GPT-4.1 vs GPT-5.6 Sol
GPT-5.6 Sol: 72.4% average across five Vision Evals tasks (#19 of 65 models). GPT-4.1 is deprecated and was not run through Roboflow's Vision Evals, so there is no head-to-head score.
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GPT-4.1 is deprecated and can no longer be run. Details and evals are still available on its model page.
GPT-4.1 vs GPT-5.6 Sol Comparison Table
Evals updated October 26, 2026Pricing updated November 1, 2026
| Property | GPT-4.1 | GPT-5.6 Sol |
|---|---|---|
| Organization | OpenAI | OpenAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Apr 2025 | Jul 2026 |
| Context Window | 1.0M | 1.5M |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $4.00 |
| Output $/1M | $8.00 | $20.00 |
| Vision Tasks | ||
| Captioning | Supported | Demo |
| Classification | Supported | Demo |
| Object Detection | Supported | Demo |
| OCR | Supported | Demo |
| Visual Question Answering | Supported | Demo |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Deprecated | 72.4% |
| Avg cost / sample | – | $0.019 |
| Avg speed / sample | – | 12.16s |
| By task | ||
| Object Detection (low) | – | 68.4% ±0.7, Mean of 3 runs, range 67.9 to 69.3 |
| Object Detection (high) | – | 68.4% ±0.8, Mean of 3 runs, range 67.7 to 69.3 |
| Counting (low) | – | 74.3% ±1.4, Mean of 3 runs, range 73.0 to 75.7 |
| Counting (high) | – | 76.1% ±2.0, Mean of 3 runs, range 74.3 to 78.4 |
| Identification (low) | – | 89.6% ±4.7, Mean of 3 runs, range 84.4 to 93.8 |
| Identification (high) | – | 92.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 |
| OCR (low) | – | 63.6% |
| by category |
| |
| OCR (high) | – | 65.3% |
| by category |
| |
| Reasoning (low) | – | 66.0% ±2.6, Mean of 3 runs, range 63.6 to 68.9 |
| Reasoning (high) | – | 71.7% ±1.3, Mean of 3 runs, range 70.2 to 72.8 |
GPT-4.1 vs GPT-5.6 Sol: Overview
GPT-4.1, released by OpenAI in April 2025, is a multimodal large language model that advances the GPT-4 series with major improvements in coding, reasoning, and instruction following. It accepts both text and images, supports tool calling and structured outputs, and features an expanded context window of up to ~1 million tokens—enabling it to process very large documents, multi-file codebases, or long conversations in a single prompt. Its knowledge is current through June 2024.
The GPT-4.1 family includes standard, mini, and nano variants, offering trade-offs between performance, cost, and latency. While parameter counts remain undisclosed, the series improves efficiency and responsiveness compared to GPT-4, making it suitable for both enterprise-scale tasks and cost-sensitive applications. Common use cases include software development, technical research, knowledge management, multimodal analysis, and high-context enterprise assistants.
GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, which also includes Terra (a balanced everyday-work tier) and Luna (a fast, cost-efficient tier). Sol is designed for demanding reasoning, long-horizon agentic workflows, software engineering, computer use, scientific research, and cybersecurity tasks. It introduces two new capability modes: a "max" reasoning effort setting that allocates additional compute time for difficult problems, and an "ultra" mode that coordinates multiple subagents in parallel to accelerate complex, multi-step work. The model supports native multimodal input, allowing it to process screenshots, diagrams, charts, documents, and photographs alongside text. A reported context window of approximately 1.5 million tokens enables processing of large codebases, lengthy research documents, and extended agentic sessions.
GPT-5.6 Sol was announced on June 26, 2026, initially in a limited preview for trusted partners, and reached general availability on July 9, 2026. On the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields, Sol scores 53.6. The model also demonstrates gains in life sciences evaluations, including long-horizon genomics and quantitative biology analyses. OpenAI paired the release with its most extensive safety evaluation to date, combining human red teaming with large-scale automated testing, and classified Sol as High capability in both cybersecurity and biological risk under its Preparedness Framework, though it does not cross the Critical threshold in either category.