Capabilities
| Capability | Mistral Large 3 675B Instruct | Qwen3-Max |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Mistral Large 3 675B Instruct | Qwen3-Max |
|---|---|---|
| τ-bench | 70.2 | 76.8 |
Deep dive
On shared benchmark coverage, τ-bench has Mistral Large 3 675B Instruct at 70.2 and Qwen3-Max at 76.8, with Qwen3-Max ahead by 6.6 points. The largest visible gap is 6.6 points on τ-bench, 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 function calling: Qwen3-Max and tool use: Qwen3-Max. Both models share vision, multimodal input, and 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 3 675B Instruct lists $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider, while Qwen3-Max lists tiered pricing: 0-32,001t is $1.20/1M input and $6/1M output; 0-128,001t is $2.40/1M input and $12/1M output; 128,001t+ is $3/1M input and $15/1M output. A 70/30 input-output blend puts Mistral Large 3 675B Instruct lower by about $0.92 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 5 providers versus 3, so concentration risk also matters.
Choose Mistral Large 3 675B Instruct when vision-heavy evaluation, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3-Max when long-context analysis and larger context windows 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 3 675B Instruct or Qwen3-Max?
Qwen3-Max supports 262k tokens, while Mistral Large 3 675B 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 3 675B Instruct or Qwen3-Max?
Mistral Large 3 675B Instruct lists $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider. Qwen3-Max lists tiered pricing: 0-32,001t is $1.20/1M input and $6/1M output; 0-128,001t is $2.40/1M input and $12/1M output; 128,001t+ is $3/1M input and $15/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large 3 675B Instruct or Qwen3-Max open source?
Mistral Large 3 675B Instruct is listed under Mistral License. Qwen3-Max 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 3 675B Instruct or Qwen3-Max?
Both Mistral Large 3 675B Instruct and Qwen3-Max expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Mistral Large 3 675B Instruct or Qwen3-Max?
Both Mistral Large 3 675B Instruct and Qwen3-Max expose multimodal input. 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 3 675B Instruct and Qwen3-Max?
Mistral Large 3 675B Instruct is available on AWS Bedrock, NVIDIA NIM, Mistral AI Studio, Microsoft Foundry, and Vercel AI Gateway. Qwen3-Max is available on OpenRouter, Vercel AI Gateway, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.