Liquid AI
LFM2 24B
FrontierJun 2025Publicado131K tokensContextoApache 2.0Licença78 ForteQualidade
LFM2 24B (24B parameters) requires approximately 18.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 22 GB of VRAM.
Comece agora
— copie e cole para rodar localmenteCopy-paste commands to run LFM2 24B on your machine.
Run
ollama run lfm2Quick specs
Parameters24B
Architecturedense
Context131K tokens
Modalitytext
Min RAM9.4 GB
Rec. RAM14.6 GB (Q4_K_M)
LicenseApache 2.0
FamilyLFM
✓ Code✓ Chat✓ Reasoning
About this model
- •Hybrid SSM-Transformer architecture for efficient inference
- •Linear-time scaling for long context processing
- •Competitive with larger dense transformers on reasoning tasks
Escolhas rápidas
Melhor hardware
Melhores opções para LFM2 24B
Rodar este modelo
Opções de quantização
Estimativas de VRAM por nível de quantização
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | — |
Q3_K_S | 3 | 11.8 GB | Low | — |
NVFP4 | 4 | 13.4 GB | Medium | — |
Q4_K_M | 4 | 14.6 GB | Medium | — |
Q5_K_M | 5 | 17.3 GB | High | — |
Q6_K | 6 | 19.7 GB | High | — |
Q8_0 | 8 | 25.7 GB | Very High | — |
F16 | 16 | 49.2 GB | Maximum | — |
Compatibilidade de hardware
Estimativas de compatibilidade para todo o hardware
Computing compatibility...
Detalhamento de memória
Reference: RTX 2060 6GB
Weights14.6 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom0.6 GB
Perguntas frequentes
FAQ — LFM2 24B
Veja também