Family Granite · 8B parameters

Granite 3.3 8B Instruct

3.2 update with fill-in-the-middle code. Improved instruction following.

🇺🇸 IBM·License Apache 2.0·Context 125k tokens·Output January 2025·Fits within the 128 GB of the GIGABYTE AI TOP ATOM← Catalog

01What it can do

Strengths
  • 128k context
  • Apache 2.0
  • Strong at agents and tool use
  • Better than 3.2 at instruction following
Limitations to know
  • —Enterprise-first profile
  • —Less versatile than Qwen 3 8B
Architecture
Dense · 8B · IBM Granite 3.3 · improved agents and tool use
Training
Granite 3.2 evolution with improved agent/tool use and code.
Ideal for
EnterpriseFIM code

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.

$ollama run granite3.3:8b
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

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.

Q4_K_M
The lightest, ~5% loss
5 GB
Q5_K_M
Good quality/size compromise
6 GB
Q8_0
Nearly indistinguishable from FP16
9 GB
FP16
Full precision — server use
16 GB
Fallback CPU · If you don't have a GPU, allow 10 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Granite 3.3 8B Instruct?

To run Granite 3.3 8B Instruct locally with Q4 quantization, you need about 5 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.

Current offer: RTX 5060 Ti 16GB (ASUS Prime)
AmazonSee price →

Affiliate links — commission possible at no extra cost to you; independent recommendations. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

On the go: Granite 3.3 8B Instruct 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.

Entry-level
~10t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~30t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~80t/s
RTX 4090, M4 Max, Radeon 7900