Liquid AI
LFM2.5 8B A1B
最先端
116.1Kダウンロード658いいねMay 2026公開日128K トークンコンテキストOtherライセンス58 良好品質
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.
はじめに
— コピー&ペーストでローカル実行Copy-paste commands to run LFM2.5 8B A1B on your machine.
Run
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
✓ Chat
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.
関連モデル
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最適なハードウェア
LFM2.5 8B A1Bのおすすめ
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量子化オプション
量子化レベル別VRAM推定値
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 | — |
ハードウェア互換性
全ハードウェアの適合度推定
Computing compatibility...
メモリ内訳
Reference: RTX 2060 6GB
Weights5.2 GB
KV Cache0.2 GB
Runtime0.9 GB
Headroom0.6 GB
よくある質問
FAQ — LFM2.5 8B A1B
関連項目