gpt-oss-safeguard-20b vs MiniMax M2.1
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for gpt-oss-safeguard-20b and MiniMax M2.1.
gpt-oss-safeguard-20b
gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...
MiniMax M2.1
MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world...
Technical Specifications
| Specification | gpt-oss-safeguard-20b | MiniMax M2.1 |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Context Window | 131,072 tokens | 204,800 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-10-29 | 2025-12-23 |
API Pricing Comparison
Input Price per Million Tokens
gpt-oss-safeguard-20b
$0.07
MiniMax M2.1
$0.30
Output Price per Million Tokens
gpt-oss-safeguard-20b
$0.30
MiniMax M2.1
$1.20
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
gpt-oss-safeguard-20b Quirks & Gotchas
No developer gotchas reported.
MiniMax M2.1 Quirks & Gotchas
No developer gotchas reported.