Gemma 3 4B vs Grok 4
Compare Gemma 3 4B and Grok 4 side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Gemma 3 4B vs Grok 4: 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.
Grok 4, released by xAI on July 9, 2025, is the fourth-generation model in the Grok family and the most advanced to date. It is multimodal, supporting text, vision, tool use, and real-time web search, with a reported 256,000-token context window for long-form reasoning and document analysis. Its training data extends through November 2024, making it the most up-to-date Grok model at launch.
The lineup includes Grok 4 Generalist for broad tasks, Grok 4 Heavy for higher-capacity reasoning, and Grok 4 Code optimized for programming and debugging. A notable feature is its always-on “Think” mode, designed for deeper multi-step reasoning. While xAI has not disclosed parameter counts, Grok 4 is positioned to compete with frontier models like GPT-5 and Claude 4, balancing real-time knowledge via web integration with structured tool use. It is best suited for coding, complex reasoning, and multimodal AI assistants.
Gemma 3 4B vs Grok 4 Comparison Table
| Property | Gemma 3 4B | Grok 4 |
|---|---|---|
| Organization | xAI | |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Mar 2025 | Jul 2025 |
| Context Window | 128K | 256K |
| Parameters | 4B | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.050 | |
| Output $/1M | $0.100 | |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | 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% | 52.24% |
| Avg Response Time | 16.80s | 85.24s |
| Defect Detection | 60%(9/15) | 80%(12/15) |
| Document Understanding | 55.6%(5/9) | 44.4%(4/9) |
| Object Counting | 0%(0/10) | 10%(1/10) |
| Object Understanding | 42.9%(6/14) | 57.1%(8/14) |
| Spatial Understanding | 26.3%(5/19) | 52.6%(10/19) |
| 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) | |