Gemma 3 4B vs GPT-4o
Compare Gemma 3 4B and GPT-4o side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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GPT-4o is deprecated and can no longer be run. Details and evals are still available on its model page.
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Gemma 3 4B vs GPT-4o: 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-4o (“omni”), released by OpenAI in May 2024, is a multimodal flagship model designed to unify text, image, and audio processing in a single system. Unlike earlier GPT-4 variants, GPT-4o supports real-time speech-to-speech interaction, enabling natural voice conversations alongside text and image reasoning. It features a context window of ~128,000 tokens for text input, with smaller output limits (commonly ~16K tokens), and has a knowledge cutoff of October 2023.
The model is optimized for efficiency and multilingual accessibility, supporting over 50 languages and covering ~97% of the world’s speakers. GPT-4o offers a cost-effective balance of speed and capability. It powers ChatGPT across free and paid tiers, making it widely accessible for applications in conversational AI, real-time translation, multimodal assistants, and global-scale communication tools.
Gemma 3 4B vs GPT-4o Comparison Table
| Property | Gemma 3 4B | GPT-4o |
|---|---|---|
| Organization | OpenAI | |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Mar 2025 | May 2024 |
| Context Window | 128K | 128K |
| Parameters | 4B | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.050 | $2.50 |
| Output $/1M | $0.100 | $10.00 |
| Vision Tasks | ||
| Captioning | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Classification | ||
| Object Detection | ||
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 37.31% | |
| Avg Response Time | 16.80s | |
| Defect Detection | 60%(9/15) | |
| Document Understanding | 55.6%(5/9) | |
| Object Counting | 0%(0/10) | |
| Object Understanding | 42.9%(6/14) | |
| Spatial Understanding | 26.3%(5/19) | |
| OCR | ||
| Overall Score | 64.19% | |
| Avg Response Time | 0.92s | |
| Median input tokensincl. image tokens | 300 | |
| Median output tokens | 12 | |
| Est. cost / taskon this benchmark | <$0.0001 | |
| Focused Scene OCR | 63.6%(63/99) | |
| Handwritten Math | 10%(1/10) | |
| License Plate Recognition | 86.7%(26/30) | |
| Text Recognition | 73.3%(22/30) | |
| VQA & Extraction | 58.3%(35/60) | |