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 (batch) vs Qwen: Qwen3 8B
Qwen: Qwen3 8B wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,...
Model details →Side-by-side comparison
| Capability | OpenAI: gpt-oss-120b (batch) | Qwen: Qwen3 8B | 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. | $0.15 | $0.12 | 🏆 Qwen: Qwen3 8B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.60 | $0.46 | 🏆 Qwen: Qwen3 8B |
| 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 (batch) better than Qwen: Qwen3 8B?
Qwen: Qwen3 8B 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 (batch) and Qwen: Qwen3 8B?
Input: $0.15 vs $0.12 per 1M tokens. Output: $0.60 vs $0.46 per 1M tokens.
What context windows do OpenAI: gpt-oss-120b (batch) and Qwen: Qwen3 8B support?
OpenAI: gpt-oss-120b (batch) supports up to 131K tokens. Qwen: Qwen3 8B supports up to 131K tokens.
Do both OpenAI: gpt-oss-120b (batch) and Qwen: Qwen3 8B support tool calling?
OpenAI: gpt-oss-120b (batch): yes. Qwen: Qwen3 8B: yes.