gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
Model details →OpenAI: gpt-oss-20b (batch) vs Qwen: Qwen3 14B
OpenAI: gpt-oss-20b (batch) wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Model details →Side-by-side comparison
| Capability | OpenAI: gpt-oss-20b (batch) | Qwen: Qwen3 14B | 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. | $0.05 | $0.12 | 🏆 OpenAI: gpt-oss-20b (batch) |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.20 | $0.24 | 🏆 OpenAI: gpt-oss-20b (batch) |
| Tool / function calling First-class support for emitting structured tool calls. | — | Yes | 🏆 Qwen: Qwen3 14B |
| 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-20b (batch) better than Qwen: Qwen3 14B?
OpenAI: gpt-oss-20b (batch) 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-20b (batch) and Qwen: Qwen3 14B?
Input: $0.05 vs $0.12 per 1M tokens. Output: $0.20 vs $0.24 per 1M tokens.
What context windows do OpenAI: gpt-oss-20b (batch) and Qwen: Qwen3 14B support?
OpenAI: gpt-oss-20b (batch) supports up to 131K tokens. Qwen: Qwen3 14B supports up to 131K tokens.
Do both OpenAI: gpt-oss-20b (batch) and Qwen: Qwen3 14B support tool calling?
OpenAI: gpt-oss-20b (batch): not advertised. Qwen: Qwen3 14B: yes.