Gemma 2 Family — local AI model by Google
Written by Jakub Rusinowski · Last updated
Built from the same research and technology as Google Gemini. Gemma 2 uses knowledge distillation for extremely high efficiency and creative performance.
Variants
The smallest Gemma 2 Family variant needs about 6 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache.
| Model | VRAM at Q4 | VRAM | Context | Run it |
|---|---|---|---|---|
| Gemma 2 9B IT → 9B | ~6.2 GB | 8,192 | ollama run gemma2 |
Memory is quantized weights plus overhead at Q4_K_M, from the same engine as the GPU & VRAM checker.
How to run Gemma 2 Family locally
Install Ollama, then pull the tag.
ollama run gemma2Pick a size above for its own VRAM figure, speed estimate and install command.
Download Gemma 2 Family — GGUF Quantizations
Pick a quantization and open it in LM Studio, Ollama, or Jan, or download the raw .gguf file directly. Quant list and sizes resolved from Hugging Face.
Gemma 2 9B IT — GGUF quants · bartowski/gemma-2-9b-it-GGUF
| Quant | Size | Download (.gguf) |
|---|---|---|
| Q3_K_M | 3.84 GB (est.) | gemma-2-9b-it-Q3_K_M.gguf |
| Q4_K_M | 5.43 GB (est.) | gemma-2-9b-it-Q4_K_M.gguf |
| Q5_K_M | 6.38 GB (est.) | gemma-2-9b-it-Q5_K_M.gguf |
| Q6_K | 7.38 GB (est.) | gemma-2-9b-it-Q6_K.gguf |
| Q8_0 | 9.56 GB (est.) | gemma-2-9b-it-Q8_0.gguf |
Download in LM Studio: lms get bartowski/gemma-2-9b-it-GGUF
Want this model on your phone? You can run it on your desktop with LM Studio and chat from your iPhone or iPad over an encrypted link — see Run LM Studio Models on Your Phone (LM Link).
Licence
Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.
Applies to: Gemma 2 9B ITRecommended GPU
The cheapest catalogued GPU that runs Gemma 2 Family locally (min 6 GB VRAM) is the Intel Arc B570 (10 GB).
Can I run Gemma 2 Family on my GPU?
- Gemma 2 Family on AMD Radeon RX 9060 XT 8GB
- Gemma 2 Family on Intel Arc B570
- Gemma 2 Family on Intel Arc B580
- Gemma 2 Family on NVIDIA GeForce RTX 3060 (12GB)
- Gemma 2 Family on NVIDIA GeForce RTX 3070
- Gemma 2 Family on NVIDIA GeForce RTX 3070 Ti
- Gemma 2 Family on NVIDIA GeForce RTX 3080 (10GB)
- Gemma 2 Family on NVIDIA GeForce RTX 4060
- Gemma 2 Family on NVIDIA GeForce RTX 4070
- Gemma 2 Family on NVIDIA GeForce RTX 4070 Super
- Gemma 2 Family on NVIDIA GeForce RTX 4070 Ti
- Gemma 2 Family on NVIDIA GeForce RTX 5060
- Gemma 2 Family on NVIDIA GeForce RTX 5060 Ti 8GB
- Gemma 2 Family on NVIDIA GeForce RTX 5070
Gemma 2 Family — frequently asked questions
How much VRAM does Gemma 2 Family need?
Gemma 2 Family needs about 6 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Gemma 2 9B IT (6 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run Gemma 2 Family on an RTX 4090 (24 GB)?
Yes — Gemma 2 Family runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
What quantization should I use for Gemma 2 Family?
Q4_K_M is the best balance of quality and VRAM for Gemma 2 Family in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run Gemma 2 Family with Ollama?
Install Ollama, then run: ollama run gemma2. This downloads Gemma 2 Family and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.