GPT-Image-2.5 (Sunburst) vs MiniMax M3.1-Flash-Preview
A direct, empirical evaluation of GPT-Image-2.5 (Sunburst) (OpenAI) against MiniMax M3.1-Flash-Preview (MiniMax).
GPT-Image-2.5 (Sunburst)
Developed by OpenAI · Proprietary Multimodal DiT parameters
High-fidelity typographic rendering, raytracing reflection accuracy, sketch-to-image conditioning, and localized comment inpainting.
MiniMax M3.1-Flash-Preview
Developed by MiniMax · Proprietary Sparse Coding MoE parameters
Low-latency interactive IDE code completions at 165 tokens/sec, SWE-bench Verified bug fixes (73.8%), terminal automation, and budget-optimized pull request reviews.
| Metric | GPT-Image-2.5 (Sunburst) | MiniMax M3.1-Flash-Preview |
|---|---|---|
| SWE-bench Verified | 62.4% | 73.8% |
| MMLU-Pro | 89.5% | 81.2% |
| MATH-500 | 91.2% | 92.4% |
| Context Window | Spatial Vector Token Canvas (1792×1024) | 1,000,000 tokens |
| Input Pricing (per 1M) | $2.50 | $0.10 |
| Output Pricing (per 1M) | $10.00 | $0.40 |