LFM2

Name: LFM2
Author: Liquid AI

Liquid AIOpen WeightsPending Human Review

The second Liquid Foundation Model generation uses gated short convolutions alongside attention to improve local inference. Its language checkpoints target instruction following, structured generation, and efficient execution on phones and personal computers. This family page groups the original dense sizes and their instruction checkpoints; later sparse tiers and multimodal models have separate pages. Downloadable weights use the Liquid Open Model License, whose commercial-use conditions should be checked before deployment. Local inference supports private customization, while task reliability and performance require evaluation on the intended hardware.

2025-07-10

350M, 700M, 1.2B, 2.6B

Hybrid short-convolution and attention

Liquid Open Model License 1.0

Compare with other models

Specifications

Parameters: 350M, 700M, 1.2B, 2.6B
Architecture: Hybrid short-convolution and attention
License: Liquid Open Model License 1.0
Context Window: 32,768 tokens
Type: text
Modalities: text

Benchmark Scores

Advanced Specifications

Model Family: LFM
API Access: Not Available
Chat Interface: Available
Multilingual Support: Yes
Variants: LFM2-1.2B

Capabilities & Limitations

Capabilities: instruction followinglocal inferencetext generationtool use
Known Limitations: Custom license conditions applySmall models have limited knowledge and complex reasoning capacityReported speed depends on hardware, precision, and context
Notable Use Cases: local assistantsprivate domain customizationedge agent workflows

Resources

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