LGAI-EXAONE / text-generation updated 6 months ago

EXAONE-3.5-7.8B-Instruct-AWQ

Name: EXAONE-3.5-7.8B-Instruct-AWQ
Author: LGAI-EXAONE

We introduce EXAONE 3.5, a collection of instruction-tuned bilingual (English and Korean) generative models ranging from 2.4B to 32B parameters, developed and released by LG AI Research. EXAONE 3.5 language models include: 1) 2.4B model optimized for deployment on small or resource-constrained devices, 2) 7.8B model matching the size of its predecessor but offering improved performance, and 3) 32B model delivering po...

Params

7.8 B

Context

32,768

Downloads 30d

389 K

Likes

Licence: other Not gated SAFETENSORS 2 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

389 K295 K

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	5.3 GB	7.5 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 32K ctx	5.3 GB	11.0 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/exaone-3-5-7-8b-instruct-awq
{
  "hf_id": "LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct-AWQ",
  "params_b": 7.82,
  "context_length": 32768,
  "license": { "id": "other", "commercial": "unknown" },
  "downloads_30d": 389108,
  "vram_estimates": [
    { "quant": "i32", "gb": 7.5 }
  ],
  "updated_at": "2026-07-28T18:06:44Z"
}

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

Specifications

Architecture: ExaoneForCausalLM
Parameters: 7.8 B
Tensor type: I32
Context length: 32,768
Vocabulary: 102,400
Licence: other
First seen on the Hub: 2024-12-01
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

Qwen3-8B 16.3 M Qwen2.5-7B-Instruct 12.1 M Qwen3.6-35B-A3B-NVFP4 11.3 M Llama-3.1-8B-Instruct 8.0 M Qwen2.5-7B-Instruct-AWQ 4.6 M granite-4.1-8b 4.2 M

Appears in

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