FitMyLLM
Liquid AI/Dense

Liquid AILFM3 1.7B

LFM3 1.7B — Liquid AI's first LFM3 text model, built on a new tri-hybrid layout of short convolutions, sliding-window and global attention. Post-trained for local agents and tool calling with a 256K context; only 6 of its 24 layers keep a full KV cache.

chatagentictool_usemultilingual
1.73B
Parameters
256K
Context length
4
Benchmarks
6
Quantizations
48K
HF downloads
Architecture
Dense
Released
2026-10-27
Layers
24
KV Heads
4
Head Dim
128
Family
lfm

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
1.7 GB
1.5 + 0.1 KV
good
Q5_K_S5.57
1.8 GB
1.7 + 0.1 KV
good
Q5_K_M5.7
1.9 GB
1.7 + 0.1 KV
good
Q6_K6.56
2.0 GB
1.9 + 0.1 KV
excellent
Q8_08.5
2.5 GB
2.3 + 0.1 KV
lossless
FP1616
4.1 GB
3.9 + 0.1 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN LFM3 1.7B NOW

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (4)

LiveCodeBench73.5
GPQA Diamond63.4
SWE-bench43.4
HLE7.2

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run lfm3:1.7b-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Find the best GPU for LFM3 1.7B

Build Hardware for LFM3 1.7B
▸ SPEC SHEET

LFM3 1.7B — 1.73B Dense.

▸ SPECIFICATIONS
PARAMETERS
1.73B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, agentic, tool_use, multilingual
RELEASE DATE
2026-10-27
PROVIDER
Liquid AI
FAMILY
lfm
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.891.5 GB94%
Q5_K_S5.571.7 GB96%
Q5_K_M5.71.7 GB96%
Q6_K6.561.9 GB97%
Q8_08.52.3 GB100%
FP16163.9 GB100%
§ 01BENCHMARK SCORES
GPQA Diamond63.4
LiveCodeBench73.5
HLE7.2
SWE-bench43.4
§ 02RUN COMMAND

Run LFM3 1.7B locally with Ollama — needs 1.5 GB VRAM at Q4_K_M:

$ollama run lfm3:1.7b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M