Mistral Medium 3.5 vs Qwen3.5-9B
Mistral Medium 3.5 (2026) and Qwen3.5-9B (2026) are frontier reasoning models from MistralAI and Alibaba. Mistral Medium 3.5 ships a 256K-token context window, while Qwen3.5-9B ships a 262K-token context window. On MMLU PRO, Qwen3.5-9B leads by 2.7 pts. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $1.50/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3.5-9B is ~1400% cheaper at $0.10/1M; pay for Mistral Medium 3.5 only for reasoning depth.
Decision scorecard
Local evidence first| Signal | Mistral Medium 3.5 | Qwen3.5-9B |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 256K | 262K |
| Cheapest output | $7.50/1M tokens | $0.15/1M tokens |
| Provider routes | 3 tracked | 3 tracked |
| Shared benchmarks | 2 rows | MMLU PRO leader |
Decision tradeoffs
- Mistral Medium 3.5 uniquely exposes Reasoning in local model data.
- Local decision data tags Mistral Medium 3.5 for Coding, RAG, and Agents.
- Qwen3.5-9B leads the largest shared benchmark signal on MMLU PRO by 2.7 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.
- Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mistral Medium 3.5
$3,075
Cheapest tracked route/tier: Mistral AI Studio
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $2,958. 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 $7.35/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Mistral Medium 3.5 is $7.35/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Medium 3.5 adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-29 | 2026-03-02 |
| Context window | 256K | 262K |
| Parameters | 128B | 9B |
| Architecture | decoder only | decoder only |
| License | Mistral License | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Mistral Medium 3.5 | Qwen3.5-9B |
|---|---|---|
| Input price | $1.50/1M tokens | $0.10/1M tokens |
| Output price | $7.50/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Mistral Medium 3.5 | Qwen3.5-9B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| 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 Medium 3.5 | Qwen3.5-9B |
|---|---|---|
| MMLU PRO | 79.8 | 82.5 |
| Google-Proof Q&A | 71.3 | 81.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has Mistral Medium 3.5 at 79.8 and Qwen3.5-9B at 82.5, with Qwen3.5-9B ahead by 2.7 points; Google-Proof Q&A has Mistral Medium 3.5 at 71.3 and Qwen3.5-9B at 81.7, with Qwen3.5-9B ahead by 10.4 points. The largest visible gap is 10.4 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 reasoning mode: Mistral Medium 3.5. 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 Medium 3.5 lists $1.50/1M input and $7.50/1M 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 $3.18 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.
Choose Mistral Medium 3.5 when reasoning depth 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 3.5 or Qwen3.5-9B?
Qwen3.5-9B supports 262K tokens, while Mistral Medium 3.5 supports 256K 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 Medium 3.5 or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Mistral Medium 3.5 costs $1.50/1M input and $7.50/1M 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 3.5 or Qwen3.5-9B open source?
Mistral Medium 3.5 is listed under Mistral License. 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 3.5 or Qwen3.5-9B?
Both Mistral Medium 3.5 and Qwen3.5-9B 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 Medium 3.5 or Qwen3.5-9B?
Both Mistral Medium 3.5 and Qwen3.5-9B 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 Medium 3.5 and Qwen3.5-9B?
Mistral Medium 3.5 is available on Mistral AI Studio, OpenRouter, and Vercel AI Gateway. 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: 2026-05-22. Data sourced from public model cards and provider documentation.