Will It Run AI

Can Granite Code 20B run on NVIDIA H100 80GB?

YES — Runs Great

A78Great
Estimated from fit model

Granite Code 20B needs ~24.6 GB VRAM. NVIDIA H100 80GB has 80.0 GB. With Q4_K_M quantization, expect ~231 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced
Share:

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 24.6 GB, 249.1 tok/s, Runs well
24.6 GB required80.0 GB available
31% VRAM used

Fit status

Runs well

Decode

249.1 tok/s

TTFT

777 ms

Safe context

8K

Memory

24.6 GB / 80.0 GB

Memory breakdown

Weights12.2 GB
KV Cache3.2 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsGranite Code 20B on NVIDIA H100 80GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort: def quicksort(arr): if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quicksort(left) + middle + quicksort(right) # Example usage numbers = [3, 6, 8, 10, 1, 2, 1] print(quicksort(numbers)) # [1, 1, 2, 3, 6, 8, 10] The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]: """Sort a list using the quicksort algorithm. Args: arr: List of integers to sort. Returns: A new sorted list. """ if len(arr) <= 1: return arr pivot = arr[len(arr) // 2] left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot] return quicksort(left) + middle + quicksort(right) Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 249.1 tok/s decode · 777ms TTFT (warm) · 623 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well230.7 tok/s458 ms8K
CodingARuns well230.7 tok/s839 ms8K
Agentic CodingARuns well230.7 tok/s1221 ms8K
ReasoningARuns well230.7 tok/s992 ms8K
RAGARuns well230.7 tok/s1526 ms8K

Quantization options

How Granite Code 20B (20B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
LowB70
Q3_K_S
3
9.8 GB
LowB70
NVFP4
4
11.2 GB
MediumB70
Q4_K_M
4
12.2 GB
MediumA70
Q5_K_M
5
14.4 GB
HighA70
Q6_K
6
16.4 GB
HighA71
Q8_0
8
21.4 GB
Very HighA72
F16Best for your GPU
16
41.0 GB
MaximumA76

Get started

Copy-paste commands to run Granite Code 20B on your machine.

Run

ollama run granite-code:20b

Your hardware

More models your NVIDIA H100 80GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BA28.9 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS425.5 tok/s
AlibabaQwen 3.5 27B27BS184.5 tok/s
AlibabaQwen 3.6 27B27BS185.1 tok/s
AlibabaQwen 3.5 122B A10B122BS85.5 tok/s

Frequently asked questions

Can NVIDIA H100 80GB run Granite Code 20B?

Yes, NVIDIA H100 80GB can run Granite Code 20B with a A grade (Runs well). Expected decode speed: 230.7 tok/s.

How much VRAM does Granite Code 20B need?

Granite Code 20B (20B parameters) requires approximately 24.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 20B?

The recommended quantization for Granite Code 20B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite Code 20B run at on NVIDIA H100 80GB?

On NVIDIA H100 80GB, Granite Code 20B achieves approximately 230.7 tokens per second decode speed with a time-to-first-token of 839ms using Q4_K_M quantization.

Can NVIDIA H100 80GB run Granite Code 20B for coding?

For coding workloads, Granite Code 20B on NVIDIA H100 80GB receives a A grade with 230.7 tok/s and 8K context.

What context window can Granite Code 20B use on NVIDIA H100 80GB?

On NVIDIA H100 80GB, Granite Code 20B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.

See all results for NVIDIA H100 80GBSee all hardware for Granite Code 20B
Embed this result

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/granite-code-20b-on-h100-80gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: