Granite 3.0 — local AI model by IBM
Written by Jakub Rusinowski · Last updated
IBM's enterprise-grade model family. Granite 3.0 is Apache 2.0 licensed and rigorously trained for coding, transparency, and safety in business environments.
Variants
The smallest Granite 3.0 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 |
|---|---|---|---|---|
| Granite 3.0 8B Instruct → 8B | ~5.6 GB | 4,096 | ollama run granite3-dense |
Memory is quantized weights plus overhead at Q4_K_M, from the same engine as the GPU & VRAM checker.
How to run Granite 3.0 locally
Install Ollama, then pull the tag.
ollama run granite3-densePick a size above for its own VRAM figure, speed estimate and install command.
Licence
Commercial use permitted. No usage restrictions beyond attribution.
Applies to: Granite 3.0 8B InstructRecommended GPU
The cheapest catalogued GPU that runs Granite 3.0 locally (min 6 GB VRAM) is the Intel Arc B570 (10 GB).
Can I run Granite 3.0 on my GPU?
- Granite 3.0 on AMD Radeon RX 9060 XT 8GB
- Granite 3.0 on Intel Arc B570
- Granite 3.0 on Intel Arc B580
- Granite 3.0 on NVIDIA GeForce RTX 3060 (12GB)
- Granite 3.0 on NVIDIA GeForce RTX 3070
- Granite 3.0 on NVIDIA GeForce RTX 3070 Ti
- Granite 3.0 on NVIDIA GeForce RTX 3080 (10GB)
- Granite 3.0 on NVIDIA GeForce RTX 4060
- Granite 3.0 on NVIDIA GeForce RTX 4070
- Granite 3.0 on NVIDIA GeForce RTX 4070 Super
- Granite 3.0 on NVIDIA GeForce RTX 4070 Ti
- Granite 3.0 on NVIDIA GeForce RTX 5060
- Granite 3.0 on NVIDIA GeForce RTX 5060 Ti 8GB
- Granite 3.0 on NVIDIA GeForce RTX 5070
Granite 3.0 — frequently asked questions
How much VRAM does Granite 3.0 need?
Granite 3.0 needs about 6 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Granite 3.0 8B Instruct (6 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run Granite 3.0 on an RTX 4090 (24 GB)?
Yes — Granite 3.0 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 Granite 3.0?
Q4_K_M is the best balance of quality and VRAM for Granite 3.0 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 Granite 3.0 with Ollama?
Install Ollama, then run: ollama run granite3-dense. This downloads Granite 3.0 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.