Mistral Large 2 (2407) vs Qwen3.5-122B-A10B
Mistral Large 2 (2407) (2024) and Qwen3.5-122B-A10B (2026) are frontier reasoning models from MistralAI and Alibaba. Mistral Large 2 (2407) ships a 128k-token context window, while Qwen3.5-122B-A10B ships a 262k-token context window. On pricing, Qwen3.5-122B-A10B costs $0.26/1M 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.
Qwen3.5-122B-A10B is ~92% cheaper at $0.26/1M; pay for Mistral Large 2 (2407) only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Mistral Large 2 (2407) | Qwen3.5-122B-A10B |
|---|---|---|
| Best for | multimodal apps and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | RAG, Long context, and Vision | Coding, RAG, and Agents |
| Context window | 128k | 262k |
| Cheapest output | $1.50/1M tokens | $2.08/1M tokens |
| Provider routes | 3 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Mistral Large 2 (2407) has the lower cheapest tracked output price at $1.50/1M tokens.
- Local decision data tags Mistral Large 2 (2407) for RAG, Long context, and Vision.
- Qwen3.5-122B-A10B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-122B-A10B uniquely exposes Multimodal, Reasoning, and Function calling 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 (2407)
$775
Cheapest tracked route/tier: Chutes AI
Qwen3.5-122B-A10B
$728
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $47.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Mistral Large 2 (2407) and Qwen3.5-122B-A10B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-122B-A10B is $0.58/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.5-122B-A10B adds Multimodal, Reasoning, and Function calling in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-122B-A10B and Mistral Large 2 (2407); plan for SDK, billing, or endpoint changes.
- Mistral Large 2 (2407) is $0.58/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Multimodal, Reasoning, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 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 | 2024-03 | - |
Pricing and availability
| Pricing attribute | Mistral Large 2 (2407) | Qwen3.5-122B-A10B |
|---|---|---|
| Input price | $0.50/1M tokens | $0.26/1M tokens |
| Output price | $1.50/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Large 2 (2407) | Qwen3.5-122B-A10B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| 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
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: Qwen3.5-122B-A10B, reasoning mode: Qwen3.5-122B-A10B, function calling: Qwen3.5-122B-A10B, and tool use: Qwen3.5-122B-A10B. Both models share vision 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 2 (2407) lists $0.50/1M input and $1.50/1M 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 Mistral Large 2 (2407) lower by about $0.01 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.
Choose Mistral Large 2 (2407) when vision-heavy evaluation 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. 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.
FAQ
Which has a larger context window, Mistral Large 2 (2407) or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B supports 262k tokens, while Mistral Large 2 (2407) 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 Qwen3.5-122B-A10B?
Mistral Large 2 (2407) is cheaper on tracked token pricing. Mistral Large 2 (2407) costs $0.50/1M input and $1.50/1M 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 (2407) or Qwen3.5-122B-A10B open source?
Mistral Large 2 (2407) 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 (2407) or Qwen3.5-122B-A10B?
Both Mistral Large 2 (2407) 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 (2407) or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B 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 (2407) and Qwen3.5-122B-A10B?
Mistral Large 2 (2407) is available on Microsoft Foundry, Chutes AI, and SiliconFlow. 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.