Can Granite Code 34B run on NVIDIA GB200 192GB?

YES — Runs Great

A74Great

Estimated from fit model

Granite Code 34B needs ~44.8 GB VRAM. NVIDIA GB200 192GB has 192.0 GB. With Q4_K_M quantization, expect ~351 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: Balanced

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) — 44.8 GB, 351.0 tok/s, Runs well

44.8 GB required192.0 GB available

23% VRAM used

Fit status

Runs well

Decode

351.0 tok/s

TTFT

552 ms

Safe context

Memory

44.8 GB / 192.0 GB

Memory breakdown

Weights20.7 GB

KV Cache3.7 GB

Runtime1.2 GB

Headroom19.2 GB

See how fast it feels

See how fast it feelsGranite Code 34B on NVIDIA GB200 192GB
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: 351.0 tok/s decode · 552ms TTFT (warm) · 878 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	351.0 tok/s	350 ms	8K
Coding	A	Runs well	351.0 tok/s	552 ms	8K
Agentic Coding	A	Runs well	351.0 tok/s	802 ms	8K
Reasoning	A	Runs well	351.0 tok/s	652 ms	8K
RAG	A	Runs well	351.0 tok/s	1003 ms	8K

Quantization options

How Granite Code 34B (34B params) fits at each quantization level on NVIDIA GB200 192GB (192.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	13.3 GB	Low	B64
Q3_K_S	3	16.7 GB	Low	B64
NVFP4	4	19.0 GB	Medium	B64
Q4_K_M	4	20.7 GB	Medium	B65
Q5_K_M	5	24.5 GB	High	B65
Q6_K	6	27.9 GB	High	B65
Q8_0	8	36.4 GB	Very High	B66
F16Best for your GPU	16	69.7 GB	Maximum	A70

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 GB200 192GB can run

Model	Params	Grade	Decode
Devstral 2 123B Instruct	123B	S	97.4 tok/s
Qwen 3.5 122B A10B	122B	S	270.2 tok/s
DeepSeek V4 Flash	284B	S	144.8 tok/s
Qwen 3.6 35B A3B	35B	S	854 tok/s
Qwen 3.5 35B A3B	35B	S	928.7 tok/s

Frequently asked questions

Can NVIDIA GB200 192GB run Granite Code 34B?

Yes, NVIDIA GB200 192GB can run Granite Code 34B with a A grade (Runs well). Expected decode speed: 351.0 tok/s.

How much VRAM does Granite Code 34B need?

Granite Code 34B (34B parameters) requires approximately 44.8 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 GB200 192GB?

On NVIDIA GB200 192GB, Granite Code 34B achieves approximately 351.0 tokens per second decode speed with a time-to-first-token of 552ms using Q4_K_M quantization.

Can NVIDIA GB200 192GB run Granite Code 34B for coding?

For coding workloads, Granite Code 34B on NVIDIA GB200 192GB receives a A grade with 351.0 tok/s and 8K context.

What context window can Granite Code 34B use on NVIDIA GB200 192GB?

On NVIDIA GB200 192GB, 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 GB200 192GB See all hardware for Granite Code 34B

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