Gemini 4 Hydrogen vs GPT-6.1 Sol
Gemini 4 Hydrogen and GPT-6.1 Sol score 87.3% vs 81.7% averaged across five Vision Evals tasks (#3 and #9 of 69 models), so Gemini 4 Hydrogen leads overall.
- Gemini 4 Hydrogen wins all 5 tasks, with its widest lead on OCR (86.7% vs 75.8%).
- GPT-6.1 Sol is cheaper: $0.0068 vs $0.0094 overall average cost per sample.
Roboflow Vision Evals. Full breakdown below.
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Gemini 4 Hydrogen vs GPT-6.1 Sol on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Gemini 4 Hydrogen vs GPT-6.1 Sol Comparison Table
Evals updated November 12, 2026Pricing updated November 13, 2026
| Property | Gemini 4 Hydrogen | GPT-6.1 Sol |
|---|---|---|
| Organization | OpenAI | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Nov 2026 | Sep 2026 |
| Context Window | 1.0M | 1.1M |
| Parameters | Unknown | undisclosed |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | No published price | $2.00 |
| Output $/1M | No published price | $10.00 |
| Vision Tasks | ||
| Chart Question Answering | Not listed | Supported |
| Document Question Answering | Not listed | Supported |
| Image Tagging | Not listed | Supported |
| Multi-Label Classification | Not listed | Supported |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 87.3% | 81.7% |
| Avg cost / sample | $0.0094 | $0.0068 |
| Avg speed / sample | 13.23s | 12.82s |
| By task | ||
| Object Detection (low) | 81.0% ±0.8, Mean of 3 runs, range 80.3 to 81.9 | 80.8% ±0.1, Mean of 3 runs, range 80.7 to 80.9 |
| Object Detection (high) | 83.3% ±0.7, Mean of 3 runs, range 82.4 to 83.8 | 81.6% ±0.4, Mean of 3 runs, range 81.1 to 82.0 |
| Counting (low) | 83.8% ±2.0, Mean of 3 runs, range 82.4 to 86.5 | 78.8% ±3.4, Mean of 3 runs, range 75.7 to 82.4 |
| Counting (high) | 84.2% ±2.7, Mean of 3 runs, range 82.4 to 87.8 | 80.2% ±3.4, Mean of 3 runs, range 77.0 to 83.8 |
| Identification (low) | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 | 89.6% ±1.6, Mean of 3 runs, range 87.5 to 90.6 |
| Identification (high) | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 | 88.5% ±1.6, Mean of 3 runs, range 87.5 to 90.6 |
| OCR (low) | 86.7% | 75.8% |
| by category |
|
|
| OCR (high) | 87.2% | 75.8% |
| by category |
|
|
| Reasoning (low) | 88.1% ±0.7, Mean of 3 runs, range 87.4 to 88.7 | 83.7% ±1.3, Mean of 3 runs, range 82.1 to 84.8 |
| Reasoning (high) | 91.8% ±0.3, Mean of 3 runs, range 91.4 to 92.0 | 88.7% ±2.0, Mean of 3 runs, range 87.4 to 91.4 |
Gemini 4 Hydrogen vs GPT-6.1 Sol: Overview
Gemini 4 Hydrogen is a multimodal model from Google, positioned as a successor to Gemini 3.8 Flash with stronger agent and coding capabilities at Flash-class speed.
GPT-6.1 Sol is a reasoning model in OpenAI's GPT-6 series that accepts text and image input and returns text. It is an upgrade to GPT-6 Sol positioned to approach the intelligence of the larger GPT-6 Astra model on agentic coding, computer use, and professional knowledge work. The model exposes an adjustable reasoning effort control, ranging from low settings for simple turns to maximum settings for harder tasks, and can be driven with tool use enabled or disabled. It operates over a context window of roughly one million tokens and emits up to 128,000 output tokens in a single response, which supports long-running agent loops over large codebases and multi-document collections. Audio and video inputs are not supported.
OpenAI reports that GPT-6.1 Sol performs on par with or better than GPT-6 Sol across its image input safety evaluations, and that the share of responses containing a factual error at low reasoning effort falls from 11.4 percent to 7.7 percent.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 4 Hydrogen performed better. It scores higher on all five vision tasks and averages 87.3% (#3 of 69) against 81.7% (#9 of 69) for GPT-6.1 Sol. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals OCR benchmark at low effort, Gemini 4 Hydrogen leads with 86.7% against 75.8%. This is the widest gap between the two models across the benchmark's tasks.
GPT-6.1 Sol is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0068 per sample against $0.0094. Actual costs depend on your image sizes, prompts, and output length.
GPT-6.1 Sol is faster. Across Roboflow's Vision Evals it averaged 12.8s per inference against 13.2s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.