Qwen2.5-Coder 32B Instruct vs Qwen3 VL 32B Thinking
Qwen3 VL 32B Thinking leads the LLM Stats Score 23.5 to 2.0.
Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 32B Thinking leads the overall LLM Stats Score 23.5 to 2.0, ranking #177 overall.
In the 3 individual benchmarks reported for both models, Qwen3 VL 32B Thinking wins 3; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Qwen2.5-Coder 32B Instruct
- you want predictable pricing at $0.09/M input and $0.09/M output
Choose Qwen3 VL 32B Thinking
- overall performance matters — it scores 23.5 and ranks #177 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for Qwen2.5-Coder 32B Instruct · 47 for Qwen3 VL 32B Thinking
Qwen2.5-Coder 32B Instruct outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 3 benchmarks (MMLU, MMLU-Pro, MMLU-Redux).
Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3 VL 32B Thinking has 1.0B more parameters than Qwen2.5-Coder 32B Instruct, making it 3.1% larger.
Context Window
Maximum input and output token capacity
Only Qwen2.5-Coder 32B Instruct specifies input context (128,000 tokens). Only Qwen2.5-Coder 32B Instruct specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3 VL 32B Thinking supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
Qwen3 VL 32B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen2.5-Coder 32B Instruct
Qwen3 VL 32B Thinking
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Qwen2.5-Coder 32B Instruct was released on 2024-09-19, while Qwen3 VL 32B Thinking was released on 2025-09-22.
Qwen3 VL 32B Thinking is 12 months newer than Qwen2.5-Coder 32B Instruct.
Sep 19, 2024
2.0 years ago
Sep 22, 2025
1.0 years 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.
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen2.5-Coder 32B Instruct and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen2.5-Coder 32B Instruct vs Qwen3 VL 32B Thinking.