Unverified50% confidenceFactExact time
In the LFM2.5 series, text models besides 24B also include 230M, 350M, 1.2B (including Instruct, Thinking, and JP versions), 2.6B, and 8B-A1B MoE; 24B is the only model that enters the 30B-class MoE race.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/14/2026
First Seen
Valid until: 1/12/2027
Sources
Related Entities
Related Claims
UnverifiedLiquidAI's LFM2.5-24B-A2B uses sparse MoE to activate only 2B per token out of 24B total parameters, extends context from 32K to 131K, runs at 184 tok/s on an Apple M5 Max, and reaches aggregate throughput of up to 21K tok/s on a single NVIDIA B300.71% similarUnverifiedLiquid AI's LFM2.5-24B-A2B is a mixture-of-experts (MoE) model with 24B total parameters and only 2.45B activated per token.70% similarUnverifiedThe BF16 weights of the 27B model are approximately 54GB (27B × 2 bytes).69% similarUnverifiedLFM2.5-24B-A2B uses a 40-layer architecture: 30 double-gated short convolution blocks + 10 GQA attention layers, 64 experts per MoE block, top-4 routing, a 131,072 token context, and a 128K vocabulary.68% similar
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