yuxinlu1 / text-generation updated 1 month ago

gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2

Name: gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2
Author: yuxinlu1

> This is the full-precision safetensors master for my Gemma 4 12B coding + agentic fine-tune — the same > model many of you have been running as GGUF, now in its original weights. 🧠🛠️ v2 is the big agentic upgrade: > it reads, reasons, uses tools, and works through multi-step technical tasks before it acts. This repo is for > builders — roll your own quants, fine-tune further, or run it in transformers.

Params

12.0 B

Context

—

Downloads 30d

266 K

Likes

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

Download history

daily snapshots · 10 days

266 K206 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	f16	23.9 GB	28.6 GB	❌ Won’t fit

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/gemma-4-12b-agentic-fable5-composer2-5-v2-3-5x-tau2
{
  "hf_id": "yuxinlu1/gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2",
  "params_b": 11.96,
  "context_length": null,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 266452,
  "vram_estimates": [
    { "quant": "f16", "gb": 28.6 }
  ],
  "updated_at": "2026-07-28T18:08:05Z"
}

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

Specifications

Architecture: Gemma4UnifiedForConditionalGeneration
Parameters: 12.0 B
Tensor type: F16
Licence: apache-2.0
First seen on the Hub: 2026-06-28
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

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Appears in

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