Can DevStral 7B run on Tesla P40 24GB?

YES — Runs Great

A74Great

Estimated from fit model

DevStral 7B needs ~9.8 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~51 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: 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) — 9.8 GB, 51.4 tok/s, Runs well

9.8 GB required24.0 GB available

41% VRAM used

Fit status

Runs well

Decode

51.4 tok/s

TTFT

3767 ms

Safe context

Memory

9.8 GB / 24.0 GB

Memory breakdown

Weights4.3 GB

KV Cache2.0 GB

Runtime1.2 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsDevStral 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: 51.4 tok/s decode · 3.8s TTFT (warm) · 129 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	51.4 tok/s	2055 ms	8K
Coding	A	Runs well	51.4 tok/s	3767 ms	8K
Agentic Coding	A	Runs well	51.4 tok/s	5479 ms	8K
Reasoning	A	Runs well	51.4 tok/s	4452 ms	8K
RAG	A	Runs well	51.4 tok/s	6849 ms	8K

Quantization options

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

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	B69
Q3_K_S	3	3.4 GB	Low	B70
NVFP4	4	3.9 GB	Medium	A70
Q4_K_M	4	4.3 GB	Medium	A70
Q5_K_M	5	5.0 GB	High	A71
Q6_K	6	5.7 GB	High	A71
Q8_0	8	7.5 GB	Very High	A72
F16Best for your GPU	16	14.3 GB	Maximum	A75

Get started

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

Run

ollama run devstral

Your hardware

More models your Tesla P40 24GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	30.9 tok/s
Qwen 3.5 27B	27B	S	13.4 tok/s
Qwen 3.6 27B	27B	S	13.4 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	31.9 tok/s
Qwen 3.5 9B	9B	S	40 tok/s

Frequently asked questions

Can Tesla P40 24GB run DevStral 7B?

Yes, Tesla P40 24GB can run DevStral 7B with a A grade (Runs well). Expected decode speed: 51.4 tok/s.

How much VRAM does DevStral 7B need?

DevStral 7B (7B parameters) requires approximately 9.8 GB of memory with Q4_K_M quantization.

What is the best quantization for DevStral 7B?

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

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

On Tesla P40 24GB, DevStral 7B achieves approximately 51.4 tokens per second decode speed with a time-to-first-token of 3767ms using Q4_K_M quantization.

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

For coding workloads, DevStral 7B on Tesla P40 24GB receives a A grade with 51.4 tok/s and 8K context.

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

On Tesla P40 24GB, DevStral 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 24GB See all hardware for DevStral 7B

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