MiniCPM5 2B VRAM requirements

VRAM by quantization

Weights plus the KV cache for 8,192 tokens in FP16 and the runtime overhead (0.5 GB plus 10%). Each row opens the calculator with that setting. What the GGUF names mean.

KV cache at long context

All 42 layers use full attention. Each extra token of context adds 42 KB of FP16 cache per request. How the KV cache works.

Which GPUs can run MiniCPM5 2B

With 8,192 tokens of context. Several GPUs means one tensor-parallel group of 2, 4 or 8 cards.

How fast MiniCPM5 2B writes

Tokens per second for one request with 8,192 tokens of context, estimated from memory bandwidth. A dash means it does not fit on one card. Try other settings in the speed calculator.

Longest context on one GPU

How many tokens of context fit on a single card with one request and an FP16 KV cache. "Full" means the model's whole context window fits.

Model details

Parameters

2.5B (2,516,756,480)

Layers

All 42 layers use full attention

Attention cache

2 KV heads × 128

Context length

131,072 tokens

Published weights

4.69 GB (BF16)

On Hugging Face

openbmb/MiniCPM5-2B

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