GPT-5.5 vs Grok 4.6
Compare GPT-5.5 and Grok 4.6 side-by-side. See how these vision models stack up in Object Detection, Image Captioning, Classification, Open Prompt, and OCR.
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GPT-5.5 vs Grok 4.6 on Vision Evals
GPT-5.5 scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where GPT-5.5 leads 41.7% to 20.2%.
Overall, GPT-5.5 averages 73.9% (#12 of 31) against 67.8% (#17 of 31) for Grok 4.6.
Grok 4.6 is both cheaper ($0.0069 vs $0.022 per sample) and faster (7.4s vs 9.3s per sample).
GPT-5.5 vs Grok 4.6 Comparison Table
Evals updated August 20, 2026Pricing updated August 23, 2026
| Property | GPT-5.5 | Grok 4.6 |
|---|---|---|
| Organization | OpenAI | SpaceXAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Apr 2026 | Aug 2026 |
| Context Window | 1.0M | 500K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $2.00 |
| Output $/1M | $30.00 | $6.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 73.9% | 67.8% |
| Avg cost / sample | $0.022 | $0.0069 |
| Avg speed / sample | 9.35s | 7.39s |
| By task | ||
| Object Detection | 41.7% $0.034 | 20.2% $0.0068 |
| Counting | 64.9% $0.015 | 70.3% $0.0074 |
| Identification | 90.6% $0.0085 | 78.1% $0.0048 |
| OCR | 91.2% $0.023 | 92.0% $0.0086 |
| Data Extraction | 87.6% $0.010 | 84.5% $0.0042 |
| Reasoning (low) | 67.5% $0.014 | 61.6% $0.0087 |
| Reasoning (high) | 69.5% $0.030 | 61.6% $0.027 |
GPT-5.5 vs Grok 4.6: Overview
GPT-5.5 is a multimodal large language model released by OpenAI on April 23, 2026, engineered for autonomous, multi-step knowledge work and agentic workflows. It accepts text, images, and code as input, featuring enhanced spatial reasoning and visual grounding to support its computer use capabilities for operating software and navigating UI elements. Built to execute complex workflows end-to-end, the model interprets loosely defined tasks, selects appropriate tools, and performs self-verification with minimal user intervention. It is available in a standard version, a Thinking mode for extended reasoning budgets, and a Pro variant that uses parallel test-time compute for maximum precision on complex tasks.
Co-optimized with NVIDIA for GB200 NVL72 infrastructure, GPT-5.5 delivers per-token latency comparable to its predecessor GPT-5.4 while maintaining a 1-million-token context window. Despite increased capability, the model achieves greater token efficiency in coding and data analysis workflows, often completing tasks with fewer total tokens than previous versions. OpenAI reports a 60% reduction in hallucination rate compared to GPT-5.4, improving reliability for accuracy-sensitive applications. API access is available via the Responses and Chat Completions endpoints at $5 per million input tokens and $30 per million output tokens, double the unit price of GPT-5.4.
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.