Qwen2.5 72B Instruct vs Qwen3 VL 235B A22B Thinking
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Qwen2.5 72B Instruct is 3.3x cheaper per token.
Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen2.5 72B Instruct outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 3 benchmarks (IFEval, MMLU-Pro, MMLU-Redux). Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
On price, Qwen2.5 72B Instruct is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 235B A22B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Qwen2.5 72B Instruct
- cost matters — it's about 3.3x cheaper per token
Choose Qwen3 VL 235B A22B Thinking
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Qwen2.5 72B Instruct outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 3 benchmarks (IFEval, MMLU-Pro, MMLU-Redux).
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen2.5 72B Instruct ($0.35/1M tokens) is 1.3x cheaper than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, Qwen2.5 72B Instruct ($0.40/1M tokens) is 8.7x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than Qwen2.5 72B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 VL 235B A22B Thinking has 163.3B more parameters than Qwen2.5 72B Instruct, making it 224.6% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to Qwen2.5 72B Instruct's 131,072 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while Qwen2.5 72B Instruct is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas Qwen2.5 72B Instruct does not.
Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen2.5 72B Instruct
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
Qwen2.5 72B Instruct is licensed under Qwen, while Qwen3 VL 235B A22B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Qwen
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Qwen2.5 72B Instruct was released on 2024-09-19, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.
Qwen3 VL 235B A22B Thinking is 12 months newer than Qwen2.5 72B Instruct.
Sep 19, 2024
1.9 years ago
Sep 22, 2025
11 months ago
1.0yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Qwen2.5 72B Instruct is available from DeepInfra, Hyperbolic, Fireworks, Together. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
Qwen2.5 72B Instruct
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen2.5 72B Instruct and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen2.5 72B Instruct vs Qwen3 VL 235B A22B Thinking.