Will It Run AI

Can Mistral 7B Instruct v0.3 run on Tesla P40 24GB?

YES — Runs Great

B61Good
Estimated from fit model

Mistral 7B Instruct v0.3 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
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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) — 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

8K

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 feelsMistral 7B Instruct v0.3 on Tesla P40 24GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
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

WorkloadGradeFitDecodeTTFTContext
ChatBRuns well51.4 tok/s2055 ms8K
CodingBRuns well51.4 tok/s3767 ms8K
Agentic CodingBRuns well51.4 tok/s5479 ms8K
ReasoningBRuns well51.4 tok/s4452 ms8K
RAGBRuns well51.4 tok/s6849 ms8K

Quantization options

How Mistral 7B Instruct v0.3 (7B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowB57
Q3_K_S
3
3.4 GB
LowB57
NVFP4
4
3.9 GB
MediumB57
Q4_K_M
4
4.3 GB
MediumB57
Q5_K_M
5
5.0 GB
HighB58
Q6_K
6
5.7 GB
HighB58
Q8_0
8
7.5 GB
Very HighB59
F16Best for your GPU
16
14.3 GB
MaximumB62

Get started

Copy-paste commands to run Mistral 7B Instruct v0.3 on your machine.

Run

lms load Mistral-7B-Instruct-v0.3 && lms server start

Opciones de mejora

Hardware que ejecuta bien Mistral 7B Instruct v0.3

NVIDIARTX 5090 32GBOpción económica
32 GB VRAM (+8)1792 GB/s (+1446)
B
Sube la velocidad estimada de decodificación alrededor de un 91%.98 tok/s decodificación

Sube la velocidad estimada de decodificación alrededor de un 91%.

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$1,999 MSRP

NVIDIARTX PRO 4500 Blackwell 32GBMejor relación calidad-precio
32 GB VRAM (+8)896 GB/s (+550)
B
Sube la velocidad estimada de decodificación alrededor de un 91%.98 tok/s decodificación

Sube la velocidad estimada de decodificación alrededor de un 91%.

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$2,499 MSRP

NVIDIARTX 5000 Ada 32GBMejora NVIDIA
32 GB VRAM (+8)576 GB/s (+230)
B
Sube la velocidad estimada de decodificación alrededor de un 91%.98 tok/s decodificación

Sube la velocidad estimada de decodificación alrededor de un 91%.

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$4,000 MSRP

Frequently asked questions

Can Tesla P40 24GB run Mistral 7B Instruct v0.3?

Yes, Tesla P40 24GB can run Mistral 7B Instruct v0.3 with a B grade (Runs well). Expected decode speed: 51.4 tok/s.

How much VRAM does Mistral 7B Instruct v0.3 need?

Mistral 7B Instruct v0.3 (7B parameters) requires approximately 9.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Mistral 7B Instruct v0.3?

The recommended quantization for Mistral 7B Instruct v0.3 is Q4_K_M, which balances quality and memory efficiency.

What speed will Mistral 7B Instruct v0.3 run at on Tesla P40 24GB?

On Tesla P40 24GB, Mistral 7B Instruct v0.3 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 Mistral 7B Instruct v0.3 for coding?

For coding workloads, Mistral 7B Instruct v0.3 on Tesla P40 24GB receives a B grade with 51.4 tok/s and 8K context.

What context window can Mistral 7B Instruct v0.3 use on Tesla P40 24GB?

On Tesla P40 24GB, Mistral 7B Instruct v0.3 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 Mistral 7B Instruct v0.3
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