MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning, …
Model details →MiniMax: MiniMax M2 vs OpenAI: gpt-oss-20b
OpenAI: gpt-oss-20b wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
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 lower-latency inference and deplo…
Model details →Side-by-side comparison
| Capability | MiniMax: MiniMax M2 | OpenAI: gpt-oss-20b | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 197K | 131K | 🏆 MiniMax: MiniMax M2 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.26 | $0.03 | 🏆 OpenAI: gpt-oss-20b |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $1.00 | $0.11 | 🏆 OpenAI: gpt-oss-20b |
| 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 MiniMax: MiniMax M2 better than OpenAI: gpt-oss-20b?
OpenAI: gpt-oss-20b wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between MiniMax: MiniMax M2 and OpenAI: gpt-oss-20b?
Input: $0.26 vs $0.03 per 1M tokens. Output: $1.00 vs $0.11 per 1M tokens.
What context windows do MiniMax: MiniMax M2 and OpenAI: gpt-oss-20b support?
MiniMax: MiniMax M2 supports up to 197K tokens. OpenAI: gpt-oss-20b supports up to 131K tokens.
Do both MiniMax: MiniMax M2 and OpenAI: gpt-oss-20b support tool calling?
MiniMax: MiniMax M2: yes. OpenAI: gpt-oss-20b: yes.