LLM Comparison
MiniMax M2.5 vs MiniMind
Side-by-side specs, pricing & capabilities · Updated September 2026
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 47 | |
| Family | MiniMax | MiniMind |
| Status | Current | Current |
| Release Date | Feb 2026 | Sep 2026 |
| Context Window | 197K tokens | 1K tokens |
| Input Price | — | — |
| Output Price | — | — |
| Pricing Notes | Free tier available on OpenRouter with rate limits | Open-source project; API pricing is not applicable unless a downstream host adds serving costs. |
| Capabilities | textcode | texteducationtraining |
| Training Cutoff | — | Not specified |
| Max Output | 8K tokens | 1K tokens |
| API Identifier | minimax/minimax-m2.5:free | jingyaogong/minimind |
| Benchmarks | ||
| GPQA Diamond | 84.8485artificial-analysis | — |
| View MiniMax M2.5 | View MiniMind | |
MiniMax
MiniMax M2.5
MiniMax M2.5 is a large language model from MiniMax. Supports up to 196,608 token context window. Available free with rate limits on OpenRouter.
Jingyao Gong
MiniMind
MiniMind is a small open-source language-model training project that demonstrates how to train a 64M-parameter LLM from scratch. The repository is aimed at builders who want a compact, inspectable model-training path rather than a hosted frontier API.
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