gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimize…
Model details →OpenAI: gpt-oss-120b vs Qwen: QwQ 32B
OpenAI: gpt-oss-120b wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problem…
Model details →Side-by-side comparison
| Capability | OpenAI: gpt-oss-120b | Qwen: QwQ 32B | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 131K | 131K | Tie |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.04 | $0.15 | 🏆 OpenAI: gpt-oss-120b |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.19 | $0.58 | 🏆 OpenAI: gpt-oss-120b |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is OpenAI: gpt-oss-120b better than Qwen: QwQ 32B?
OpenAI: gpt-oss-120b wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between OpenAI: gpt-oss-120b and Qwen: QwQ 32B?
Input: $0.04 vs $0.15 per 1M tokens. Output: $0.19 vs $0.58 per 1M tokens.
What context windows do OpenAI: gpt-oss-120b and Qwen: QwQ 32B support?
OpenAI: gpt-oss-120b supports up to 131K tokens. Qwen: QwQ 32B supports up to 131K tokens.
Do both OpenAI: gpt-oss-120b and Qwen: QwQ 32B support tool calling?
OpenAI: gpt-oss-120b: yes. Qwen: QwQ 32B: yes.