Gemma 3 4B vs GPT-6 Sol
GPT-6 Sol: 76.9% average across five Vision Evals tasks (#13 of 65 models). We have not run Gemma 3 4B through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
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Gemma 3 4B vs GPT-6 Sol Comparison Table
Evals updated October 26, 2026Pricing updated November 6, 2026
| Property | Gemma 3 4B | GPT-6 Sol |
|---|---|---|
| Organization | OpenAI | |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Mar 2025 | Sep 2026 |
| Context Window | 128K | 1.1M |
| Parameters | 4B | undisclosed |
| License | Custom | Proprietary |
| Commercial use | See license terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.050 | $2.00 |
| Output $/1M | $0.100 | $10.00 |
| Vision Tasks | ||
| Classification | Supported | Demo |
| Object Detection | Not listed | Demo |
| Promptable Concept Segmentation | Not listed | Demo |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 76.9% |
| Avg cost / sample | – | $0.0074 |
| Avg speed / sample | – | 10.20s |
| By task | ||
| Object Detection (low) | – | 74.7% ±0.7, Mean of 3 runs, range 74.1 to 75.5 |
| Object Detection (high) | – | 76.4% ±1.2, Mean of 3 runs, range 75.0 to 77.4 |
| Counting (low) | – | 76.6% ±2.0, Mean of 3 runs, range 74.3 to 78.4 |
| Counting (high) | – | 77.5% ±1.3, Mean of 3 runs, range 75.7 to 78.4 |
| Identification (low) | – | 93.8% ±0.0, Mean of 3 runs, range 93.8 to 93.8 |
| Identification (high) | – | 92.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 |
| OCR (low) | – | 66.7% |
| by category |
| |
| OCR (high) | – | 68.8% |
| by category |
| |
| Reasoning (low) | – | 72.6% ±3.6, Mean of 3 runs, range 69.5 to 76.8 |
| Reasoning (high) | – | 77.7% ±1.0, Mean of 3 runs, range 76.8 to 78.8 |
Gemma 3 4B vs GPT-6 Sol: Overview
Gemma 3 4B, released on March 12, 2025, is the mid-sized member of Google DeepMind’s open-weight Gemma 3 family. With about 4 billion parameters, it is multimodal—supporting text and image inputs and generating text outputs. Like the larger Gemma 3 models, it features a 128,000-token input context window with an output capacity of ~8,192 tokens, enabling it to handle long documents and mixed text–image reasoning tasks.
The 4B variant is designed as a balance between efficiency and capability: it offers multilingual support across 140+ languages, strong summarization and reasoning performance, and compatibility with moderate hardware. Inference can run with ~6.4 GB VRAM in BF16, or significantly less in quantized 8-bit (~4.4 GB) or 4-bit (~3.4 GB) modes, making it accessible to developers outside large-scale infrastructure. While it lags behind the 12B and 27B versions on the most complex reasoning and multimodal benchmarks, its lower compute footprint makes it ideal for research, prototyping, and practical deployment where efficiency matters.
GPT-6 Sol is a proprietary multimodal reasoning model from OpenAI, released on September 22, 2026 alongside GPT-6 Luna as an efficiency-oriented tier of the GPT-6 family that began with GPT-6 Astra. OpenAI states that Sol and Luna are trained with methods similar to those used for Astra, carrying the same work on professional tasks, factuality, coding, computer use, and alignment into models that run faster. Sol accepts text and image input and returns text output, and OpenAI documents a context window of roughly one million tokens together with a knowledge cutoff of April 20, 2026.
The model targets complex coding and agentic workflows and exposes a configurable reasoning effort setting with levels of none, low, medium, high, xhigh, and max, which trades latency and token consumption against answer quality. Its vision behavior covers image understanding tasks such as visual question answering, captioning, document and chart interpretation, and text recognition.
Frequently Asked Questions
Gemma 3 4B is released under Custom, while GPT-6 Sol uses Proprietary. In practice: GPT-6 Sol: commercial use per vendor terms. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
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.