Can Granite Code 8B run on Tesla P40 24GB?

YES — Runs Great

A74Great
Estimated from fit model

Granite Code 8B needs ~10.4 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~45 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: 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) 10.4 GB, 45.0 tok/s, Runs well
10.4 GB required24.0 GB available
43% VRAM used

Fit status

Runs well

Decode

45.0 tok/s

TTFT

4305 ms

Safe context

8K

Memory

10.4 GB / 24.0 GB

Memory breakdown

Weights4.9 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom2.4 GB

See how fast it feels

See how fast it feelsGranite Code 8B on Tesla P40 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: 45.0 tok/s decode · 4.3s TTFT (warm) · 112 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well45.0 tok/s2348 ms8K
CodingARuns well45.0 tok/s4305 ms8K
Agentic CodingARuns well45.0 tok/s6262 ms8K
ReasoningARuns well45.0 tok/s5088 ms8K
RAGARuns well45.0 tok/s7828 ms8K

Quantization options

How Granite Code 8B (8B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowB70
Q3_K_S
3
3.9 GB
LowA70
NVFP4
4
4.5 GB
MediumA70
Q4_K_M
4
4.9 GB
MediumA71
Q5_K_M
5
5.8 GB
HighA71
Q6_K
6
6.6 GB
HighA72
Q8_0
8
8.6 GB
Very HighA73
F16Best for your GPU
16
16.4 GB
MaximumA75

Get started

Copy-paste commands to run Granite Code 8B on your machine.

Run

ollama run granite-code:8b

Your hardware

More models your Tesla P40 24GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS30.9 tok/s
AlibabaQwen 3.5 27B27BS13.4 tok/s
AlibabaQwen 3.6 27B27BS13.4 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS31.9 tok/s
AlibabaQwen 3.5 9B9BS40 tok/s

Frequently asked questions

Can Tesla P40 24GB run Granite Code 8B?

Yes, Tesla P40 24GB can run Granite Code 8B with a A grade (Runs well). Expected decode speed: 45.0 tok/s.

How much VRAM does Granite Code 8B need?

Granite Code 8B (8B parameters) requires approximately 10.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 8B?

The recommended quantization for Granite Code 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite Code 8B run at on Tesla P40 24GB?

On Tesla P40 24GB, Granite Code 8B achieves approximately 45.0 tokens per second decode speed with a time-to-first-token of 4305ms using Q4_K_M quantization.

Can Tesla P40 24GB run Granite Code 8B for coding?

For coding workloads, Granite Code 8B on Tesla P40 24GB receives a A grade with 45.0 tok/s and 8K context.

What context window can Granite Code 8B use on Tesla P40 24GB?

On Tesla P40 24GB, Granite Code 8B 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 Tesla P40 24GBSee all hardware for Granite Code 8B
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