Qwen3-Next-80B-A3B-Instruct
Over the past few months, we have observed increasingly clear trends toward scaling both total parameters and context lengths in the pursuit of more powerful and agentic artificial intelligence (AI). We are excited to share our latest advancements in addressing these demands, centered on improving scaling efficiency through innovative model architecture. We call this next-generation foundation models Qwen3-Next.
Params
81.3 B
Context
262,144
Downloads 30d
330 K
Likes
1,052
Download history
daily snapshots · 55 days
▲ 85 K in the last 30 days (34.5%)
330 K245 K
Aug 22Sep 1Sep 11Sep 20
330 K245 K
Jul 28Aug 15Sep 2Sep 20
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 | 162.7 GB | 191.6 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 256K ctx | 162.7 GB | 569.8 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-next-80b-a3b-instruct
{
"hf_id": "Qwen/Qwen3-Next-80B-A3B-Instruct",
"params_b": 81.32,
"context_length": 262144,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 330404,
"vram_estimates": [
{ "quant": "bf16", "gb": 191.6 }
],
"updated_at": "2026-07-28T18:06:49Z"
}
Specifications
- Architecture
- Qwen3NextForCausalLM
- Parameters
- 81.3 B
- Tensor type
- BF16
- Context length
- 262,144
- Vocabulary
- 151,936
- Layers / heads
- 48 / 16
- Licence
- apache-2.0
- First seen on the Hub
- 2025-09-09
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any text-generation model