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URL: https://willitrunai.com/can-run/llama-4-scout-17b-16e-on-tesla-p100-16gb

⇱ Llama 4 Scout 17B 16E on Tesla P100 16GB? No — Alternatives

Can Llama 4 Scout 17B 16E run on Tesla P100 16GB?

NO — Won't Fit

F0Won't run
○Estimated from fit model

Llama 4 Scout 17B 16E needs ~72.2 GB but Tesla P100 16GB only has 16.0 GB. Try a smaller quantization or lighter model.

Runtime: OllamaCapacity: No fitBandwidth: MediumStack: BasicBottleneck: Memory capacity
Share:

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) — 72.2 GB, exceeds 16.0 GB available
72.2 GB required16.0 GB available
451% VRAM needed

56.2 GB over capacity — needs offload or smaller quantization

Fit status

Too heavy

Decode

2.5 tok/s

TTFT

78152 ms

Safe context

4K

Memory

72.2 GB / 16.0 GB

Offload

80%

Memory breakdown

Weights66.5 GB
KV Cache2.9 GB
Runtime1.2 GB
Headroom1.6 GB

See how fast it feels

With memory offload — actual speed may be lower
See how fast it feelsLlama 4 Scout 17B 16E on Tesla P100 16GB
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: 2.5 tok/s decode · 78.2s TTFT (warm) · 6 tok/s prefill

What limits this setup

Usable VRAM is the main blocker for this model.

Not enough usable memory

The model needs 72.2 GB, but this setup only exposes 16.0 GB of usable VRAM.

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

Add more VRAM headroom

The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatFToo heavy2.5 tok/s42628 ms4K
CodingFToo heavy2.5 tok/s78152 ms4K
Agentic CodingFToo heavy2.5 tok/s113675 ms4K
ReasoningFToo heavy2.5 tok/s92361 ms4K
RAGFToo heavy2.5 tok/s142094 ms4K

Quantization options

How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on Tesla P100 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
42.5 GB
LowF0
Q3_K_S
3
53.4 GB
LowF0
NVFP4
4
61.0 GB
MediumF0
Q4_K_M
4
66.5 GB
MediumF0
Q5_K_M
5
78.5 GB
HighF0
Q6_K
6
89.4 GB
HighF0
Q8_0
8
116.6 GB
Very HighF0
F16
16
223.5 GB
MaximumF0

Upgrade options

Hardware that runs Llama 4 Scout 17B 16E well

👁 NVIDIA
RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pick
96 GB VRAM (+80)1792 GB/s (+1060)
A
Makes the model fit on the accelerator instead of staying completely out of reach.57.6 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$9,999 MSRP

👁 NVIDIA
RTX PRO 6000 Blackwell Server Edition 96GBBest value
96 GB VRAM (+80)1597 GB/s (+865)
A
Makes the model fit on the accelerator instead of staying completely out of reach.51.3 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$9,999 MSRP

👁 NVIDIA
NVIDIA H20 96GBNVIDIA upgrade
96 GB VRAM (+80)4000 GB/s (+3268)
A
Makes the model fit on the accelerator instead of staying completely out of reach.123.9 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$12,000 MSRP

Frequently asked questions

See all results for Tesla P100 16GBSee all hardware for Llama 4 Scout 17B 16E