Qwen3-Next-80B-A3B-Thinking

Language Alibaba Qwen Partly verified Released Sep 11, 2025
  • In Input modalities: Text Out Output modalities: Text
  • Reasoning
  • Tool use
  • Open weights

Prices

3 offerings · prices as listed
Alibaba Cloud Model Studio (opens in a new tab) Official International · USD qwen3-next-80b-a3b-thinking
Conditions/ 1M tokensInputOutput
Standard no longer listed since Oct 11, 2026 $0.15$1.20

Prices from Alibaba Cloud Model Studio pricing (opens in a new tab) (checked Oct 11, 2026)

Alibaba Cloud Model Studio (opens in a new tab) Official Global · USD qwen3-next-80b-a3b-thinking
Conditions/ 1M tokensInputOutput
Standard no longer listed since Oct 11, 2026 $0.144$1.434

Prices from Alibaba Cloud Model Studio pricing (opens in a new tab) (checked Oct 11, 2026)

Alibaba Cloud Model Studio (opens in a new tab) Official China · CNY qwen3-next-80b-a3b-thinking
Conditions/ 1M tokensInputOutput
Standard no longer listed since Oct 11, 2026 ¥1.00¥10.00

Prices from 阿里云百炼:模型价格 (opens in a new tab) (checked Oct 4, 2026)

Standard: the price a request with no conditions pays (the headline price elsewhere on the site).

Details

Structured output
—
Knowledge cutoff
Apr 2025
Family
qwen-next-thinking
Model ID

Not stated on Alibaba Qwen’s pages: max input, reasoning efforts, reasoning can be off, max thinking budget, built-in tools, licence, aliases.

  • Parameters 81.3B
  • Active 3B · 512 experts, 10 per token
  • Native precision BF16
  • Layers 48
  • KV cache per token 24 KB
  • Native context 256K (model card)
  • Config positions 256K (config.json max_position_embeddings)
  • API context 128K (maker’s API)
My hardware GeForce RTX 4090 24 GB · 1008 GB/s · 64 GB DDR5 dual channel · 89.6 GB/s
On your hardware · GeForce RTX 4090
Needs system memory Q6_K (automatic) 8K context 25–38 tok/s34/48 layers in system memory
WeightsKV cacheOverheadIn system memoryUsable
Needs
≈ 64.3 GB (weights 61.0 (maker’s file) + KV cache 0.2 + overhead 3.1)
Usable
21.6 GB (90% of its memory)
In system memory
43.2 GB · 14/48 layers on the GPU (--n-gpu-layers 14)
Generation speed
25–38 tok/s (reads the active 3B per token)
First token
about 0.10–0.15 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file151.5 GB≈ 159.3Doesn’t fit—
Q8_0maker’s file79.0 GB≈ 83.1Doesn’t fit—
FP8maker’s file76.4 GB≈ 80.4Doesn’t fit—
Q6_Kmaker’s file61.0 GB≈ 64.3Needs system memory 25–38 tok/s—
Q5_K_Mmaker’s file52.8 GB≈ 55.6Needs system memory 38–57 tok/s—
Q5_0maker’s file51.2 GB≈ 54.0Needs system memory 39–59 tok/s—
Q4_K_Mmaker’s file45.1 GB≈ 47.5Needs system memory 45–67 tok/s—
Q4_042.6 GB≈ 44.9Needs system memory 47–71 tok/s—
IQ4_XS40.2 GB≈ 42.4Needs system memory 50–75 tok/s—
Q3_K_Mquality drops37.0 GB≈ 39.1Needs system memory 58–87 tok/s—
IQ3_XXSquality drops29.0 GB≈ 30.6Needs system memory 104–157 tok/s—
Q2_Kquality drops28.4 GB≈ 30.0Needs system memory 107–160 tok/s—
IQ2_XXSquality drops19.5 GB≈ 20.7Runs well 518–776 tok/s48K

Click a row to choose a precision. “Maker’s file” sizes are the maker’s own files; others are parameters × bits per weight.

Compared with other hardware

Each at the highest precision it runs. Click one for details.

Smallest that runs it (Q4_K_M, 8K): GPU NVIDIA H100 SXM; unified memory Apple M5 Max (40-core GPU) · 64 GB.

Run commands

llama.cpp
llama-server -hf Qwen/Qwen3-Next-80B-A3B-Thinking-GGUF:Q6_K -c 8192 --n-gpu-layers 14
Ollama
ollama run hf.co/Qwen/Qwen3-Next-80B-A3B-Thinking-GGUF:Q6_K
Memory to fine-tune
Full≈ 1214.0 GBDoesn’t fit your hardware
LoRA≈ 153.8 GBDoesn’t fit your hardware
QLoRA≈ 45.0 GBDoesn’t fit your hardware

Batch 1, 2,048-token sequences, gradient checkpointing; LoRA and QLoRA train rank-16 adapters on the attention projections.

Estimates; facts from the maker’s Hugging Face repositories, as of 2026-11-06. How it’s estimated

Cited scores

From third-party leaderboards, not measured by us
  • LMArena Text 1,369

    #119 of 163 listed models · CI 1,363–1,375 · 13,476 votes

  • LMArena Text · Chinese 1,402

    #116 of 161 listed models · CI 1,384–1,420 · 1,059 votes

  • LMArena Text · Coding 1,421

    #119 of 163 listed models · CI 1,410–1,432 · 2,666 votes

  • LMArena Text · Creative writing 1,326

    #120 of 163 listed models · CI 1,311–1,340 · 1,776 votes

  • LMArena (Arena), leaderboard-dataset on Hugging Face, licensed CC BY 4.0 · License · as of Oct 28, 2026
  • changes we made
  1. Context window 256K → 131.07K

Sources

Alibaba Qwen’s official policies: data use, privacy, terms →

Some values on this page are still waiting to be checked against official pages: a filled dot is verified, a hollow one is not yet (with or without a source on file). How we verify data

Alibaba Qwen · China · qwen.ai

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