VOOZH about

URL: https://willitrunai.com/can-run/granite-code-34b-on-h200-141gb


Can Granite Code 34B run on NVIDIA H200 141GB?

YES — Runs Great

A75Great
Estimated from fit model

Granite Code 34B needs ~39.7 GB VRAM. NVIDIA H200 141GB has 141.0 GB. With Q4_K_M quantization, expect ~194 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced
Share:

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) — 39.7 GB, 210.6 tok/s, Runs well
39.7 GB required141.0 GB available
28% VRAM used

Fit status

Runs well

Decode

210.6 tok/s

TTFT

919 ms

Safe context

8K

Memory

39.7 GB / 141.0 GB

Memory breakdown

Weights20.7 GB
KV Cache3.7 GB
Runtime1.2 GB
Headroom14.1 GB

See how fast it feels

See how fast it feelsGranite Code 34B on NVIDIA H200 141GB
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: 210.6 tok/s decode · 919ms TTFT (warm) · 527 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 well194.4 tok/s543 ms8K
CodingARuns well194.4 tok/s996 ms8K
Agentic CodingARuns well194.4 tok/s1449 ms8K
ReasoningARuns well194.4 tok/s1177 ms8K
RAGARuns well194.4 tok/s1811 ms8K

Quantization options

How Granite Code 34B (34B params) fits at each quantization level on NVIDIA H200 141GB (141.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
13.3 GB
LowB65
Q3_K_S
3
16.7 GB
LowB65
NVFP4
4

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 H200 141GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct
123BS58.4 tok/s
👁 Alibaba
Qwen 3.5 122B A10B
122BS

Frequently asked questions

See all results for NVIDIA H200 141GBSee all hardware for Granite Code 34B
19.0 GB
Medium
B66
Q4_K_M
4
20.7 GB
MediumB66
Q5_K_M
5
24.5 GB
HighB66
Q6_K
6
27.9 GB
HighB67
Q8_0
8
36.4 GB
Very HighB68
F16Best for your GPU
16
69.7 GB
MaximumA73
162.1 tok/s
👁 Alibaba
Qwen 3.6 35B A3B
35BS512.4 tok/s
👁 Alibaba
Qwen 3.5 35B A3B
35BS557.2 tok/s
👁 Mistral
Mistral Small 4 119B
119BS175.8 tok/s