Written by Jakub Rusinowski · Last updated October 21, 2024
Model library → Granite 3.0 → Granite 3.0 8B Instruct
A robust 8B model optimized for enterprise tasks, coding, and RAG. Completely open license.
Granite 3.0 8B Instruct needs about 6 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.
| Parameters | 8 Billion |
| Context window | 4,096 |
| Architecture | Dense |
| Provider | IBM |
| Licence | Apache 2.0 |
| Specified at | Q4_K_M |
| System RAM | 16 GB |
| Record updated | 2024-10-21 |
Apache-2.0 — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.
Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.
| Quant | Weights | VRAM needed | Est. speed | Fit on 24 GB |
|---|---|---|---|---|
| Q2_K | 2.6 GB | 4.8 GB | ~151 tok/s (est.) | Fits comfortably |
| Q3_K_M | 3.4 GB | 5.6 GB | ~131 tok/s (est.) | Fits comfortably |
| Q4_K_M | 4.8 GB | 7.0 GB | ~105 tok/s (est.) | Fits comfortably |
| Q5_K_M | 5.7 GB | 7.8 GB | ~94 tok/s (est.) | Fits comfortably |
| Q6_K | 6.6 GB | 8.7 GB | ~85 tok/s (est.) | Fits comfortably |
| Q8_0 | 8.5 GB | 10.6 GB | ~70 tok/s (est.) | Fits comfortably |
| F16 | 16.0 GB | 18.1 GB | ~41 tok/s (est.) | Fits comfortably |
Want the memory numbers alone, at every quantization level and your own context length? Use the Granite 3.0 8B Instruct VRAM calculator.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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The cheapest catalogued GPU that runs Granite 3.0 8B Instruct is the Intel Arc B570 (10 GB).
Install Ollama, then run:
ollama run granite3-dense
Weights on Hugging Face: ibm-granite/granite-3.0-8b-instruct.
Best for: coding, enterprise, rag.
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