Qwen2.5-VL-72B-Instruct

Language Alibaba Qwen Partly verified Released Feb 6, 2025
  • In Input modalities: TextImage Out Output modalities: Text
  • Open weights

Prices

1 offering · prices as listed
Alibaba Cloud Model Studio (opens in a new tab) Official China · CNY qwen2.5-vl-72b-instruct
ConditionsInput/ 1K tokensInput/ 1M tokensOutput/ 1K tokensOutput/ 1M tokens
Standard —¥16.00—¥48.00

Prices from 阿里云百炼:模型价格 (opens in a new tab) (checked Oct 2, 2026) · How to check model training and deployment pricing-Alibaba Cloud Model Studio(Model Studio)-阿里云帮助中心 (opens in a new tab) (checked Nov 1, 2026)

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

Details

Reasoning
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Tool use
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Structured output
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Knowledge cutoff
Apr 2024
Licence
Qwen LICENSE AGREEMENT
Family
qwen-vl
Model ID

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

Run locally

Weights: Qwen/Qwen2.5-VL-72B-Instruct
  • Parameters 73.4B
  • Dense
  • Native precision BF16
  • Layers 80
  • KV cache per token 320 KB
  • Config positions 125K (config.json max_position_embeddings)
  • API context 977K (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 IQ4_XS (automatic) 8K context 2–3 tok/s42/80 layers in system memory
WeightsKV cacheOverheadIn system memoryUsable
Needs
≈ 40.6 GB (weights 36.3 + KV cache 2.5 + overhead 1.8)
Usable
21.6 GB (90% of its memory)
In system memory
19.1 GB · 38/80 layers on the GPU (--n-gpu-layers 38)
Generation speed
2–3 tok/s
First token
about 2.37–3.56 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file136.7 GB≈ 146.1Doesn’t fit—
Q8_072.6 GB≈ 78.8Doesn’t fit—
FP868.4 GB≈ 74.3Doesn’t fit—
Q6_K56.1 GB≈ 61.5Doesn’t fit—
Q5_K_M48.6 GB≈ 53.6Doesn’t fit—
Q5_047.0 GB≈ 51.9Doesn’t fit—
Q4_K_M41.5 GB≈ 46.1Doesn’t fit—
Q4_038.5 GB≈ 42.9Needs system memory 2–3 tok/s—
INT4 (AWQ / GPTQ)maker’s file40.1 GB≈ 44.6Needs system memory 2–3 tok/s—
IQ4_XS36.3 GB≈ 40.6Needs system memory 2–3 tok/s—
Q3_K_Mquality drops33.4 GB≈ 37.6Needs system memory 2–4 tok/s—
IQ3_XXSquality drops26.2 GB≈ 30.0Needs system memory 4–6 tok/s—
Q2_Kquality drops25.6 GB≈ 29.4Needs system memory 4–7 tok/s—
IQ2_XXSquality drops17.6 GB≈ 21.0Runs well 23–35 tok/s10K

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

The maker publishes no files at this precision. Choose its native precision or one of its own builds, or quantise it yourself with llama.cpp.

Memory to fine-tune
Full≈ 1098.6 GBDoesn’t fit your hardware
LoRA≈ 142.4 GBDoesn’t fit your hardware
QLoRA≈ 44.1 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 Vision 1,107

    #79 of 89 listed models · CI 1,097–1,118 · 3,768 votes

  • LMArena (Arena), leaderboard-dataset on Hugging Face, licensed CC BY 4.0 · License · as of Oct 19, 2026
  • changes we made
  1. 2 new prices on Alibaba Cloud Model Studio, China Input ¥16.00 · Output ¥48.00
  2. New language model

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

Snapshots, the same family and other models from this provider