Can NVIDIA RTX 6000 Ada run Codestral 22B?

22B parameter Code model on 48GB GDDR6 ECC

Yes — runs at full precision
~12-15 tok/sSlow
SpeedFastest possible inference
QualityMaximum quality, no degradation

VRAM Requirements

Codestral 22B is a 22B parameter model. At full precision (FP16), it requires 44GB of VRAM. Your NVIDIA RTX 6000 Ada has 48GB — enough to run it without any quantization.

FP16 (Full Precision)44GB (4GB free)

Maximum quality, no quantization

Q8 (8-bit)22GB (26GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)13GB (35GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 48GB GDDR6 ECC at 960 GB/s bandwidth
Recommended system RAM: 96GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

Codestral 22B at this precision on NVIDIA RTX 6000 Ada gives excellent code completion and generation. Fast enough for real-time IDE integration. Handles complex refactoring, multi-file edits, and long-context code understanding.

How to Set It Up

Step 1: Install Ollama

curl -fsSL https://ollama.com/install.sh | sh

Ollama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.

Step 2: Download and run Codestral 22B

ollama run codestral:22b

This downloads the model (~44GB). First run takes a few minutes.

Step 3: Verify GPU is being used

nvidia-smi

Check that VRAM usage increases when the model loads. You should see ~44GB used.

NVIDIA RTX 6000 Ada Specs

VRAM48GB GDDR6 ECC
Memory Bandwidth960 GB/s
TDP300W
CUDA Cores18,176
Street Price~$6500
AI Rating10/10

Other Code Models on NVIDIA RTX 6000 Ada

About Codestral 22B

Top code completion model. Q4 fits on 16GB GPUs.

Category: Code · Parameters: 22B · CUDA required: No (runs via llama.cpp/GGUF)