Can RTX 4090 run LFM2.5 24B-A2B?
Yes. Measured 261-339 tok/s generation (llama.cpp, llama-bench tg128 (quant per result); source).
Every measured result for LFM2.5 24B-A2B on RTX 4090
| Build | Quant / setup | Engine | tok/s | |
|---|---|---|---|---|
| RTX 4090: 2026 models (llamabench community) | llama-bench tg128 (quant per result) | llama.cpp | 261-339 | source |
Memory: RTX 4090 has 24 GB. LFM2.5 24B-A2B weights are about 14.7 GB at Q4_K_M (23.97B params × 4.89 bits ÷ 8, before context/KV cache). Arithmetic, not a measurement; long contexts need more. Check other quants in the VRAM calculator.
Speeds are decode (generation) tokens/sec as reported by each source; quant, engine and context differ, so small gaps are noise.
All measured speeds for LFM2.5 24B-A2B: best home rig for LFM2.5 24B-A2B.
LFM2.5 24B-A2B on other hardware: RTX 3060 12GB · RTX 4060 Ti 16GB
Other models measured on RTX 4090: Flint 40B-A2.5B · GLM 4.7 Flash · Gemma 4 12B · Gemma 4 26B-A4B · Gemma 4 31B · Nemotron 3.5 Bolt 74B-A9B · Qwen3.5 9B · Qwen3.6 27B · Qwen3.6 35B-A3B · gpt-oss 20B
Not enough VRAM? Rent before you buy. Run LFM2.5 24B-A2B on a bigger GPU on a rented 24–96 GB cloud GPU by the hour and see the real speed before spending €1,000+. Try it on Runpod
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Referral link: if you sign up with Google and add $10, Runpod gives you and RigBase bonus credit (terms). It never affects our data.