Can Granite Code 20B run on NVIDIA A100 40GB?

YES — Runs Great

A83Great
Estimated from fit model

Granite Code 20B needs ~20.6 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~116 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced
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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) 20.6 GB, 115.6 tok/s, Runs well
20.6 GB required40.0 GB available
52% VRAM used

Fit status

Runs well

Decode

115.6 tok/s

TTFT

1674 ms

Safe context

8K

Memory

20.6 GB / 40.0 GB

Memory breakdown

Weights12.2 GB
KV Cache3.2 GB
Runtime1.2 GB
Headroom4.0 GB

See how fast it feels

See how fast it feelsGranite Code 20B on NVIDIA A100 40GB
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: 115.6 tok/s decode · 1.7s TTFT (warm) · 289 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 well115.6 tok/s913 ms8K
CodingARuns well115.6 tok/s1674 ms8K
Agentic CodingARuns well115.6 tok/s2435 ms8K
ReasoningARuns well115.6 tok/s1979 ms8K
RAGARuns well115.6 tok/s3044 ms8K

Quantization options

How Granite Code 20B (20B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
LowA73
Q3_K_S
3
9.8 GB
LowA74
NVFP4
4
11.2 GB
MediumA74
Q4_K_M
4
12.2 GB
MediumA75
Q5_K_M
5
14.4 GB
HighA75
Q6_K
6
16.4 GB
HighA76
Q8_0Best for your GPU
8
21.4 GB
Very HighA78
F16
16
41.0 GB
MaximumF0

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 A100 40GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS197.5 tok/s
AlibabaQwen 3.5 27B27BS85.7 tok/s
AlibabaQwen 3.6 27B27BS85.9 tok/s
AlibabaQwen 3.6 35B A3B35BS166 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS204.3 tok/s

Frequently asked questions

Can NVIDIA A100 40GB run Granite Code 20B?

Yes, NVIDIA A100 40GB can run Granite Code 20B with a A grade (Runs well). Expected decode speed: 115.6 tok/s.

How much VRAM does Granite Code 20B need?

Granite Code 20B (20B parameters) requires approximately 20.6 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 A100 40GB?

On NVIDIA A100 40GB, Granite Code 20B achieves approximately 115.6 tokens per second decode speed with a time-to-first-token of 1674ms using Q4_K_M quantization.

Can NVIDIA A100 40GB run Granite Code 20B for coding?

For coding workloads, Granite Code 20B on NVIDIA A100 40GB receives a A grade with 115.6 tok/s and 8K context.

What context window can Granite Code 20B use on NVIDIA A100 40GB?

On NVIDIA A100 40GB, 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 A100 40GBSee all hardware for Granite Code 20B
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