LFM2.5
A small language model employing a Mixture of Experts (MoE) architecture, in which only a subset of parameters is activated during inference. This design enables relatively fast inference speeds despite a comparatively large model file size.
Timeline (last 90 days)
LFM2.5 uses a Mixture of Experts (MoE) architecture, activating only approximately 1.5 billion parameters when generating each token.
Qwen3.5 with approximately 800 million parameters achieved the fastest generation speed, approaching 15 tokens per second, with the second-place LFM2.5 exceeding 10 tokens per second.
In the summarization task, 4 out of the 8 models failed: the 4-billion-parameter Qwen3.5 fabricated content, LFM2.5 altered facts, Bonsai added nonexistent information, and MiniCPM5 missed key points.
All Facts (3)
LFM2.5 uses a Mixture of Experts (MoE) architecture, activating only approximately 1.5 billion parameters when generating each token.
50%UnverifiedQwen3.5 with approximately 800 million parameters achieved the fastest generation speed, approaching 15 tokens per second, with the second-place LFM2.5 exceeding 10 tokens per second.
50%UnverifiedIn the summarization task, 4 out of the 8 models failed: the 4-billion-parameter Qwen3.5 fabricated content, LFM2.5 altered facts, Bonsai added nonexistent information, and MiniCPM5 missed key points.
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