LocalClaw/LLM/LFM3 1.7B
Open-weight local LLM

LFM3 1.7B

Use case: General local assistant. Check the memory fit and choose a setup path below.

8 GB short-context planning estimate8 GB RAMQ4_K_MGeneral local assistant
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Open on Hugging FaceFiles, licence and available downloads
llama.cppNot available for this model
Use with LocalClawOptional workspace after the model is installed
This model needs its official runtimellama.cpp containing 19cce6919992fdffd92e0ac152caaf1e2b8f254e (PR 31252); start with -c 4096
Parameters
1.73B
RAM planning estimate
8 GB
Model size
1.1 GB
Quantization
Q4_K_M

About LFM3 1.7B

Catalogue summary: Liquid AI tri-hybrid text model for multilingual chat, tool calling and structured outputs. Official Q4_K_M GGUF is 1.10GB. Plan for 8GB RAM at short context. Requires LFM3-enabled llama.cpp; not recommended for agentic coding or complex reasoning.

LFM3 1.7B has a 8 GB short-context RAM planning estimate based on its 1.1 GB GGUF. This is not a measured minimum or a guarantee at maximum context.

Use the official llama.cpp containing 19cce6919992fdffd92e0ac152caaf1e2b8f254e (PR 31252); start with -c 4096 setup. The current low-bit files are not a stock LM Studio install.

Model sourcePublic GGUF repository (verified 2026-11-06): LiquidAI/LFM3-1.7B-GGUFUpstream releaseLicence text
chattool-callinglightmultilinguallong-context

Install path

01
Check RAM fitPlan for 8 GB RAM at short context; this is an estimate. Use Q4_K_M.
02
Load the modelFollow the official llama.cpp containing 19cce6919992fdffd92e0ac152caaf1e2b8f254e (PR 31252); start with -c 4096 instructions. Stock LM Studio support is not confirmed.
03
Try your workloadStart with a short prompt, check memory use and adjust context length before running longer tasks.

Download formats for this model

These are quantizations of the same model. The RAM fit above uses Q4_K_M; larger files need more memory. File sizes exclude the runtime, context cache and optional vision projector.

Catalogue record

  • Family: lfm
  • Parameters: 1.73B
  • Recommended quantization: Q4_K_M
  • Short-context RAM estimate: 8 GB
  • Catalogue model size: 1.1 GB
  • Tags: chat, tool-calling, light, multilingual, long-context

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.

Reading the scores

LocalClaw /10 is an editorial catalogue rating. Community /5 comes from member reviews. Your machine fit is a separate memory and runtime assessment.

Capability profile

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

speed
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quality
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coding
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reasoning
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Technical notes

Developer
Liquid AI
License
LFM 1.0
Context window
262,144 tokens
Architecture
24-layer tri-hybrid LFM3 backbone: 13 gated short convolutions, 5 sliding-window attention and 6 global attention layers. 1.73B parameters.

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.

LFM2.5-24B-A2B 24B (2.45B active, MoE)LFM2.5-2.6B 2.7BLFM2.5-8B-A1B 8.3B (1.5B active)LFM2.5-VL-3B 3B multimodalLFM3 VL 2B 1.92BAgents-A1 4B 4BNanbeige4.2 3B 4B (3B non-embedding)Spark-X2.5-1.7B 1.7B

Where to go next