👁 Liquid AI
Liquid AI
LFM2 24B
Frontier
Jun 2025Released131K tokensContextApache 2.0License78 StrongQuality
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.
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— copy & paste to run locallyCopy-paste commands to run LFM2 24B on your machine.
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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
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Quantization options
VRAM estimates by quant level
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 | — |
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights14.6 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom0.6 GB
Frequently asked questions
FAQ — LFM2 24B
See also