Qwen2.5-VL-7B-Instruct

Language Alibaba Qwen Partly verified
  • In Input modalities: TextImage Out Output modalities: Text
  • Open weights

Prices

2 offerings · prices as listed
Alibaba Cloud Model Studio (opens in a new tab) Official International · USD qwen2.5-vl-7b-instruct
Conditions/ 1M tokensInputOutput
Standard $0.35$1.05

Prices from models.dev: qwen2-5-vl-7b-instruct (community data, MIT) (opens in a new tab) (checked Oct 15, 2026)

Alibaba Cloud Model Studio (opens in a new tab) Official China · CNY qwen2.5-vl-7b-instruct
Conditions/ 1M tokensInputOutput
Standard ¥2.00¥5.00

Prices from 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
apache-2.0
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-7B-Instruct
  • Parameters 8.3B
  • Dense
  • Native precision BF16
  • Layers 28
  • KV cache per token 56 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
Runs well BF16 (native) (automatic) 8K context 30–44 tok/sOne GPU
WeightsKV cacheOverheadUsable
Needs
≈ 16.7 GB (weights 15.4 (maker’s file) + KV cache 0.4 + overhead 0.8)
Usable
21.6 GB (90% of its memory)
Generation speed
30–44 tok/s
Longest context
98K (longer doesn’t fit)
First token
about 0.27–0.40 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file15.4 GB≈ 16.7Runs well 30–44 tok/s98K
Q8_08.2 GB≈ 9.1Runs well 54–81 tok/s125K
FP87.7 GB≈ 8.7Runs well 58–86 tok/s125K
Q6_K6.3 GB≈ 7.3Runs well 69–104 tok/s125K
Q5_K_M5.5 GB≈ 6.4Runs well 79–119 tok/s125K
Q5_05.3 GB≈ 6.2Runs well 82–123 tok/s125K
Q4_K_M4.7 GB≈ 5.6Runs well 92–137 tok/s125K
Q4_04.3 GB≈ 5.3Runs well 98–147 tok/s125K
INT4 (AWQ / GPTQ)maker’s file6.4 GB≈ 7.4Runs well 68–102 tok/s125K
IQ4_XS4.1 GB≈ 5.0Runs well 103–155 tok/s125K
Q3_K_Mquality drops3.8 GB≈ 4.7Runs well 111–167 tok/s125K
IQ3_XXSquality drops3.0 GB≈ 3.9Runs well 138–208 tok/s125K
Q2_Kquality drops2.9 GB≈ 3.8Runs well 141–211 tok/s125K
IQ2_XXSquality drops2.0 GB≈ 2.9Runs well 193–290 tok/s125K

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 GeForce RTX 3080; unified memory Apple M5 · 16 GB.

Run commands

vLLM
vllm serve Qwen/Qwen2.5-VL-7B-Instruct --max-model-len 8192
Memory to fine-tune
Full≈ 125.8 GBDoesn’t fit your hardware
LoRA≈ 17.9 GBFits your hardware
QLoRA≈ 6.8 GBFits 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

This model isn’t on any leaderboard we cite yet.

  1. Now priced on Alibaba Cloud Model Studio, China Input ¥2.00 · Output ¥5.00
  2. Now priced on Alibaba Cloud Model Studio, International Input $0.35 · Output $1.05
  3. 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