HuggingFace/Dense

HuggingFaceSmolLM2 1.7B

Best-in-class tiny model. Surprisingly capable for chat on minimal hardware.

chatTool Use
1.71B
Parameters
8K
Context length
8
Benchmarks
6
Quantizations
400K
HF downloads
Architecture
Dense
Released
2024-11-21
Layers
24
KV Heads
32
Head Dim
64
Family
smollm

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.891.5 GBgood
Q5_K_S5.571.7 GBgood
Q5_K_M5.71.7 GBgood
Q6_K6.561.9 GBexcellent
Q8_08.52.3 GBlossless
FP16163.9 GBlossless

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

READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN SMOLLM2 1.7B NOW

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

Community Ratings

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Benchmarks (8)

Arena Elo1062
IFEval55.0
HumanEval22.0
MMLU-PRO11.7
BBH10.9
MATH5.8
MUSR4.1
GPQA3.9

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run smollm2:1.7b-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 SmolLM2 1.7B

Build Hardware for SmolLM2 1.7B

Best-in-class tiny model. Surprisingly capable for chat on minimal hardware.

▸ SPEC SHEET

SmolLM2 1.7B1.71B Dense.

▸ SPECIFICATIONS
PARAMETERS
1.71B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
8K tokens
CAPABILITIES
chat
RELEASE DATE
2024-11-21
PROVIDER
HuggingFace
FAMILY
smollm
▸ 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
HumanEval22.0
MMLU-PRO11.7
MATH5.8
IFEval55.0
BBH10.9
GPQA3.9
MUSR4.1
Arena Elo1062.0
§ 02RUN COMMAND

Run SmolLM2 1.7B locally with Ollama — needs 1.5 GB VRAM at Q4_K_M:

$ollama run smollm2:1.7b