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
Download history
daily snapshots · 10 days339 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.
| File | Quant | Size | Est. VRAM | Verdict 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 -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"
}
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.
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