Meta-Llama-3-8B-Instruct-abliterated-v3
My Jupyter "cookbook" to replicate the methodology can be found here, refined library coming soon
Params
8.0 B
Context
8,192
Downloads 30d
192 K
Likes
66
Download history
tracking started — chart appears after 7 days of snapshots (3 recorded)192 K downloads in the last 30 days
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 | 16.1 GB | 19.4 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 -s https://aimodelscomparison.com/api/v1/models/meta-llama-3-8b-instruct-abliterated-v3
{
"hf_id": "failspy/Meta-Llama-3-8B-Instruct-abliterated-v3",
"params_b": 8.03,
"context_length": 8192,
"license": { "id": "llama3", "commercial": "conditional" },
"downloads_30d": 191677,
"vram_estimates": [
{ "quant": "bf16", "gb": 19.4 }
],
"updated_at": "2026-10-23T01:00:14Z"
}
Specifications
- Architecture
- LlamaForCausalLM
- Parameters
- 8.0 B
- Tensor type
- BF16
- Context length
- 8,192
- Vocabulary
- 128,256
- Layers / heads
- 32 / 32
- Licence
- llama3
- First seen on the Hub
- 2024-05-20
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-23
Compare with any text-generation model