Qwen3-Coder-Next-FP8
To Run Qwen3-Coder-Next locally - Read our Guide! Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.
Params
79.7 B
Context
262,144
Downloads 30d
250 K
Likes
11
Download history
daily snapshots · 7 days250 K199 K
Sep 15Sep 17Sep 19Sep 21
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 | f8_e4m3 | 80.4 GB | 100.9 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 256K ctx | 80.4 GB | 471.4 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 -s https://aimodelscomparison.com/api/v1/models/qwen3-coder-next-fp8-unsloth
{
"hf_id": "unsloth/Qwen3-Coder-Next-FP8",
"params_b": 79.68,
"context_length": 262144,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 250342,
"vram_estimates": [
{ "quant": "f8_e4m3", "gb": 100.9 }
],
"updated_at": "2026-09-15T01:00:34Z"
}
Specifications
- Architecture
- Qwen3NextForCausalLM
- Parameters
- 79.7 B
- Tensor type
- F8_E4M3
- Context length
- 262,144
- Vocabulary
- 151,936
- Layers / heads
- 48 / 16
- Licence
- apache-2.0
- First seen on the Hub
- 2026-02-03
- Base model
- Qwen3-Coder-Next
- Training datasets
- undisclosed
- Added to our catalog
- 2026-09-15
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any text-generation model