Qwen / text-generation updated 10 months ago

Qwen3-Next-80B-A3B-Instruct-FP8

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
339 K
Likes
89
Commercial use: allowed apache-2.0 Not gated SAFETENSORS View on Hugging Face ↗

Download history

daily snapshots · 10 days
339 K331 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.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
model.safetensors f8_e4m3 82.1 GB 103.0 GB ❌ Won’t fit
model.safetensors (bf16, full) bf16 + 256K ctx 82.1 GB 481.1 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/qwen3-next-80b-a3b-instruct-fp8
{
  "hf_id": "Qwen/Qwen3-Next-80B-A3B-Instruct-FP8",
  "params_b": 81.33,
  "context_length": 262144,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 339404,
  "vram_estimates": [
    { "quant": "f8_e4m3", "gb": 103.0 }
  ],
  "updated_at": "2026-07-28T18:06:17Z"
}
est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture
Qwen3NextForCausalLM
Parameters
81.3 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
2025-09-22
Base model
Qwen3-Next-80B-A3B-Instruct
Training datasets
undisclosed
Added to our catalog
2026-07-28

Family

Base model and the most-downloaded derivatives in the catalog.