infosave / LFM2.5-cmf

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Model's Last Updated: August 28 2026
text-generation

Introduction of LFM2.5-cmf

Model Details of LFM2.5-cmf

LFM2.5 → CMF — one file, one Rust binary, no Python

cargo install cortiq-cli
hf download infosave/LFM2.5-cmf lfm2.5-2.6b-q4tp.cmf --local-dir .
cortiq run lfm2.5-2.6b-q4tp.cmf --prompt "Explain what a Fourier transform does, in two sentences."

LiquidAI's LFM2.5 is a hybrid: most layers mix with a short gated convolution and only a few carry full attention, so the state a token needs is small and constant where the convolution runs. These are those checkpoints in the CMF container — a single memory-mapped file read by cortiq , a Rust binary with no ML framework under it. GPU via Vulkan/Metal/DX12 with a CPU fallback; NVIDIA, AMD, Intel and Apple silicon read the same file.

file params layers size
lfm2.5-230m-q4tp.cmf 0.23B 14 (5 attention / 9 conv) 132 MB
lfm2.5-2.6b-q4tp.cmf 2.70B 30 (8 attention / 22 conv) 1.43 GB
lfm2.5-8b-a1b-q4tp.cmf 8.3B total, 1B active 24 (6 attention / 18 conv), 32 experts, 4 per token 4.6 GB

All three are 4-bit tiled with ladder scales ( q4tp ), quantized straight from the bf16 checkpoints.

Speed

Steady-state decode, cortiq bench --core , single stream, cortiq 0.5.99+ (the whole-token graph learned this family's short-conv mixer and its sigmoid-routed MoE in 0.5.98/0.5.99 — earlier versions decode it an order of magnitude slower).

A100 80GB (Vulkan) Apple M4
230M 390 tok/s 138 tok/s
2.6B 141 tok/s 42 tok/s ( CMF_GPU=0 )
8B-A1B 124 tok/s

On a discrete card the whole token runs as one submitted graph, conv ring and expert routing included; the MoE's greedy output is token-identical to the CPU path. On Apple silicon the engine measures both arms at startup and picks; for the 2.6B the host arm wins there, and CMF_GPU=0 pins it.

Server and API
cortiq serve lfm2.5-2.6b-q4tp.cmf --port 8080

Speaks the OpenAI API, so anything that talks to OpenAI talks to it:

curl localhost:8080/v1/chat/completions -H 'content-type: application/json' \
  -d '{"model":"lfm2.5","messages":[{"role":"user","content":"Say hello"}]}'
Checksums

Each .cmf ships a .sha256 beside it.

Runs of infosave LFM2.5-cmf on huggingface.co

835
Total runs
39
24-hour runs
190
3-day runs
269
7-day runs
820
30-day runs

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LFM2.5-cmf huggingface.co

LFM2.5-cmf huggingface.co is an AI model on huggingface.co that provides LFM2.5-cmf's model effect (), which can be used instantly with this infosave LFM2.5-cmf model. huggingface.co supports a free trial of the LFM2.5-cmf model, and also provides paid use of the LFM2.5-cmf. Support call LFM2.5-cmf model through api, including Node.js, Python, http.

infosave LFM2.5-cmf online free

LFM2.5-cmf huggingface.co is an online trial and call api platform, which integrates LFM2.5-cmf's modeling effects, including api services, and provides a free online trial of LFM2.5-cmf, you can try LFM2.5-cmf online for free by clicking the link below.

infosave LFM2.5-cmf online free url in huggingface.co:

https://huggingface.co/infosave/LFM2.5-cmf

LFM2.5-cmf install

LFM2.5-cmf is an open source model from GitHub that offers a free installation service, and any user can find LFM2.5-cmf on GitHub to install. At the same time, huggingface.co provides the effect of LFM2.5-cmf install, users can directly use LFM2.5-cmf installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

LFM2.5-cmf install url in huggingface.co:

https://huggingface.co/infosave/LFM2.5-cmf

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