Can I run LFM2.5-24B-A2B-FP8 on an RTX 5090?

Yes, just

Its published weights (24.7 GB) fit in the 28.8 GB an RTX 5090 can use, with room for ≈ 128K tokens of context.

Full analysis of LFM2.5-24B-A2B-FP8 Everything that runs on RTX 5090 Get the weights on Hugging Face

hf download LiquidAI/LFM2.5-24B-A2B-FP8

Files and context on RTX 5090

Each file of LFM2.5-24B-A2B-FP8 (and of GGUF versions the site has analyzed), and how much context fits next to it, with the context cache in 16-bit or 8-bit.

File	Size	On RTX 5090	Context (16-bit)	Context (8-bit)
As published	24.7 GB	Tight	128K	128K
4-bit (estimate)	13.5 GB	Fits	128K	128K

LFM2.5-24B-A2B-FP8 on other hardware

NVIDIA H100Yes
RTX 5090Yes, just
RTX 4090Probably, at 4-bit
RTX 3090Probably, at 4-bit
RTX 5060 Ti 16 GBProbably, at 4-bit
RTX 3060 12 GBNo
RTX 4060No
Mac with 32 GBProbably, at 4-bit
Mac with 64 GBYes
Mac with 128 GBYes

Popular models that run on RTX 5090

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Qwen3-8BQwen · 8.19B
Qwen3-Coder-30B-A3B-Instruct-GGUFunsloth · 30.5B
Qwen2.5-7B-InstructQwen · 7.62B
Qwen3.5-9BQwen · 9.65B
Qwen2.5-0.5B-InstructQwen · 494M

Assumes 90% of the card's memory is usable and at least 4K tokens of context for one conversation, with the context cache in 16-bit unless noted. Fits leaves at least 20% of that memory for context; Tight leaves less.