Qwen3.5-397B-A17B vs Together AI Mixtral-8x7B-Instruct-v0.1
Qwen3.5-397B-A17B (2026) and Together AI Mixtral-8x7B-Instruct-v0.1 (2023) are compact production models from Alibaba and MistralAI. Qwen3.5-397B-A17B ships a 262K-token context window, while Together AI Mixtral-8x7B-Instruct-v0.1 ships a 33K-token context window. On pricing, Qwen3.5-397B-A17B costs $0.39/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.5-397B-A17B fits 8x more tokens; pick it for long-context work and Together AI Mixtral-8x7B-Instruct-v0.1 for tighter calls.
Specs
| Released | 2026-02-16 | 2023-12-10 |
| Context window | 262K | 33K |
| Parameters | 397B | 56B |
| Architecture | MoE | decoder only |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Qwen3.5-397B-A17B | Together AI Mixtral-8x7B-Instruct-v0.1 | |
|---|---|---|
| Input price | $0.39/1M tokens | $0.4/1M tokens |
| Output price | $2.34/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| Qwen3.5-397B-A17B | Together AI Mixtral-8x7B-Instruct-v0.1 | |
|---|---|---|
| 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 multimodal input: Qwen3.5-397B-A17B and structured outputs: Qwen3.5-397B-A17B. 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, Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens, while Together AI Mixtral-8x7B-Instruct-v0.1 lists $0.4/1M input and $0.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Together AI Mixtral-8x7B-Instruct-v0.1 lower by about $0.57 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Qwen3.5-397B-A17B when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Together AI Mixtral-8x7B-Instruct-v0.1 when provider fit 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Qwen3.5-397B-A17B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-397B-A17B supports 262K tokens, while Together AI Mixtral-8x7B-Instruct-v0.1 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, Qwen3.5-397B-A17B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-397B-A17B is cheaper on tracked token pricing. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Together AI Mixtral-8x7B-Instruct-v0.1 costs $0.4/1M input and $0.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Qwen3.5-397B-A17B or Together AI Mixtral-8x7B-Instruct-v0.1 open source?
Qwen3.5-397B-A17B is listed under Apache 2.0. Together AI Mixtral-8x7B-Instruct-v0.1 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 multimodal input, Qwen3.5-397B-A17B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-397B-A17B 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.
Which is better for structured outputs, Qwen3.5-397B-A17B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-397B-A17B has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Qwen3.5-397B-A17B and Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-397B-A17B is available on OpenRouter. Together AI Mixtral-8x7B-Instruct-v0.1 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.