Gemma 3 4B
Balanced 4B model with strong reasoning. Great for iPhones.
About This Model
Gemma 3 4B is a large language model developed by Google, designed for advanced text generation tasks. With 4 billion parameters, it strikes a balance between performance and resource requirements, making it suitable for a wide range of applications such as content creation, chatbot development, and natural language understanding. The model's context length of 32,768 tokens allows it to handle longer sequences of text, which is particularly useful for generating coherent and contextually rich outputs. It is licensed under the gemma license, which is generally permissive for both research and commercial use.
In its size class, Gemma 3 4B punches above its weight, offering performance that rivals larger models while requiring significantly less computational resources. This makes it an efficient choice for users who need high-quality text generation without the need for top-tier hardware. The available quantizations, Q4_K_M and Q8_0, further enhance its efficiency, reducing the VRAM requirement to a range of 2.8–4.3 GB, which is manageable even on mid-range GPUs. Ideal users include developers, researchers, and hobbyists who are looking for a powerful yet accessible model for local deployment. Realistic hardware for running Gemma 3 4B includes modern GPUs with at least 4 GB of VRAM, making it a practical choice for a broad audience.
Check Your Hardware
See which quantizations of Gemma 3 4B your hardware can run.
Quantization Options
| Quantization | Bits | File Size | VRAM Needed | RAM Needed | Quality |
|---|---|---|---|---|---|
| Q4_K_M | 4.5 | 2.319 GB | 2.82 GB | 3.32 GB | 85% |
| Q8_0 | 8 | 3.847 GB | 4.35 GB | 4.85 GB | 98% |
See It In Action
Real model outputs generated via RunThisModel.com — watch responses stream in real time.
Outputs generated by real AI models via RunThisModel.com. Generation speed shown is from cloud inference. Local speeds vary by hardware — check your device.
Frequently Asked Questions
How much VRAM do I need to run Gemma 3 4B?
Gemma 3 4B requires 2.82GB VRAM minimum with Q4_K_M quantization. For full precision, you need 4.35GB VRAM.
What is the best quantization for Gemma 3 4B?
Q4_K_M offers the best balance of quality and VRAM usage. Q8_0 is near-lossless if you have enough VRAM.