Will It Run AI

Can Granite Code 34B run on NVIDIA A800 80GB?

YES — Runs Great

A77Great
Estimated from fit model

Granite Code 34B needs ~33.6 GB VRAM. NVIDIA A800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~79 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) 33.6 GB, 78.8 tok/s, Runs well
33.6 GB required80.0 GB available
42% VRAM used

Fit status

Runs well

Decode

78.8 tok/s

TTFT

2456 ms

Safe context

8K

Memory

33.6 GB / 80.0 GB

Memory breakdown

Weights20.7 GB
KV Cache3.7 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsGranite Code 34B 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: 78.8 tok/s decode · 2.5s TTFT (warm) · 197 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 well78.8 tok/s1339 ms8K
CodingARuns well78.8 tok/s2456 ms8K
Agentic CodingARuns well78.8 tok/s3572 ms8K
ReasoningARuns well78.8 tok/s2902 ms8K
RAGARuns well78.8 tok/s4465 ms8K

Quantization options

How Granite Code 34B (34B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
13.3 GB
LowB68
Q3_K_S
3
16.7 GB
LowB68
NVFP4
4
19.0 GB
MediumB69
Q4_K_M
4
20.7 GB
MediumB69
Q5_K_M
5
24.5 GB
HighB70
Q6_K
6
27.9 GB
HighA70
Q8_0Best for your GPU
8
36.4 GB
Very HighA72
F16
16
69.7 GB
MaximumF0

Get started

Copy-paste commands to run Granite Code 34B on your machine.

Run

ollama run granite-code:34b

Your hardware

More models your NVIDIA A800 80GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BA15.5 tok/s
AlibabaQwen 3.5 122B A10B122BA45.9 tok/s
AlibabaQwen 3.6 35B A3B35BS191.8 tok/s
AlibabaQwen 3.5 35B A3B35BS208.6 tok/s
MistralMistral Small 4 119B119BA48.7 tok/s

Frequently asked questions

Can NVIDIA A800 80GB run Granite Code 34B?

Yes, NVIDIA A800 80GB can run Granite Code 34B with a A grade (Runs well). Expected decode speed: 78.8 tok/s.

How much VRAM does Granite Code 34B need?

Granite Code 34B (34B parameters) requires approximately 33.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 34B?

The recommended quantization for Granite Code 34B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite Code 34B run at on NVIDIA A800 80GB?

On NVIDIA A800 80GB, Granite Code 34B achieves approximately 78.8 tokens per second decode speed with a time-to-first-token of 2456ms using Q4_K_M quantization.

Can NVIDIA A800 80GB run Granite Code 34B for coding?

For coding workloads, Granite Code 34B on NVIDIA A800 80GB receives a A grade with 78.8 tok/s and 8K context.

What context window can Granite Code 34B use on NVIDIA A800 80GB?

On NVIDIA A800 80GB, Granite Code 34B 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 A800 80GBSee all hardware for Granite Code 34B
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