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Grok 4.7 is on the Vision Evals leaderboard. Running it in the Playground is not available yet. View evals
Grok 4.7 is a proprietary model from SpaceXAI, released on September 21, 2026. It accepts text and images as input and returns text. It extends Grok 4.6 and is listed at the same API price.
Its Vision Evals scores are on the leaderboard. Running it in the Playground is not available yet, because the inference workflow is not ready.
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Vision Evals is Roboflow's ground-truth benchmark: every model runs the same real-world samples across six vision tasks, and answers are scored against ground truth.
Evals updated September 22, 2026Pricing updated September 22, 2026
Grok 4.7 averages 71.9% across the six Vision Evals tasks, ranking #22 of 54 models overall.
Its weakest relative showing is Object Detection, ranking #39 of 54 at 40.4%.
At $0.012 per sample it is the 48th cheapest of the 54 benchmarked models, and its average inference time of 23.6s per sample makes it the 43rd fastest.
Field medians: Object Detection 53.4%, Counting 59.0%, Identification 84.4%, OCR 88.7%, Data Extraction 84.5%, Reasoning 54.4%.
| Task | Score | Field (0 to 100) | Rank | Cost / sample | Speed |
|---|---|---|---|---|---|
| Object Detection (low) | 40.4% ±0.6, Mean of 3 runs, range 39.8 to 41.0 | #39 of 54 | $0.017 | 32.56s | |
| Object Detection (high) | 41.2% ±1.6, Mean of 3 runs, range 39.6 to 42.8 | #17 of 20 | $0.023 | 49.09s | |
| Counting (low) | 61.7% ±1.3, Mean of 3 runs, range 60.8 to 63.5 | #26 of 54 | $0.0086 | 16.76s | |
| Counting (high) | 60.8% ±1.3, Mean of 3 runs, range 59.5 to 62.2 | #18 of 20 | $0.013 | 32.45s | |
| Identification (low) | 87.5% ±3.1, Mean of 3 runs, range 84.4 to 90.6 | #20 of 54 | $0.0050 | 6.18s | |
| Identification (high) | 80.2% ±1.6, Mean of 3 runs, range 78.1 to 81.3 | #20 of 20 | $0.0074 | 13.61s | |
| OCR (low) | 92.6% ±0.7, Mean of 3 runs, range 92.1 to 93.4 | #9 of 54 | $0.014 | 30.02s | |
| OCR (high) | 93.5% ±0.3, Mean of 3 runs, range 93.1 to 93.8 | #2 of 20 | $0.034 | 80.11s | |
| Data Extraction (low) | 84.9% ±2.6, Mean of 3 runs, range 82.5 to 87.6 | #23 of 54 | $0.0048 | 4.90s | |
| Data Extraction (high) | 87.6% ±1.5, Mean of 3 runs, range 86.6 to 89.7 | #10 of 20 | $0.0054 | 6.13s | |
| Reasoning (low) | 64.2% ±2.3, Mean of 3 runs, range 62.3 to 66.9 | #17 of 54 | $0.012 | 26.03s | |
| Reasoning (high) | 66.9% ±1.3, Mean of 3 runs, range 65.6 to 68.2 | #20 of 40 | $0.019 | 51.09s |
Overall benchmark score against estimated cost per sample, on a log scale. Upper-left is the sweet spot: high quality at low cost.
53 models on the current benchmark · scores and efficiency pooled across all six tasks at low effort · Grok 4.7 highlighted
Grok 4.7 scores are the mean of 3 runs per task at both low and high effort · Methodology
View all Vision Evals →Grok 4.7 costs $1.60 per 1M input tokens and $4.80 per 1M output tokens.
Pricing updated Sep 22, 2026
Grok 4.7 is proprietary: the weights are not distributed, and the Grok 4.7 license is the vendor's commercial terms of service that you accept when you call the API.
Vendor terms govern data retention, whether your inputs can be trained on, rate limits, and regional availability, and they can change with notice. Review them if you handle regulated or customer data.
Proprietary terms are set by the vendor rather than negotiated per project, and no open-source obligation attaches to your code. If you would rather deploy a model whose commercial license is included in your plan — on Roboflow Managed Cloud or a Self-Hosted Inference Server — Roboflow's licensing page lists the supported alternatives to Grok 4.7.
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Yes. Grok 4.7 accepts image input and handles OCR, data extraction, object counting, identification, visual reasoning, and object detection. On Roboflow's Vision Evals its strongest task is OCR at 92.6% (#9 of 54 at low effort).
Yes, and it is one of the model's strongest vision skills: its transcriptions match the ground truth 92.6% on average (#9 of 54 at low effort) on Vision Evals OCR. Pulling specific fields out of documents (data extraction) scores 84.9%.
Not its strength. On Vision Evals, Grok 4.7 scores 40.4% mAP@50 on object detection (#39 of 54 at low effort) and 61.7% judge-graded accuracy on object counting. For production counting or precise localization, pairing it with a specialized detector like RF-DETR or your own trained model in a Roboflow Workflow is usually more reliable: detect the objects, then count the detections.
On our benchmark's task mix, Grok 4.7 averages $0.01 per sample at $1.60 per 1M input and $4.80 per 1M output tokens (#48 of 54 on cost), with an average speed of 23.6s per sample across the benchmark. Actual cost depends on your images and prompts.
On the overall Vision Evals ranking, Grok 4.7 sits #22 of 54 at 71.9%, just behind Qwen3.6 35B-A3B (71.9%) and just ahead of Qwen3.5 27B (70.8%). See the full side-by-side: Grok 4.7 vs Qwen3.6 35B-A3B.