Unverified50% confidenceFactExact time
Liquid AI's LFM2.5-24B-A2B is a mixture-of-experts (MoE) model with 24B total parameters and only 2.45B activated per token.
1
Sources
50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
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 B300.79% similarUnverifiedIn 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.70% similarUnverifiedWith 64 GB of memory, models with 30B to 34B parameters can run smoothly under Q4 quantization, while a 70B model is barely feasible under Q4 but with a noticeably slower response speed.64% similarUnverifiedQwen3-235B-A22B adopts a MoE architecture, activating only 22B out of 235B total parameters at a time.63% similarUnverifiedWhen running a 35B-parameter model on an 80GB H100 for conversation, each generated token actually uses only about 3B equivalent of weights.63% similar
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