QCRI / text-generation updated 1 year ago

Fanar-1-9B-Instruct

Name: Fanar-1-9B-Instruct
Author: QCRI

Fanar-1-9B-Instruct is a powerful Arabic-English LLM developed by Qatar Computing Research Institute (QCRI) at Hamad Bin Khalifa University (HBKU), a member of Qatar Foundation for Education, Science, and Community Development. It is the instruction-tuned version of Fanar-1-9B. We continually pretrain the google/gemma-2-9b model on 1T Arabic and English tokens. We pay particular attention to the richness of the Arabi...

Params

8.8 B

Context

4,096

Downloads 30d

364 K

Likes

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 2 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

364 K321 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	bf16	17.6 GB	21.1 GB	⚠️ Tight — reduce context

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/fanar-1-9b-instruct
{
  "hf_id": "QCRI/Fanar-1-9B-Instruct",
  "params_b": 8.78,
  "context_length": 4096,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 364070,
  "vram_estimates": [
    { "quant": "bf16", "gb": 21.1 }
  ],
  "updated_at": "2026-07-28T18:06:23Z"
}

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

Specifications

Architecture: Gemma2ForCausalLM
Parameters: 8.8 B
Tensor type: BF16
Context length: 4,096
Vocabulary: 128,256
Layers / heads: 42 / 16
Licence: apache-2.0
First seen on the Hub: 2025-06-01
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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