Family Granite · 8B parameters

IBM Granite Code 8B Instruct

IBM Granite Code 8B Instruct: code-specialized dense 8B, 128k context, ~4.6 GB Q4 VRAM. Instruct, Apache 2.0 license.

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

01What it can do

Strengths
  • Dense 8B: fits on an 8 GB GPU in Q4 (~4.6 GB)
  • Code-specialized, Instruct variant
  • Permissive Apache 2.0 license
  • 128k native context
Limitations to know
  • —Lagging behind recent 2025–2026 coders
  • —Gated weights on Hugging Face (acceptance required)
Architecture
Dense transformer · 8B parameters · 128k context · specialized for code
Training
IBM's Granite Code model in the Instruct variant, designed for code generation, completion, and explanation. Apache 2.0 license.
Ideal for
Code completionLocal development assistant8 GB GPU

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 pull granite-code: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
4.6 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 IBM Granite Code 8B Instruct?

To run IBM Granite Code 8B Instruct 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.

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: IBM Granite Code 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
~32t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~50t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~75t/s
RTX 4090, M4 Max, Radeon 7900