nm-testing / text-generation updated 2 weeks ago

SmolLM-1.7B-Instruct-quantized.w4a16

Name: SmolLM-1.7B-Instruct-quantized.w4a16
Author: nm-testing

- Model Architecture: SmolLM-135M-Instruct - Input: Text - Output: Text - Model Optimizations: - Weight quantization: INT4 - Intended Use Cases: Intended for commercial and research use in English. Similarly to SmolLM-135M-Instruct, this models is intended for assistant-like chat. - Out-of-scope: Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in languages other t...

Params

1.8 B

Context

2,048

Downloads 30d

1.5 M

Likes

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

1.5 M1.4 M

Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	i32	1.7 GB	2.7 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub

~ · curl · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/smollm-1-7b-instruct-quantized-w4a16
{
  "hf_id": "nm-testing/SmolLM-1.7B-Instruct-quantized.w4a16",
  "params_b": 1.84,
  "context_length": 2048,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 1506527,
  "vram_estimates": [
    { "quant": "i32", "gb": 2.7 }
  ],
  "updated_at": "2026-07-28T18:03:11Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: LlamaForCausalLM
Parameters: 1.8 B
Tensor type: I32
Context length: 2,048
Vocabulary: 49,152
Layers / heads: 24 / 32
Licence: apache-2.0
First seen on the Hub: 2024-08-23
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

Qwen3-0.6B 29.7 M Qwen2.5-1.5B-Instruct 14.0 M Llama-3.2-1B-Instruct 10.4 M Qwen3-1.7B 7.8 M Qwen2.5-3B-Instruct 6.0 M Qwen2-1.5B-Instruct 3.2 M

Appears in

Best open coding models Commercial-use text models Models that fit in 12 GB