GPT-5.6 Sol vs Grok 4.6
Compare GPT-5.6 Sol and Grok 4.6 side-by-side. See how these vision models stack up in OCR, Image Captioning, Object Detection, Open Prompt, and Classification.
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Models in this comparison
GPT-5.6 Sol vs Grok 4.6 on Vision Evals
GPT-5.6 Sol scores higher on all five Vision Evals tasks.
The widest gap is Object Detection, where GPT-5.6 Sol leads 68.4% to 23.8%.
Overall, GPT-5.6 Sol averages 72.4% (#18 of 63) against 59.1% (#36 of 63) for Grok 4.6.
GPT-5.6 Sol is both cheaper ($0.0096 vs $0.011 per sample) and faster (12.2s vs 19.3s per sample).
GPT-5.6 Sol vs Grok 4.6 Comparison Table
Evals updated October 13, 2026Pricing updated October 13, 2026
| Property | GPT-5.6 Sol | Grok 4.6 |
|---|---|---|
| Organization | OpenAI | SpaceXAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Aug 2026 |
| Context Window | 1.5M | 500K |
| 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 | $2.00 |
| Output $/1M | $10.00 | $6.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | Supported | Supported |
| Classification | Demo | Demo |
| Document Question Answering | Supported | Supported |
| Image Tagging | Supported | Supported |
| Multi-Label Classification | Supported | Supported |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | Supported | Supported |
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Supported |
| Multimodal Vision | Supported | Supported |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 72.4% | 59.1% |
| Avg cost / sample | $0.0096 | $0.011 |
| Avg speed / sample | 12.16s | 19.32s |
| By task | ||
| Object Detection (low) | 68.4% ±0.7, Mean of 3 runs, range 67.9 to 69.3 | 23.8% ±2.8, Mean of 3 runs, range 20.2 to 25.9 |
| Object Detection (high) | 68.4% ±0.8, Mean of 3 runs, range 67.7 to 69.3 | 24.0% ±1.0, Mean of 3 runs, range 23.1 to 25.1 |
| Counting (low) | 74.3% ±1.4, Mean of 3 runs, range 73.0 to 75.7 | 65.8% ±4.1, Mean of 3 runs, range 62.2 to 70.3 |
| Counting (high) | 76.1% ±2.0, Mean of 3 runs, range 74.3 to 78.4 | 56.8% ±1.4, Mean of 3 runs, range 55.4 to 58.1 |
| Identification (low) | 89.6% ±4.7, Mean of 3 runs, range 84.4 to 93.8 | 84.4% ±3.1, Mean of 3 runs, range 81.3 to 87.5 |
| Identification (high) | 92.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 | 85.4% ±1.6, Mean of 3 runs, range 84.4 to 87.5 |
| OCR (low) | 63.6% | 60.6% |
| by category |
|
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| OCR (high) | 65.3% | 61.2% |
| by category |
|
|
| Reasoning (low) | 66.0% ±2.6, Mean of 3 runs, range 63.6 to 68.9 | 61.1% ±1.3, Mean of 3 runs, range 59.6 to 62.3 |
| Reasoning (high) | 71.7% ±1.3, Mean of 3 runs, range 70.2 to 72.8 | 63.8% ±2.0, Mean of 3 runs, range 62.3 to 66.2 |
GPT-5.6 Sol vs Grok 4.6: Overview
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. On Terminal-Bench 2.1, which tests command-line agentic coding workflows, Sol Ultra achieves 91.9%. 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.
Grok 4.6 is a proprietary reasoning model from xAI aimed at long-running agentic workflows, coding, and knowledge work. It accepts text and image input and returns text, with a 500,000 token context window and a knowledge cutoff of February 1, 2026. The model exposes an adjustable reasoning budget with low, medium, high, and xhigh settings, where high is the default, and it supports function calling, structured outputs, web and X search, and code execution as documented tool behaviors. Its visual capability covers interpreting images supplied alongside text prompts, which places it in the visual question answering and document understanding family, and it can also return object detection boxes as text coordinates when prompted.
xAI characterizes Grok 4.6 as the result of an extended post-training run over the Grok 4.5 lineage rather than a new pretrained base. The described recipe combines curated model-generated reasoning and technical data, engineering data, a revised optimizer, regenerated supervised fine-tuning trajectories, and reinforcement learning across agent environments spanning knowledge work, coding, kernel optimization, web development, and computer-aided design. Parameter count and architecture specifics are not disclosed. Independent measurement from Artificial Analysis places the model at 61 on its Intelligence Index, five points above Grok 4.5.