Claude Haiku 5.5 vs Grok 4.6
Compare Claude Haiku 5.5 and Grok 4.6 side-by-side.
Compare Claude Haiku 5.5 vs Grok 4.6 live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Claude Haiku 5.5 vs Grok 4.6 on Vision Evals
Claude Haiku 5.5 scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Claude Haiku 5.5 leads 65.8% to 23.8%.
Overall, Claude Haiku 5.5 averages 77.2% (#20 of 61) against 68.7% (#34 of 61) for Grok 4.6.
Claude Haiku 5.5 is both cheaper ($0.0005 vs $0.0097 per sample) and faster (13.2s vs 17.5s per sample).
Claude Haiku 5.5 vs Grok 4.6 Comparison Table
Evals updated October 8, 2026Pricing updated October 8, 2026
| Property | Claude Haiku 5.5 | Grok 4.6 |
|---|---|---|
| Organization | Anthropic | SpaceXAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Oct 2026 | Aug 2026 |
| Context Window | 1.0M | 500K |
| Parameters | undisclosed | Unknown |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | $2.00 |
| Output $/1M | $0.500 | $6.00 |
| Vision Tasks | ||
| Captioning | Supported | Demo |
| Chart Question Answering | Supported | Supported |
| Classification | Supported | Demo |
| Document Question Answering | Supported | Supported |
| Image Tagging | Supported | Supported |
| Multi-Label Classification | Supported | Supported |
| Object Detection | Supported | Demo |
| OCR | Supported | Demo |
| Vision Language | Supported | Supported |
| Visual Question Answering | Supported | Demo |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Supported |
| Multimodal Vision | Supported | Supported |
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 77.2% | 68.7% |
| Avg cost / sample | $0.0005 | $0.0097 |
| Avg speed / sample | 13.23s | 17.55s |
| By task | ||
| Object Detection (low) | 65.8% ±0.6, Mean of 3 runs, range 65.1 to 66.2 | 23.8% ±2.8, Mean of 3 runs, range 20.2 to 25.9 |
| Object Detection (high) | 68.2% ±1.0, Mean of 3 runs, range 67.2 to 69.2 | 24.0% ±1.0, Mean of 3 runs, range 23.1 to 25.1 |
| Counting (low) | 68.9% ±4.7, Mean of 3 runs, range 64.9 to 74.3 | 65.8% ±4.1, Mean of 3 runs, range 62.2 to 70.3 |
| Counting (high) | 73.0% ±1.3, Mean of 3 runs, range 71.6 to 74.3 | 56.8% ±1.4, Mean of 3 runs, range 55.4 to 58.1 |
| Identification (low) | 83.3% ±3.1, Mean of 3 runs, range 81.3 to 87.5 | 84.4% ±3.1, Mean of 3 runs, range 81.3 to 87.5 |
| Identification (high) | 86.5% ±1.6, Mean of 3 runs, range 84.4 to 87.5 | 85.4% ±1.6, Mean of 3 runs, range 84.4 to 87.5 |
| OCR (low) | 90.1% ±1.1, Mean of 3 runs, range 88.8 to 91.0 | 91.8% ±0.3, Mean of 3 runs, range 91.5 to 92.1 |
| OCR (high) | 88.0% ±1.3, Mean of 3 runs, range 87.0 to 89.6 | 91.6% ±0.2, Mean of 3 runs, range 91.4 to 91.7 |
| Data Extraction (low) | 85.9% ±1.5, Mean of 3 runs, range 84.5 to 87.6 | 85.6% ±1.0, Mean of 3 runs, range 84.5 to 86.6 |
| Data Extraction (high) | 87.3% ±0.5, Mean of 3 runs, range 86.6 to 87.6 | 85.6% ±1.0, Mean of 3 runs, range 84.5 to 86.6 |
| Reasoning (low) | 68.9% ±2.0, Mean of 3 runs, range 66.9 to 70.9 | 61.1% ±1.3, Mean of 3 runs, range 59.6 to 62.3 |
| Reasoning (high) | 74.8% ±2.6, Mean of 3 runs, range 72.2 to 77.5 | 63.8% ±2.0, Mean of 3 runs, range 62.3 to 66.2 |
Claude Haiku 5.5 vs Grok 4.6: Overview
Claude Haiku 5.5 is a proprietary multimodal language model from Anthropic and the smallest member of the Claude 5.5 family, released on October 7, 2026 after Claude Opus 5.5 and Claude Sonnet 5.5. It accepts text and image input and returns text, with a 1M token context window and up to 128K output tokens per request. It is the first Haiku-class model with an adjustable effort parameter: adaptive thinking is on by default and the model decides how much to reason, steered by effort levels from low to max with medium as the default. Its training data cutoff is June 2026. Pricing starts at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100K tokens, which Anthropic reports is about 90% lower than Claude Haiku 4.5 for requests in that range.
Anthropic positions Haiku 5.5 for high-volume, latency-sensitive work such as classification, extraction, routing, summarization, and subagent tasks, and describes it as its fastest model to date at standard speed. On visual and agentic evaluations reported at launch, it scores 46.4% on Chartography, a chart reading benchmark, compared with 6.4% for Haiku 4.5 and 61.6% for Sonnet 5.5, and 72.4% on the offline subset of OSWorld 2.1, a screenshot driven computer use benchmark, compared with 15.7% for Haiku 4.5. It uses the same tokenizer as Claude Opus 4.7 and later models, so the same text counts as roughly 30% more tokens than on Haiku 4.5.
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.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Haiku 5.5 performed better. It scores higher on 4 of the six vision tasks and averages 77.2% (#20 of 61) against 68.7% (#34 of 61) for Grok 4.6. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Object Detection benchmark at low effort, Claude Haiku 5.5 leads with 65.8% against 23.8%. This is the widest gap between the two models across the benchmark's tasks.
Claude Haiku 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0005 per sample against $0.0097. Claude Haiku 5.5 is priced at $0.10 per 1M input tokens and $0.50 per 1M output; Grok 4.6 is priced at $2.00 per 1M input tokens and $6.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Haiku 5.5 is faster. Across Roboflow's Vision Evals it averaged 13.2s per inference against 17.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.