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DeepSeek-V2.5 vs Qwen2-VL-72B-Instruct

Qwen2-VL-72B-Instruct leads the LLM Stats Score 14.3 to 8.1.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen2-VL-72B-Instruct leads the overall LLM Stats Score 14.3 to 8.1, ranking #237 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V2.5

  • you want predictable pricing at $0.14/M input and $0.28/M output

Choose Qwen2-VL-72B-Instruct

  • overall performance matters — it scores 14.3 and ranks #237 on LLM Stats
  • you want the most recent training data — it shipped Aug 2024

At a glance

The differences that matter most.

Core performance indexes
8.1
#281
14.3
#237
8.2
#277
11.6
#252
Cost, coverage & limits
Benchmark wins
Input price
$0.14 / M
— / M
Output price
$0.28 / M
— / M
Context window
8,192

Individual benchmarks

15 reported for DeepSeek-V2.5 · 15 for Qwen2-VL-72B-Instruct

No common benchmarks found

DeepSeek-V2.5 and Qwen2-VL-72B-Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

162.6B diff

DeepSeek-V2.5 has 162.6B more parameters than Qwen2-VL-72B-Instruct, making it 221.5% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
73.4Bparameters
236.0B
DeepSeek-V2.5
73.4B
Qwen2-VL-72B-Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen2-VL-72B-Instruct supports multimodal inputs, whereas DeepSeek-V2.5 does not.

Qwen2-VL-72B-Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V2.5

Text
Images
Audio
Video

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Qwen2-VL-72B-Instruct uses tongyi-qianwen.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V2.5

deepseek

Open weights

Qwen2-VL-72B-Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

Qwen2-VL-72B-Instruct is 4 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.4 years ago

Qwen2-VL-72B-Instruct

Aug 29, 2024

2.1 years ago

3mo newer

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while DeepSeek-V2.5's cutoff date is not specified.

We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without DeepSeek-V2.5's cutoff date.

DeepSeek-V2.5

Qwen2-VL-72B-Instruct

Jun 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V2.5 and Qwen2-VL-72B-Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V2.5
✓ Preferred
Qwen2-VL-72B-Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V2.5 vs Qwen2-VL-72B-Instruct.

Which is better, DeepSeek-V2.5 or Qwen2-VL-72B-Instruct?

Qwen2-VL-72B-Instruct leads the LLM Stats Score 14.3 to 8.1. DeepSeek-V2.5 is made by DeepSeek and Qwen2-VL-72B-Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V2.5 compare to Qwen2-VL-72B-Instruct in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench: 86.5%.

What are the context window sizes for DeepSeek-V2.5 and Qwen2-VL-72B-Instruct?

DeepSeek-V2.5 supports 8K tokens and Qwen2-VL-72B-Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V2.5 and Qwen2-VL-72B-Instruct?

Key differences include LLM Stats Score (8.1 vs 14.3), multimodal support (no vs yes), licensing (deepseek vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V2.5 and Qwen2-VL-72B-Instruct?

DeepSeek-V2.5 is developed by DeepSeek and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.