Model ID
LiquidAI/LFM2.5-8B-A1B
Capabilities
LFM2.5 8B A1B
LFM2.5 8B A1B is a compact hybrid Mixture-of-Experts model designed for on-device personal assistants, tool use, instruction following, and agentic workflows. It features 8.3B total parameters with 1.5B active, using 24 layers that combine 18 double-gated convolution blocks with 6 GQA attention blocks. The architecture employs a 2,048-dimensional hidden size, 32 attention heads, 8 KV heads, and 32 experts with 4 activated per token. Supporting a 128K-token context window, it is trained on 38T tokens for efficient, high-throughput multilingual inference across ten languages and diverse edge devices.
About this model
LFM2.5 8B A1B is a compact hybrid Mixture-of-Experts model designed for on-device personal assistants, tool use, instruction following, and agentic workflows. It features 8.3B total parameters with 1.5B active, using 24 layers that combine 18 double-gated convolution blocks with 6 GQA attention blocks. The architecture employs a 2,048-dimensional hidden size, 32 attention heads, 8 KV heads, and 32 experts with 4 activated per token. Supporting a 128K-token context window, it is trained on 38T tokens for efficient, high-throughput multilingual inference across ten languages and diverse edge devices.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (LiquidAI/LFM2.5-8B-A1B). Released under LFM 1.0. Further reading: Paper · Blog
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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