Will It Run AI

Can Granite Code 20B run on NVIDIA A16 64GB?

YES — Runs Great

A77Great
Estimated from fit model

Granite Code 20B needs ~23.0 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~41 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: 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) 23.0 GB, 41.4 tok/s, Runs well
23.0 GB required64.0 GB available
36% VRAM used

Fit status

Runs well

Decode

41.4 tok/s

TTFT

4673 ms

Safe context

8K

Memory

23.0 GB / 64.0 GB

Memory breakdown

Weights12.2 GB
KV Cache3.2 GB
Runtime1.2 GB
Headroom6.4 GB

See how fast it feels

See how fast it feelsGranite Code 20B on NVIDIA A16 64GB
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: 41.4 tok/s decode · 4.7s TTFT (warm) · 104 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 well41.4 tok/s2549 ms8K
CodingARuns well41.4 tok/s4673 ms8K
Agentic CodingARuns well41.4 tok/s6797 ms8K
ReasoningARuns well41.4 tok/s5523 ms8K
RAGARuns well41.4 tok/s8496 ms8K

Quantization options

How Granite Code 20B (20B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
LowA71
Q3_K_S
3
9.8 GB
LowA71
NVFP4
4
11.2 GB
MediumA71
Q4_K_M
4
12.2 GB
MediumA71
Q5_K_M
5
14.4 GB
HighA72
Q6_K
6
16.4 GB
HighA72
Q8_0
8
21.4 GB
Very HighA73
F16Best for your GPU
16
41.0 GB
MaximumA77

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 A16 64GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS70.8 tok/s
AlibabaQwen 3.5 27B27BS30.7 tok/s
AlibabaQwen 3.6 27B27BS30.8 tok/s
AlibabaQwen 3.6 35B A3B35BS59.5 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS73.2 tok/s

Frequently asked questions

Can NVIDIA A16 64GB run Granite Code 20B?

Yes, NVIDIA A16 64GB can run Granite Code 20B with a A grade (Runs well). Expected decode speed: 41.4 tok/s.

How much VRAM does Granite Code 20B need?

Granite Code 20B (20B parameters) requires approximately 23.0 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 A16 64GB?

On NVIDIA A16 64GB, Granite Code 20B achieves approximately 41.4 tokens per second decode speed with a time-to-first-token of 4673ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run Granite Code 20B for coding?

For coding workloads, Granite Code 20B on NVIDIA A16 64GB receives a A grade with 41.4 tok/s and 8K context.

What context window can Granite Code 20B use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, 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 A16 64GBSee all hardware for Granite Code 20B
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