Will It Run AI

Can Granite Code 20B run on RTX 5000 Ada 32GB?

YES — Runs Great

A82Great
Estimated from fit model

Granite Code 20B needs ~19.8 GB VRAM. RTX 5000 Ada 32GB has 32.0 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) 19.8 GB, 40.8 tok/s, Runs well
19.8 GB required32.0 GB available
62% VRAM used

Fit status

Runs well

Decode

40.8 tok/s

TTFT

4746 ms

Safe context

8K

Memory

19.8 GB / 32.0 GB

Memory breakdown

Weights12.2 GB
KV Cache3.2 GB
Runtime1.2 GB
Headroom3.2 GB

See how fast it feels

See how fast it feelsGranite Code 20B on RTX 5000 Ada 32GB
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: 40.8 tok/s decode · 4.7s TTFT (warm) · 102 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 well40.8 tok/s2589 ms8K
CodingARuns well40.8 tok/s4746 ms8K
Agentic CodingARuns well40.8 tok/s6903 ms8K
ReasoningARuns well40.8 tok/s5609 ms8K
RAGARuns well40.8 tok/s8629 ms8K

Quantization options

How Granite Code 20B (20B params) fits at each quantization level on RTX 5000 Ada 32GB (32.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
LowA75
Q3_K_S
3
9.8 GB
LowA75
NVFP4
4
11.2 GB
MediumA76
Q4_K_M
4
12.2 GB
MediumA77
Q5_K_M
5
14.4 GB
HighA78
Q6_K
6
16.4 GB
HighA79
Q8_0Best for your GPU
8
21.4 GB
Very HighA79
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 RTX 5000 Ada 32GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS69.7 tok/s
AlibabaQwen 3.5 27B27BS30.2 tok/s
AlibabaQwen 3.6 27B27BS30.3 tok/s
AlibabaQwen 3.6 35B A3B35BS58.6 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS72.1 tok/s

Frequently asked questions

Can RTX 5000 Ada 32GB run Granite Code 20B?

Yes, RTX 5000 Ada 32GB can run Granite Code 20B with a A grade (Runs well). Expected decode speed: 40.8 tok/s.

How much VRAM does Granite Code 20B need?

Granite Code 20B (20B parameters) requires approximately 19.8 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 RTX 5000 Ada 32GB?

On RTX 5000 Ada 32GB, Granite Code 20B achieves approximately 40.8 tokens per second decode speed with a time-to-first-token of 4746ms using Q4_K_M quantization.

Can RTX 5000 Ada 32GB run Granite Code 20B for coding?

For coding workloads, Granite Code 20B on RTX 5000 Ada 32GB receives a A grade with 40.8 tok/s and 8K context.

What context window can Granite Code 20B use on RTX 5000 Ada 32GB?

On RTX 5000 Ada 32GB, 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 RTX 5000 Ada 32GBSee all hardware for Granite Code 20B
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