01What it can do
- Dense 8B: fits on an 8 GB GPU in Q4 (~4.6 GB)
- Specialized in code
- Permissive Apache 2.0 license
- 128k native context
- —Lagging behind recent 2025–2026 coders
- —Gated weights on Hugging Face (acceptance required)
04Install
Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.
02Required memory
Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.
What hardware do you need for IBM Granite Code 8B?
To run IBM Granite Code 8B locally with Q4 quantization, you need about 4.6 GB of VRAM. An option to compare: RTX 5060 Ti 16GB (ASUS Prime) — leave some headroom for the system and context; check engine compatibility with the GPU.
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On the go: IBM Granite Code 8B also runs on a RTX laptop PC (16 GB of VRAM) →
03Expected speed
Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.