Gemma 4 12B vs GPT-5.5
Compare Gemma 4 12B and GPT-5.5 side-by-side.
Compare Gemma 4 12B vs GPT-5.5 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
Gemma 4 12B vs GPT-5.5 Comparison Table
Evals updated September 5, 2026Pricing updated September 20, 2026
| Property | Gemma 4 12B | GPT-5.5 |
|---|---|---|
| Organization | OpenAI | |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 2026 | Apr 2026 |
| Context Window | — | 1.0M |
| Parameters | 12B | |
| License | Apache 2.0 | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | |
| Output $/1M | $30.00 | |
| Vision Tasks | ||
| Captioning | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 74.8% |
| Avg cost / sample | – | $0.022 |
| Avg speed / sample | – | 9.03s |
| By task | ||
| Object Detection (low) | – | 43.6% ±2.2, Mean of 3 runs, range 41.7 to 46.1 |
| Object Detection (high) | – | 44.2% ±0.6, Mean of 3 runs, range 43.5 to 44.8 |
| Counting (low) | – | 68.0% ±3.4, Mean of 3 runs, range 64.9 to 71.6 |
| Counting (high) | – | 68.0% ±1.4, Mean of 3 runs, range 66.2 to 68.9 |
| Identification (low) | – | 89.6% ±1.6, Mean of 3 runs, range 87.5 to 90.6 |
| Identification (high) | – | 88.5% ±1.6, Mean of 3 runs, range 87.5 to 90.6 |
| OCR (low) | – | 91.2% ±0.3, Mean of 3 runs, range 90.9 to 91.6 |
| OCR (high) | – | 91.7% ±0.6, Mean of 3 runs, range 91.1 to 92.3 |
| Data Extraction (low) | – | 85.9% ±1.5, Mean of 3 runs, range 84.5 to 87.6 |
| Data Extraction (high) | – | 86.9% ±0.5, Mean of 3 runs, range 86.6 to 87.6 |
| Reasoning (low) | – | 70.6% ±1.0, Mean of 3 runs, range 69.5 to 71.5 |
| Reasoning (high) | – | 72.2% ±3.6, Mean of 3 runs, range 68.9 to 76.2 |
Gemma 4 12B vs GPT-5.5: Overview
Gemma 4 12B is an open-weight multimodal model from Google in the Gemma 4 family. It is intended for text and image understanding tasks such as visual question answering, OCR, captioning, and document understanding, with a smaller parameter footprint than the larger Gemma 4 variants.
This entry is connected to Roboflow Playground vision evals for comparison. No runnable Playground workflow is configured yet, so the model page is used for discovery and benchmark context rather than direct hosted inference.
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.
Frequently Asked Questions
Gemma 4 12B has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.
Gemma 4 12B is released under Apache 2.0, while GPT-5.5 uses Proprietary. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.