Mistral Medium vs Qwen3.5-9B
Mistral Medium (2023) and Qwen3.5-9B (2026) are compact production models from MistralAI and Alibaba. Mistral Medium ships a 32K-token context window, while Qwen3.5-9B ships a 262K-token context window. On Google-Proof Q&A, Qwen3.5-9B leads by 22.8 pts. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $0.40/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3.5-9B is ~300% cheaper at $0.10/1M; pay for Mistral Medium only for provider fit.
Decision scorecard
Local evidence first| Signal | Mistral Medium | Qwen3.5-9B |
|---|---|---|
| Best for | provider-routed production | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, Classification, and JSON / Tool use | RAG, Agents, and Long context |
| Context window | 32K | 262K |
| Cheapest output | $2/1M tokens | $0.15/1M tokens |
| Provider routes | 2 tracked | 3 tracked |
| Shared benchmarks | 1 rows | Google-Proof Q&A leader |
Decision tradeoffs
- Local decision data tags Mistral Medium for Coding, Classification, and JSON / Tool use.
- Qwen3.5-9B leads the largest shared benchmark signal on Google-Proof Q&A by 22.8 points.
- Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling in local model data.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mistral Medium
$820
Cheapest tracked route/tier: OpenRouter
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $703. 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.
- Qwen3.5-9B is $1.85/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Mistral Medium is $1.85/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-12-11 | 2026-03-02 |
| Context window | 32K | 262K |
| Parameters | — | 9B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Mistral Medium | Qwen3.5-9B |
|---|---|---|
| Input price | $0.40/1M tokens | $0.10/1M tokens |
| Output price | $2/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Medium | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | 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 Medium | Qwen3.5-9B |
|---|---|---|
| Google-Proof Q&A | 58.9 | 81.7 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Mistral Medium at 58.9 and Qwen3.5-9B at 81.7, with Qwen3.5-9B ahead by 22.8 points. The largest visible gap is 22.8 points on Google-Proof Q&A, 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: Qwen3.5-9B, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, and tool use: Qwen3.5-9B. 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 Medium lists $0.40/1M input and $2/1M output tokens on the cheapest tracked provider, while Qwen3.5-9B lists $0.10/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-9B lower by about $0.76 per million blended tokens. Availability is 2 providers versus 3, so concentration risk also matters.
Choose Mistral Medium when provider fit are central to the workload. Choose Qwen3.5-9B when long-context analysis, 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 Medium or Qwen3.5-9B?
Qwen3.5-9B supports 262K tokens, while Mistral Medium supports 32K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, Mistral Medium or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Mistral Medium costs $0.40/1M input and $2/1M output tokens. Qwen3.5-9B costs $0.10/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Medium or Qwen3.5-9B open source?
Mistral Medium is listed under Apache 2.0. Qwen3.5-9B 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 Medium or Qwen3.5-9B?
Qwen3.5-9B 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Mistral Medium or Qwen3.5-9B?
Qwen3.5-9B 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 Medium and Qwen3.5-9B?
Mistral Medium is available on Mistral AI Studio and OpenRouter. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.