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URL: https://willitrunai.com/can-run/granite-code-20b-on-a800-80gb


Can Granite Code 20B run on NVIDIA A800 80GB?

YES — Runs Great

A78Great
Estimated from fit model

Granite Code 20B needs ~24.6 GB VRAM. NVIDIA A800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~124 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) — 24.6 GB, 133.6 tok/s, Runs well
24.6 GB required80.0 GB available
31% VRAM used

Fit status

Runs well

Decode

133.6 tok/s

TTFT

1449 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 A800 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: 133.6 tok/s decode · 1.4s TTFT (warm) · 334 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 well123.7 tok/s854 ms8K
CodingARuns well123.7 tok/s1565 ms8K
Agentic CodingARuns well123.7 tok/s2276 ms8K
ReasoningARuns well123.7 tok/s1849 ms8K
RAGARuns well123.7 tok/s2845 ms8K

Quantization options

How Granite Code 20B (20B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
LowB70
Q3_K_S
3
9.8 GB
LowB70
NVFP4
4

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 A800 80GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct
123BA15.5 tok/s
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
30.5BS

Frequently asked questions

See all results for NVIDIA A800 80GBSee all hardware for Granite Code 20B
11.2 GB
Medium
B70
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
228.2 tok/s
👁 Alibaba
Qwen 3.5 27B
27BS99 tok/s
👁 Alibaba
Qwen 3.6 27B
27BS99.3 tok/s
👁 Alibaba
Qwen 3.5 122B A10B
122BA45.9 tok/s