Qwen2-72B vs Qwen3-105B
Qwen2-72B (2024) and Qwen3-105B (2025) are compact production models from Alibaba. Qwen2-72B ships a 128K-token context window, while Qwen3-105B ships a 128k-token context window. 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.
Qwen3-105B is safer overall; choose Qwen2-72B when provider fit matters.
Specs
| Released | 2024-06-05 | 2025-12-15 |
| Context window | 128K | 128k |
| Parameters | 72.71B | 105B |
| Architecture | decoder only | - |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | 2025-02 |
Pricing and availability
| Qwen2-72B | Qwen3-105B | |
|---|---|---|
| Input price | $0.45/1M tokens | - |
| Output price | $0.65/1M tokens | - |
| Providers | - |
Capabilities
| Qwen2-72B | Qwen3-105B | |
|---|---|---|
| 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: Qwen3-105B, tool use: Qwen3-105B, and structured outputs: Qwen2-72B. 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.
Pricing coverage is uneven: Qwen2-72B has $0.45/1M input tokens and Qwen3-105B has no token price sourced yet. Provider availability is 4 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Qwen2-72B when provider fit and broader provider choice are central to the workload. Choose Qwen3-105B 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, Qwen2-72B or Qwen3-105B?
Qwen2-72B supports 128K tokens, while Qwen3-105B 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.
Is Qwen2-72B or Qwen3-105B open source?
Qwen2-72B is listed under Apache 2.0. Qwen3-105B 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, Qwen2-72B or Qwen3-105B?
Qwen3-105B 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, Qwen2-72B or Qwen3-105B?
Qwen3-105B 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.
Which is better for structured outputs, Qwen2-72B or Qwen3-105B?
Qwen2-72B 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 Qwen2-72B and Qwen3-105B?
Qwen2-72B is available on Fireworks AI, DeepInfra, Together AI, and Microsoft Foundry. Qwen3-105B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.