Can StarCoder 7B run on Tesla P40 24GB?

YES — Runs Great

A77Great
Estimated from fit model

StarCoder 7B needs ~15.2 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~48 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) 15.2 GB, 47.8 tok/s, Runs well
15.2 GB required24.0 GB available
63% VRAM used

Fit status

Runs well

Decode

47.8 tok/s

TTFT

4050 ms

Safe context

8K

Memory

15.2 GB / 24.0 GB

Memory breakdown

Weights4.3 GB
KV Cache7.3 GB
Runtime1.2 GB
Headroom2.4 GB

See how fast it feels

See how fast it feelsStarCoder 7B 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: 47.8 tok/s decode · 4.0s TTFT (warm) · 120 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 well47.8 tok/s2209 ms8K
CodingARuns well47.8 tok/s4050 ms8K
Agentic CodingATight fit47.8 tok/s5890 ms8K
ReasoningARuns well47.8 tok/s4786 ms8K
RAGATight fit47.8 tok/s7363 ms8K

Quantization options

How StarCoder 7B (7B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowB68
Q3_K_S
3
3.4 GB
LowB68
NVFP4
4
3.9 GB
MediumB68
Q4_K_M
4
4.3 GB
MediumB68
Q5_K_M
5
5.0 GB
HighB69
Q6_K
6
5.7 GB
HighB69
Q8_0
8
7.5 GB
Very HighA70
F16Best for your GPU
16
14.3 GB
MaximumA73

Get started

Copy-paste commands to run StarCoder 7B on your machine.

Run

lms load starcoder-7b && lms server start

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 StarCoder 7B?

Yes, Tesla P40 24GB can run StarCoder 7B with a A grade (Runs well). Expected decode speed: 47.8 tok/s.

How much VRAM does StarCoder 7B need?

StarCoder 7B (7B parameters) requires approximately 15.2 GB of memory with Q4_K_M quantization.

What is the best quantization for StarCoder 7B?

The recommended quantization for StarCoder 7B is Q4_K_M, which balances quality and memory efficiency.

What speed will StarCoder 7B run at on Tesla P40 24GB?

On Tesla P40 24GB, StarCoder 7B achieves approximately 47.8 tokens per second decode speed with a time-to-first-token of 4050ms using Q4_K_M quantization.

Can Tesla P40 24GB run StarCoder 7B for coding?

For coding workloads, StarCoder 7B on Tesla P40 24GB receives a A grade with 47.8 tok/s and 8K context.

What context window can StarCoder 7B use on Tesla P40 24GB?

On Tesla P40 24GB, StarCoder 7B 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 StarCoder 7B
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