GPT-5.1 Thinking vs Qwen2.5-Coder 32B Instruct
GPT-5.1 Thinking leads the LLM Stats Score 36.5 to 2.0. Qwen2.5-Coder 32B Instruct is 38.2x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5.1 Thinking leads the overall LLM Stats Score 36.5 to 2.0, ranking #80 overall.
On price, Qwen2.5-Coder 32B Instruct is roughly 38.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.1 Thinking also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.1 Thinking
- overall performance matters — it scores 36.5 and ranks #80 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Nov 2025
Choose Qwen2.5-Coder 32B Instruct
- cost matters — it's about 38.2x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for GPT-5.1 Thinking · 15 for Qwen2.5-Coder 32B Instruct
GPT-5.1 Thinking and Qwen2.5-Coder 32B 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
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.1 Thinking ($1.25/1M tokens) is 13.9x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, GPT-5.1 Thinking ($10.00/1M tokens) is 111.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, GPT-5.1 Thinking is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.1 Thinking accepts 400,000 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.1 Thinking supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
GPT-5.1 Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.1 Thinking
Qwen2.5-Coder 32B Instruct
License
Usage and distribution terms
GPT-5.1 Thinking is licensed under a proprietary license, while Qwen2.5-Coder 32B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-5.1 Thinking was released on 2025-11-12, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
GPT-5.1 Thinking is 14 months newer than Qwen2.5-Coder 32B Instruct.
Nov 12, 2025
10 months ago
1.1yr newerSep 19, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT-5.1 Thinking is available from OpenAI. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
GPT-5.1 Thinking
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.1 Thinking and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.1 Thinking vs Qwen2.5-Coder 32B Instruct.