What GPU do I need to run moonshotai/Kimi-Linear-48B-A3B-Instruct?
49.1B parameters, published in BF16. View on Hugging Face
Kimi-Linear-48B-A3B-Instruct is published by moonshotai on Hugging Face, with 179,264 downloads and 580 likes to date. It's a KimiLinearForCausalLM model built for text-generation, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 caveat: requires a quantized checkpoint actually published for this model — check its Hugging Face page before relying on this row.
Cheapest way to run Kimi-Linear-48B-A3B-Instruct at its published (BF16) precision: 7× RTX 5060 Ti on simplepod, at $0.100/hr per GPU ($0.700/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More moonshotai models
- Kimi-K2-Instruct (1026.4B, F8_E4M3)
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- gpt2 (137M, F32)
- Qwen3.5-9B (9.7B, BF16)
- Qwen3.6-35B-A3B-FP8 (36.0B, F8_E4M3)
