Qwen3.5-27B vs Together AI Mixtral-8x7B-Instruct-v0.1
Qwen3.5-27B (2026) and Together AI Mixtral-8x7B-Instruct-v0.1 (2023) are frontier reasoning models from Alibaba and MistralAI. Qwen3.5-27B ships a 262K-token context window, while Together AI Mixtral-8x7B-Instruct-v0.1 ships a 33K-token context window. On pricing, Qwen3.5-27B costs $0.2/1M 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.
Qwen3.5-27B is ~105% cheaper at $0.2/1M; pay for Together AI Mixtral-8x7B-Instruct-v0.1 only for provider fit.
Specs
| Released | 2026-02-24 | 2023-12-10 |
| Context window | 262K | 33K |
| Parameters | 27B | 56B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Qwen3.5-27B | Together AI Mixtral-8x7B-Instruct-v0.1 | |
|---|---|---|
| Input price | $0.2/1M tokens | $0.4/1M tokens |
| Output price | $1.56/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| Qwen3.5-27B | 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 reasoning mode: Qwen3.5-27B, function calling: Qwen3.5-27B, tool use: Qwen3.5-27B, and structured outputs: Qwen3.5-27B. 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, Qwen3.5-27B lists $0.2/1M input and $1.56/1M 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 $0.2 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Qwen3.5-27B when reasoning depth, 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.
FAQ
Which has a larger context window, Qwen3.5-27B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-27B 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, Qwen3.5-27B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-27B is cheaper on tracked token pricing. Qwen3.5-27B costs $0.2/1M input and $1.56/1M 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 Qwen3.5-27B or Together AI Mixtral-8x7B-Instruct-v0.1 open source?
Qwen3.5-27B 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 reasoning mode, Qwen3.5-27B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-27B has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, Qwen3.5-27B or Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-27B 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.
Where can I run Qwen3.5-27B and Together AI Mixtral-8x7B-Instruct-v0.1?
Qwen3.5-27B 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.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.