01What it can do
- Completely free Apache 2.0
- 128k context on 2.5B
- Fits in 1.4 GB VRAM at Q4
- Multilingual code and reasoning
- —Capabilities limited by the 2.5B size
- —Gated model on Hugging Face
- —Less versatile than the 7-14B models
04Install
Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.
02Required memory
Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.
What hardware do you need for MiniMax M2.5 2.5B?
To run MiniMax M2.5 2.5B locally with Q4 quantization, you need about 1.4 GB of VRAM. An option to compare: RTX 5060 Ti 16GB (ASUS Prime) — leave some headroom for the system and context; check engine compatibility with the GPU.
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On the go: MiniMax M2.5 2.5B also runs on a RTX laptop PC (16 GB of VRAM) →
03Expected speed
Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.