Gemini 2.5 Pro vs Gemma 3 4B
Compare Gemini 2.5 Pro and Gemma 3 4B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.
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Gemini 2.5 Pro vs Gemma 3 4B Comparison Table
Evals updated July 10, 2026Pricing updated July 16, 2026
| Property | Gemini 2.5 Pro | Gemma 3 4B |
|---|---|---|
| Organization | ||
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jun 2025 | Mar 2025 |
| Context Window | 1.0M | 128K |
| Parameters | 4B | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | $0.050 |
| Output $/1M | $10.00 | $0.100 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Classification | Demo | |
| Object Detection | Demo | |
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalsground-truth scores across 6 vision tasks | ||
| Overall | 67.9% | Not evaluated |
| Object Detection | 26.4% | – |
| Counting | 52.7% | – |
| Identification | 93.8% | – |
| OCR | 88.8% | – |
| Data Extraction | 84.5% | – |
| Reasoning | 60.9% | – |
| Avg cost / sample | $0.0036 | – |
| Avg speed / sample | 4.7s | – |
Gemini 2.5 Pro vs Gemma 3 4B: Overview
Gemini 2.5 Pro, released on June 17, 2025, is Google DeepMind’s most capable model in the Gemini 2.5 family, optimized for deep reasoning, coding, and complex multimodal tasks. It accepts text, images, audio, video, and PDFs as input and outputs text. The model supports 1 million input tokens with an output capacity of up to 65K tokens, enabling large-scale comprehension of datasets, codebases, and technical documents. Its training knowledge extends to January 2025.
Pro outperforms earlier Gemini 2.0 models across benchmarks, including agentic coding tasks where it achieved ~63.8% on SWE-Bench Verified. It supports structured outputs, function calling, code execution, search grounding, and URL context, making it well-suited for enterprise, STEM, and developer workflows. However, it does not currently support image or audio generation in its stable release, and its higher computational cost and latency make it less efficient than Flash or Flash-Lite. It is available via the Gemini API, Google AI Studio, and Vertex AI.
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.