Gemini 3.5 Flash vs Gemini 4 Hydrogen
Gemini 4 Hydrogen and Gemini 3.5 Flash score 87.3% vs 81.8% averaged across five Vision Evals tasks (#3 and #8 of 69 models), so Gemini 4 Hydrogen leads overall.
- Gemini 4 Hydrogen wins 4 of the 5 tasks, with its widest lead on object detection (81.0% vs 70.6%).
- Gemini 4 Hydrogen is cheaper: $0.0094 vs $0.012 overall average cost per sample.
- Gemini 3.5 Flash is faster: 11.5s vs 13.2s per sample.
Roboflow Vision Evals. Full breakdown below.
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Gemini 3.5 Flash vs Gemini 4 Hydrogen on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Gemini 3.5 Flash vs Gemini 4 Hydrogen Comparison Table
Evals updated November 12, 2026Pricing updated November 13, 2026
| Property | Gemini 3.5 Flash | Gemini 4 Hydrogen |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | May 2026 | Nov 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $1.50 | No published price |
| Output $/1M | $9.00 | No published price |
| Vision Tasks | ||
| Chart Question Answering | Supported | Not listed |
| Document Question Answering | Supported | Not listed |
| Image Tagging | Supported | Not listed |
| Multi-Label Classification | Supported | Not listed |
| Promptable Concept Segmentation | Not listed | Demo |
Both support 6 more tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 81.8% | 87.3% |
| Avg cost / sample | $0.012 | $0.0094 |
| Avg speed / sample | 11.52s | 13.23s |
| By task | ||
| Object Detection (low) | 70.6% ±2.0, Mean of 3 runs, range 68.7 to 72.6 | 81.0% ±0.8, Mean of 3 runs, range 80.3 to 81.9 |
| Object Detection (high) | 69.8% ±1.8, Mean of 3 runs, range 67.5 to 71.1 | 83.3% ±0.7, Mean of 3 runs, range 82.4 to 83.8 |
| Counting (low) | 80.6% ±0.7, Mean of 3 runs, range 79.7 to 81.1 | 83.8% ±2.0, Mean of 3 runs, range 82.4 to 86.5 |
| Counting (high) | 82.4% ±0.0, Mean of 3 runs, range 82.4 to 82.4 | 84.2% ±2.7, Mean of 3 runs, range 82.4 to 87.8 |
| Identification (low) | 99.0% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| Identification (high) | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | 76.7% | 86.7% |
| by category |
|
|
| OCR (high) | 75.5% | 87.2% |
| by category |
|
|
| Reasoning (low) | 82.1% ±2.0, Mean of 3 runs, range 80.1 to 84.1 | 88.1% ±0.7, Mean of 3 runs, range 87.4 to 88.7 |
| Reasoning (high) | 81.0% ±1.7, Mean of 3 runs, range 79.5 to 82.8 | 91.8% ±0.3, Mean of 3 runs, range 91.4 to 92.0 |
Gemini 3.5 Flash vs Gemini 4 Hydrogen: Overview
Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.
Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.
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.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 4 Hydrogen performed better. It scores higher on 4 of the five vision tasks and averages 87.3% (#3 of 69) against 81.8% (#8 of 69) for Gemini 3.5 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark at low effort, Gemini 4 Hydrogen leads with 81.0% against 70.6%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 4 Hydrogen is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0094 per sample against $0.012. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3.5 Flash is faster. Across Roboflow's Vision Evals it averaged 11.5s 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 open prompts and image captioning in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.