Gemini 4 Argon vs Gemma 4 12B
Compare Gemini 4 Argon and Gemma 4 12B side-by-side.
Compare Gemini 4 Argon vs Gemma 4 12B 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
Gemini 4 Argon vs Gemma 4 12B Comparison Table
Evals updated October 13, 2026Pricing updated October 13, 2026
| Property | Gemini 4 Argon | Gemma 4 12B |
|---|---|---|
| Organization | ||
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Oct 2026 | Jun 2026 |
| Context Window | 1.0M | — |
| Parameters | Undisclosed | 12B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Vision Tasks | ||
| Captioning | Demo | Supported |
| OCR | Demo | Supported |
| Vision Language | Supported | Supported |
| Visual Question Answering | Demo | Supported |
| Chart Question Answering | Supported | Not listed |
| Classification | Demo | Not listed |
| Document Question Answering | Supported | Not listed |
| Image Tagging | Supported | Not listed |
| Multi-Label Classification | Supported | Not listed |
| Object Detection | Demo | Not listed |
| Model Features | ||
| Multimodal Vision | Supported | Supported |
| Foundation Vision | Supported | Not listed |
| LLMs with Vision Capabilities | Supported | Not listed |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 87.5% | Not evaluated |
| Avg cost / sample | $0.0058 | – |
| Avg speed / sample | 13.40s | – |
| By task | ||
| Object Detection (low) | 82.5% ±0.5, Mean of 3 runs, range 81.9 to 83.0 | – |
| Object Detection (high) | 85.1% ±0.6, Mean of 3 runs, range 84.3 to 85.5 | – |
| Counting (low) | 86.0% ±0.7, Mean of 3 runs, range 85.1 to 86.5 | – |
| Counting (high) | 90.5% ±1.4, Mean of 3 runs, range 89.2 to 91.9 | – |
| Identification (low) | 93.8% ±0.0, Mean of 3 runs, range 93.8 to 93.8 | – |
| Identification (high) | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 | – |
| OCR (low) | 85.7% | – |
| by category |
| |
| OCR (high) | 88.0% | – |
| by category |
| |
| Reasoning (low) | 89.4% ±1.3, Mean of 3 runs, range 88.1 to 90.7 | – |
| Reasoning (high) | 91.4% ±0.7, Mean of 3 runs, range 90.7 to 92.0 | – |
Gemini 4 Argon vs Gemma 4 12B: Overview
Gemini 4 Argon is Google DeepMind's frontier Gemini 4 model, built to sustain extended reasoning across long-horizon workflows in software engineering, enterprise knowledge work such as legal and finance, scientific analysis, and defensive cybersecurity. It accepts text, image, video, and document input and returns text, operating over a one million token context window. The model raises the maximum output length to one million tokens, compared with a 64K ceiling on earlier Gemini releases, so a single reasoning trajectory can run for hundreds of thousands of tokens before terminating.
On the visual side, Argon targets multimodal document comprehension, professional chart analysis, and retrieval of specific details from long recordings, reporting 91.7% on LVBench for long-video understanding and 71.6% on Chartography for chart reasoning. Google also reports 77.9% on DeepSWE v1.1, 51.3% on AutomationBench, 68% on CWE-bench v1, and first place on the Vals Index, which aggregates finance, coding, legal, and tax tasks. Following Gemini API conventions, it localizes objects by emitting bounding boxes as [ymin, xmin, ymax, xmax] integers normalized to a 0 to 1000 range, which supports prompt driven detection and grounding alongside captioning, document parsing, and visual question answering. Google describes adversarial training and automated red teaming for indirect prompt injection resistance, plus chain-of-thought and action monitors that halt execution when behavior drifts outside user intent.
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.
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.
Gemini 4 Argon is released under Proprietary, while Gemma 4 12B uses Apache 2.0. In practice: Gemini 4 Argon — commercial use per vendor terms; Gemma 4 12B — free for commercial use. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.