GPUs/NVIDIA H100 80GB/Codestral 22B

Can NVIDIA H100 80GB run Codestral 22B?

22B parameter Code model on 80GB HBM3

Yes — runs at full precision
~48-59 tok/sFast
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 H100 80GB has 80GB — enough to run it without any quantization.

FP16 (Full Precision)44GB (36GB free)

Maximum quality, no quantization

Q8 (8-bit)22GB (58GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)13GB (67GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 80GB HBM3 at 3350 GB/s bandwidth
Recommended system RAM: 160GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

Codestral 22B at this precision on NVIDIA H100 80GB 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 H100 80GB Specs

VRAM80GB HBM3
Memory Bandwidth3350 GB/s
TDP350W
CUDA Cores14,592
Street Price~$22000
AI Rating10/10

Other Code Models on NVIDIA H100 80GB

About Codestral 22B

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

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