GPT-6 Rosalind vs Qwen2.5-Coder 32B Instruct
Comparing GPT-6 Rosalind and Qwen2.5-Coder 32B Instruct across benchmarks, pricing, and capabilities.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-6 Rosalind and Qwen2.5-Coder 32B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Qwen2.5-Coder 32B Instruct is roughly 333.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6 Rosalind
- you want the most recent training data — it shipped Oct 2026
Choose Qwen2.5-Coder 32B Instruct
- cost matters — it's about 333.3x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
0 reported for GPT-6 Rosalind · 15 for Qwen2.5-Coder 32B Instruct
GPT-6 Rosalind 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-6 Rosalind ($15.00/1M tokens) is 166.7x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, GPT-6 Rosalind ($75.00/1M tokens) is 833.3x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, GPT-6 Rosalind 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
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
GPT-6 Rosalind supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
GPT-6 Rosalind can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Rosalind
Qwen2.5-Coder 32B Instruct
License
Usage and distribution terms
GPT-6 Rosalind 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-6 Rosalind was released on 2026-10-30, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
GPT-6 Rosalind is 26 months newer than Qwen2.5-Coder 32B Instruct.
Oct 30, 2026
5 days ago
2.1yr newerSep 19, 2024
2.1 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-6 Rosalind is available from OpenAI. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
GPT-6 Rosalind
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Rosalind and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Rosalind vs Qwen2.5-Coder 32B Instruct.