Liquid AI
LFM2.5 8B A1B
Frontier
116.1KDownloads658CurtidasMay 2026Publicado128K tokensContextoOtherLicença58 BomQualidade
LFM2.5 8B A1B (8.5B parameters) requires approximately 6.9 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 1.5B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 8 GB of VRAM.
Comece agora
— copie e cole para rodar localmenteCopy-paste commands to run LFM2.5 8B A1B on your machine.
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lms load LFM2.5-8B-A1B && lms server startQuick specs
Parameters8.5B (1.5B active)
Architecturemoe (MoE)
Context128K tokens
Modalitytext
Min RAM3.3 GB
Rec. RAM5.2 GB (Q4_K_M)
LicenseOther
FamilyLFM2
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About this model
- •Only ~1.5B active parameters per token — MoE efficiency for on-device use.
- •Hybrid short-convolution + grouped-query-attention backbone (LFM2 architecture).
- •128K context, multilingual (en, ar, zh, fr, de, ja, ko).
- •GGUF and MLX builds recommended for llama.cpp and Apple Silicon.
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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 | 3.3 GB | Low | — |
Q3_K_S | 3 | 4.2 GB | Low | — |
NVFP4 | 4 | 4.8 GB | Medium | — |
Q4_K_M | 4 | 5.2 GB | Medium | — |
Q5_K_M | 5 | 6.1 GB | High | — |
Q6_K | 6 | 7.0 GB | High | — |
Q8_0 | 8 | 9.1 GB | Very High | — |
F16 | 16 | 17.4 GB | Maximum | — |
Compatibilidade de hardware
Estimativas de compatibilidade para todo o hardware
Computing compatibility...
Detalhamento de memória
Reference: RTX 2060 6GB
Weights5.2 GB
KV Cache0.2 GB
Runtime0.9 GB
Headroom0.6 GB
Perguntas frequentes
FAQ — LFM2.5 8B A1B
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