Will It Run AI

Can Granite Code 20B run on RTX A5000 24GB?

YES — Runs Great

A84Great
Estimated from fit model

Granite Code 20B needs ~19.0 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~48 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) 19.0 GB, 47.6 tok/s, Runs well
19.0 GB required24.0 GB available
79% VRAM used

Fit status

Runs well

Decode

47.6 tok/s

TTFT

4068 ms

Safe context

8K

Memory

19.0 GB / 24.0 GB

Memory breakdown

Weights12.2 GB
KV Cache3.2 GB
Runtime1.2 GB
Headroom2.4 GB

See how fast it feels

See how fast it feelsGranite Code 20B on RTX A5000 24GB
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: 47.6 tok/s decode · 4.1s TTFT (warm) · 119 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 well47.6 tok/s2219 ms8K
CodingARuns well47.6 tok/s4068 ms8K
Agentic CodingATight fit47.6 tok/s5917 ms8K
ReasoningARuns well47.6 tok/s4808 ms8K
RAGATight fit47.6 tok/s7396 ms8K

Quantization options

How Granite Code 20B (20B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
LowA77
Q3_K_S
3
9.8 GB
LowA78
NVFP4
4
11.2 GB
MediumA79
Q4_K_M
4
12.2 GB
MediumA80
Q5_K_M
5
14.4 GB
HighA80
Q6_KBest for your GPU
6
16.4 GB
HighA79
Q8_0
8
21.4 GB
Very HighF0
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 A5000 24GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS81.3 tok/s
AlibabaQwen 3.5 27B27BS35.3 tok/s
AlibabaQwen 3.6 27B27BS35.4 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS84.1 tok/s
AlibabaQwen 3.5 35B A3B35BA45.5 tok/s

Frequently asked questions

Can RTX A5000 24GB run Granite Code 20B?

Yes, RTX A5000 24GB can run Granite Code 20B with a A grade (Runs well). Expected decode speed: 47.6 tok/s.

How much VRAM does Granite Code 20B need?

Granite Code 20B (20B parameters) requires approximately 19.0 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 RTX A5000 24GB?

On RTX A5000 24GB, Granite Code 20B achieves approximately 47.6 tokens per second decode speed with a time-to-first-token of 4068ms using Q4_K_M quantization.

Can RTX A5000 24GB run Granite Code 20B for coding?

For coding workloads, Granite Code 20B on RTX A5000 24GB receives a A grade with 47.6 tok/s and 8K context.

What context window can Granite Code 20B use on RTX A5000 24GB?

On RTX A5000 24GB, 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 A5000 24GBSee all hardware for Granite Code 20B
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