Mixtral 8x22B v0.1 vs Together AI - Qwen3.5-9B
Mixtral 8x22B v0.1 (2024) and Together AI - Qwen3.5-9B (2026) are compact production models from MistralAI and Alibaba. Mixtral 8x22B v0.1 ships a 64K-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 $0.3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Together AI - Qwen3.5-9B is ~200% cheaper at $0.1/1M; pay for Mixtral 8x22B v0.1 only for long-context analysis.
Specs
| Released | 2024-04-17 | 2026-02-01 |
| Context window | 64K | 33K |
| Parameters | 8x22B | 9B |
| Architecture | mixture of experts | decoder only |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Mixtral 8x22B v0.1 | Together AI - Qwen3.5-9B | |
|---|---|---|
| Input price | $0.3/1M tokens | $0.1/1M tokens |
| Output price | $0.9/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Mixtral 8x22B v0.1 | 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, Mixtral 8x22B v0.1 lists $0.3/1M input and $0.9/1M 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 $0.36 per million blended tokens. Availability is 8 providers versus 1, so concentration risk also matters.
Choose Mixtral 8x22B v0.1 when long-context analysis, larger context windows, and broader provider choice 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, Mixtral 8x22B v0.1 or Together AI - Qwen3.5-9B?
Mixtral 8x22B v0.1 supports 64K 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, Mixtral 8x22B v0.1 or Together AI - Qwen3.5-9B?
Together AI - Qwen3.5-9B is cheaper on tracked token pricing. Mixtral 8x22B v0.1 costs $0.3/1M input and $0.9/1M 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 Mixtral 8x22B v0.1 or Together AI - Qwen3.5-9B open source?
Mixtral 8x22B v0.1 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, Mixtral 8x22B v0.1 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, Mixtral 8x22B v0.1 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 Mixtral 8x22B v0.1 and Together AI - Qwen3.5-9B?
Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API, Fireworks AI, DeepInfra, and Baseten API. Together AI - Qwen3.5-9B is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.