Mistral Mixtral-8x7B-Instruct vs Together AI - Qwen3.5-9B
Mistral Mixtral-8x7B-Instruct (2024) and Together AI - Qwen3.5-9B (2026) are compact production models from MistralAI and Alibaba. Mistral Mixtral-8x7B-Instruct ships a 33K-token context window, while Together AI - Qwen3.5-9B ships a 33K-token context window. On pricing, Together AI - Qwen3.5-9B costs $0.1/1M input tokens versus $0.45/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Together AI - Qwen3.5-9B is ~350% cheaper at $0.1/1M; pay for Mistral Mixtral-8x7B-Instruct only for long-context analysis.
Specs
| Released | 2024-04-09 | 2026-02-01 |
| Context window | 33K | 33K |
| Parameters | 46.7B total, 12.9B active | 9B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Mistral Mixtral-8x7B-Instruct | Together AI - Qwen3.5-9B | |
|---|---|---|
| Input price | $0.45/1M tokens | $0.1/1M tokens |
| Output price | $0.7/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Mistral Mixtral-8x7B-Instruct | Together AI - Qwen3.5-9B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: Together AI - Qwen3.5-9B, tool use: Together AI - Qwen3.5-9B, and structured outputs: Together AI - Qwen3.5-9B. Both models share the core language-model surface, 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 Mixtral-8x7B-Instruct lists $0.45/1M input and $0.7/1M output tokens, while Together AI - Qwen3.5-9B lists $0.1/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Together AI - Qwen3.5-9B lower by about $0.41 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Mistral Mixtral-8x7B-Instruct when long-context analysis and larger context windows are central to the workload. Choose Together AI - Qwen3.5-9B when provider fit 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.
FAQ
Which has a larger context window, Mistral Mixtral-8x7B-Instruct or Together AI - Qwen3.5-9B?
Mistral Mixtral-8x7B-Instruct supports 33K tokens, while Together AI - Qwen3.5-9B supports 33K 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 Mixtral-8x7B-Instruct or Together AI - Qwen3.5-9B?
Together AI - Qwen3.5-9B is cheaper on tracked token pricing. Mistral Mixtral-8x7B-Instruct costs $0.45/1M input and $0.7/1M output tokens. Together AI - Qwen3.5-9B costs $0.1/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mistral Mixtral-8x7B-Instruct or Together AI - Qwen3.5-9B open source?
Mistral Mixtral-8x7B-Instruct is listed under Apache 2.0. Together AI - Qwen3.5-9B is listed under Open Source. 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 function calling, Mistral Mixtral-8x7B-Instruct or Together AI - Qwen3.5-9B?
Together AI - Qwen3.5-9B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Mistral Mixtral-8x7B-Instruct or Together AI - Qwen3.5-9B?
Together AI - Qwen3.5-9B has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Mistral Mixtral-8x7B-Instruct and Together AI - Qwen3.5-9B?
Mistral Mixtral-8x7B-Instruct is available on AWS Bedrock. Together AI - Qwen3.5-9B is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.