Models / LFM2.5generated from capability-matrix.json
LFM2.5
Liquid AI's LFM2 and LFM2.5: short convolutions mixed with attention.
chatsafetensors
Get it
goinfer can't fetch this one yet. Download the safetensors folder with your usual tool, then point goinfer at it.
goinfer-serve -model ./path/to/checkpoint-folderWhat hasn't been shown
- Runs on the CPU only today. Not eligible to live on a GPU.
- goinfer can't download it for you: this family only loads from safetensors, which come as several files. That's planned (checkpoint fetch, P1–P9).
- No vetted checkpoint, so there's no fit verdict, no speed and no tool-calling result for this family.
How sure we are
Against the released model100.0%
picks the same next token as HuggingFace
1.00000
closest the raw scores get at their worst position (cosine, 1.00000 is identical; bar starts at 0.95)
full-oracle 100.0%/1.00000 · what parity-gated means
Measured speed · decode, tokens per second
not measured — no vetted checkpoint to measure
Architecture, for the curious
- model_type
- lfm2
- design
- softmax-GQA
- experts
- dense
- attention window
- none
- QK-norm
- yes
- RoPE
- full
- norm
- RMSNorm, pre-norm
- activation
- SwiGLU
- tied head
- yes
- modality
- text
- GPU-resident
- no
registry description: Liquid AI LFM2/LFM2.5 hybrid: a gated short convolution on most layers, GQA + QK-norm on the rest (CPU-only — no backend implements FeatShortConv)