LocalClaw/LLM/LFM2.5-8B-A1B
Open-weight local LLM

LFM2.5-8B-A1B

Catalogue summary: Liquid AI hybrid model built for on-device assistants. 8.3B total / 1.5B active, 128K context, tool use, GGUF, ONNX, MLX, llama.cpp and LM Studio support. Open-weight under LFM 1.0.

Repository editorial metadata; verify comparative claims in the linked upstream material.

8 GB catalogue minimum8 GB RAMQ4_K_MCoding assistant
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Open in LM StudioOpens the app on this model's download screenOpen in UnslothLaunches Unsloth Desktop on this model's download page
OllamaNot available for this model
Open on Hugging FaceFiles, licence and available downloadsOpen llama.cpp setupAdvanced option: opens the model filesUse with LocalClawOptional workspace after the model is installed

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Parameters
8.3B (1.5B active)
Minimum RAM
8 GB
Model size
5.2 GB
Quantization
Q4_K_M

Can LFM2.5-8B-A1B run locally?

LFM2.5-8B-A1B has a catalogue minimum of 8 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use lfm2.5-8b-a1b as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

Public GGUF repository (verified 2026-09-07): LiquidAI/LFM2.5-8B-A1B-GGUFUpstream releasePaper or model cardLicence text
chatcodereasoningspeedstandardgeneral

Install path

01
Check RAM fitMinimum 8 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch lfm2.5-8b-a1b in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: lfm
  • Parameters: 8.3B (1.5B active)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 8 GB
  • Catalogue model size: 5.2 GB
  • Tags: chat, code, reasoning, speed, standard, general

Practical limits

  • Catalogue RAM is a minimum estimate, not a guarantee for every context length or runtime.
  • Speed and memory use vary by quantization, backend, context length and system headroom.
  • Verify architecture, licence and usage restrictions in the linked upstream material before deployment.

Catalogue tags

  • chat
  • code
  • reasoning
  • speed
  • standard
  • general

Capability profile

Repository catalogue ratings used by LocalClaw's editorial rubric. They are not a standardized third-party benchmark.

speed
9
quality
8
coding
8
reasoning
8

Technical notes

Developer
Liquid AI
License
LFM 1.0
Context window
128,000 tokens
Architecture
Hybrid Liquid Foundation Model with 8.3B total parameters and 1.5B active parameters. The model mixes double-gated LIV convolution layers with grouped-query attention.

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Entry laptop fitMacBook Air 8GBMore headroomMac mini M4 16GBAll compatible picks8GB RAM guide

Related catalogue entries

Linked mechanically by family, shared tags and nearby RAM tier; this is not a quality ranking.

LFM2.5-2.6B 2.7BLFM2.5-VL-3B 3B multimodalGranite 3.3 (8B Instruct) 8BGranite 4.1 (8B) 8BGranite 4.2 (8B) 8.8BLing-3.0-tiny 7.9B (1.3B active, MoE)Ornith 1.0 9B GGUF 9BQwen 3 (8B) 8B

Where to go next