Qwen2-72B vs Qwen3.5-27B
Qwen2-72B (2024) and Qwen3.5-27B (2026) are frontier reasoning models from Alibaba. Qwen2-72B ships a 128K-token context window, while Qwen3.5-27B ships a 262K-token context window. On pricing, Qwen3.5-27B costs $0.2/1M input tokens versus $0.45/1M 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. The goal is to make the tradeoff clear before deeper testing.
Qwen3.5-27B is ~131% cheaper at $0.2/1M; pay for Qwen2-72B only for provider fit.
Specs
| Released | 2024-06-05 | 2026-02-24 |
| Context window | 128K | 262K |
| Parameters | 72.71B | 27B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Qwen2-72B | Qwen3.5-27B | |
|---|---|---|
| Input price | $0.45/1M tokens | $0.2/1M tokens |
| Output price | $0.65/1M tokens | $1.56/1M tokens |
| Providers |
Capabilities
| Qwen2-72B | Qwen3.5-27B | |
|---|---|---|
| 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, and tool use: Qwen3.5-27B. Both models share structured outputs, 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, Qwen2-72B lists $0.45/1M input and $0.65/1M output tokens, while Qwen3.5-27B lists $0.2/1M input and $1.56/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2-72B lower by about $0.09 per million blended tokens. Availability is 4 providers versus 1, so concentration risk also matters.
Choose Qwen2-72B when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-27B when reasoning depth, 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. 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, Qwen2-72B or Qwen3.5-27B?
Qwen3.5-27B supports 262K tokens, while Qwen2-72B supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, Qwen2-72B or Qwen3.5-27B?
Qwen3.5-27B is cheaper on tracked token pricing. Qwen2-72B costs $0.45/1M input and $0.65/1M output tokens. Qwen3.5-27B costs $0.2/1M input and $1.56/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Qwen2-72B or Qwen3.5-27B open source?
Qwen2-72B is listed under Apache 2.0. Qwen3.5-27B 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 reasoning mode, Qwen2-72B or Qwen3.5-27B?
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, Qwen2-72B or Qwen3.5-27B?
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 Qwen2-72B and Qwen3.5-27B?
Qwen2-72B is available on Fireworks AI, DeepInfra, Together AI, and Microsoft Foundry. Qwen3.5-27B is available on OpenRouter. 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.