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: Qwen3 32B
OpenAI: gpt-oss-120b wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for tasks like math, coding, and logical…
Model details →Side-by-side comparison
| Capability | OpenAI: gpt-oss-120b | Qwen: Qwen3 32B | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 131K | 41K | 🏆 OpenAI: gpt-oss-120b |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.04 | $0.08 | 🏆 OpenAI: gpt-oss-120b |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.19 | $0.24 | 🏆 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: Qwen3 32B?
OpenAI: gpt-oss-120b wins on 3 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: Qwen3 32B?
Input: $0.04 vs $0.08 per 1M tokens. Output: $0.19 vs $0.24 per 1M tokens.
What context windows do OpenAI: gpt-oss-120b and Qwen: Qwen3 32B support?
OpenAI: gpt-oss-120b supports up to 131K tokens. Qwen: Qwen3 32B supports up to 41K tokens.
Do both OpenAI: gpt-oss-120b and Qwen: Qwen3 32B support tool calling?
OpenAI: gpt-oss-120b: yes. Qwen: Qwen3 32B: yes.