Mistral Large 2 vs Qwen3.5-122B-A10B
Mistral Large 2 (2025) and Qwen3.5-122B-A10B (2026) are frontier reasoning models from MistralAI and Alibaba. Mistral Large 2 ships a 128k-token context window, while Qwen3.5-122B-A10B ships a 262k-token context window. On MMLU PRO, Qwen3.5-122B-A10B leads by 17 pts. On pricing, Qwen3.5-122B-A10B costs $0.26/1M input tokens versus $0.48/1M 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.
Qwen3.5-122B-A10B is ~85% cheaper at $0.26/1M; pay for Mistral Large 2 only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Mistral Large 2 | Qwen3.5-122B-A10B |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 128k | 262k |
| Cheapest output | $2.40/1M tokens | $2.08/1M tokens |
| Provider routes | 4 tracked | 3 tracked |
| Shared benchmarks | 1 rows | MMLU PRO leader |
Decision tradeoffs
- Mistral Large 2 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mistral Large 2 for Coding, RAG, and Agents.
- Qwen3.5-122B-A10B holds a shared-benchmark lead on MMLU PRO, ahead by 17 points.
- Qwen3.5-122B-A10B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-122B-A10B has the lower cheapest tracked output price at $2.08/1M tokens.
- Qwen3.5-122B-A10B uniquely exposes Reasoning in local model data.
- Local decision data tags Qwen3.5-122B-A10B 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 2
$984
Cheapest tracked route/tier: AWS Bedrock
Qwen3.5-122B-A10B
$728
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $256. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3.5-122B-A10B is $0.32/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-122B-A10B adds Reasoning in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Mistral Large 2 is $0.32/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-11-25 | 2026-02-24 |
| Context window | 128k | 262k |
| Parameters | 123B | 122B |
| Architecture | decoder only | mixture of experts |
| License | Mistral License | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Non-commercial only | Commercial use allowed |
| Knowledge cutoff | 2025-07 | - |
Pricing and availability
| Pricing attribute | Mistral Large 2 | Qwen3.5-122B-A10B |
|---|---|---|
| Input price | $0.48/1M tokens | $0.26/1M tokens |
| Output price | $2.40/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Large 2 | Qwen3.5-122B-A10B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | 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 2 | Qwen3.5-122B-A10B |
|---|---|---|
| MMLU PRO | 69.7 | 86.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has Mistral Large 2 at 69.7 and Qwen3.5-122B-A10B at 86.7, with Qwen3.5-122B-A10B ahead by 17 points. The largest visible gap is 17 points on MMLU PRO, 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 reasoning mode: Qwen3.5-122B-A10B. Both models share vision, multimodal input, 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.
For cost, Mistral Large 2 lists $0.48/1M input and $2.40/1M output tokens on the cheapest tracked provider, while Qwen3.5-122B-A10B lists $0.26/1M input and $2.08/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-122B-A10B lower by about $0.25 per million blended tokens. Availability is 4 providers versus 3, so concentration risk also matters.
Choose Mistral Large 2 when vision-heavy evaluation and broader provider choice are central to the workload. Choose Qwen3.5-122B-A10B when reasoning depth, larger context windows, and lower input-token cost 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 Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B supports 262k tokens, while Mistral Large 2 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 Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B is cheaper on tracked token pricing. Mistral Large 2 costs $0.48/1M input and $2.40/1M output tokens. Qwen3.5-122B-A10B costs $0.26/1M input and $2.08/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Large 2 or Qwen3.5-122B-A10B open source?
Mistral Large 2 is listed under Mistral License. Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B?
Both Mistral Large 2 and Qwen3.5-122B-A10B expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Mistral Large 2 or Qwen3.5-122B-A10B?
Both Mistral Large 2 and Qwen3.5-122B-A10B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Mistral Large 2 and Qwen3.5-122B-A10B?
Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Qwen3.5-122B-A10B is available on OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.