GPT-Image-2.5 (Sunburst) vs NVIDIA Nemotron Labs Dory 1.0
A direct, empirical evaluation of GPT-Image-2.5 (Sunburst) (OpenAI) against NVIDIA Nemotron Labs Dory 1.0 (NVIDIA).
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.
NVIDIA Nemotron Labs Dory 1.0
Developed by NVIDIA · 4 Billion Parameters (Looped Transformer) parameters
Ultra-low VRAM memory residency (4.4 GB FP8), 256k long-context needle retrieval, and recurrent layer depth execution.
| Metric | GPT-Image-2.5 (Sunburst) | NVIDIA Nemotron Labs Dory 1.0 |
|---|---|---|
| SWE-bench Verified | 62.4% | 66.4% |
| MMLU-Pro | 89.5% | 82.8% |
| MATH-500 | 91.2% | 85.6% |
| Context Window | Spatial Vector Token Canvas (1792×1024) | 256,000 tokens |
| Input Pricing (per 1M) | $2.50 | $0.15 |
| Output Pricing (per 1M) | $10.00 | $0.45 |
Architectural & Practical Deployment Analysis
Evaluating GPT-Image-2.5 (Sunburst) (OpenAI) alongside NVIDIA Nemotron Labs Dory 1.0 (NVIDIA) highlights key technical trade-offs across neural parameter scale and compute efficiency. GPT-Image-2.5 (Sunburst) executes across Proprietary Multimodal DiT total parameters with Continuous Flow Transformer active per token, whereas NVIDIA Nemotron Labs Dory 1.0 operates on 4 Billion Parameters (Looped Transformer) parameters with 4.1B Active Recurrent Block (Equivalent to 16B Depth) active per token.
On SWE-bench Verified software engineering tasks, GPT-Image-2.5 (Sunburst) achieves 62.4% autonomous resolution rate, compared to 66.4% for NVIDIA Nemotron Labs Dory 1.0. On complex reasoning benchmarks, GPT-Image-2.5 (Sunburst) posts 89.5% on MMLU-Pro and 91.2% on MATH-500, against 82.8% and 85.6% respectively for NVIDIA Nemotron Labs Dory 1.0.
From an operational economics perspective, processing 10,000,000 mixed tokens (7M input / 3M output) costs approximately $47.50 on GPT-Image-2.5 (Sunburst) versus $2.40 on NVIDIA Nemotron Labs Dory 1.0.
Recommendation: Deploy GPT-Image-2.5 (Sunburst) when your infrastructure prioritizes high-fidelity typographic rendering, raytracing reflection accuracy, sketch-to-image conditioning, and localized comment inpainting.. Deploy NVIDIA Nemotron Labs Dory 1.0 when workload requirements favor ultra-low vram memory residency (4.4 gb fp8), 256k long-context needle retrieval, and recurrent layer depth execution..