Can Qwen 2.5 14B run on NVIDIA H100 PCIe 80GB?

YES — Runs Great

A78Great

Estimated from fit model

Qwen 2.5 14B needs ~20.7 GB VRAM. NVIDIA H100 PCIe 80GB has 80.0 GB. With Q4_K_M quantization, expect ~196 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: 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) — 20.7 GB, 196.0 tok/s, Runs well

20.7 GB required80.0 GB available

26% VRAM used

Fit status

Runs well

Decode

196.0 tok/s

TTFT

988 ms

Safe context

131K

Memory

20.7 GB / 80.0 GB

Memory breakdown

Weights8.5 GB

KV Cache2.9 GB

Runtime1.2 GB

Headroom8.0 GB

See how fast it feels

See how fast it feelsQwen 2.5 14B on NVIDIA H100 PCIe 80GB
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: 196.0 tok/s decode · 988ms TTFT (warm) · 490 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	196.0 tok/s	539 ms	131K
Coding	A	Runs well	196.0 tok/s	988 ms	131K
Agentic Coding	A	Runs well	196.0 tok/s	1437 ms	131K
Reasoning	A	Runs well	196.0 tok/s	1167 ms	131K
RAG	A	Runs well	196.0 tok/s	1796 ms	131K

Quantization options

How Qwen 2.5 14B (14B params) fits at each quantization level on NVIDIA H100 PCIe 80GB (80.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	A71
Q3_K_S	3	6.9 GB	Low	A71
NVFP4	4	7.8 GB	Medium	A71
Q4_K_M	4	8.5 GB	Medium	A71
Q5_K_M	5	10.1 GB	High	A71
Q6_K	6	11.5 GB	High	A71
Q8_0	8	15.0 GB	Very High	A72
F16Best for your GPU	16	28.7 GB	Maximum	A74

Get started

Copy-paste commands to run Qwen 2.5 14B on your machine.

Run

ollama run qwen2.5

Your hardware

More models your NVIDIA H100 PCIe 80GB can run

Model	Params	Grade	Decode
Devstral 2 123B Instruct	123B	A	14.8 tok/s
Qwen3-Coder 30B A3B Instruct	30.5B	S	254 tok/s
Qwen 3.5 27B	27B	S	110.2 tok/s
Qwen 3.6 27B	27B	S	110.5 tok/s
Qwen 3.5 122B A10B	122B	A	44.5 tok/s

Frequently asked questions

Can NVIDIA H100 PCIe 80GB run Qwen 2.5 14B?

Yes, NVIDIA H100 PCIe 80GB can run Qwen 2.5 14B with a A grade (Runs well). Expected decode speed: 196.0 tok/s.

How much VRAM does Qwen 2.5 14B need?

Qwen 2.5 14B (14B parameters) requires approximately 20.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 14B?

The recommended quantization for Qwen 2.5 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 14B run at on NVIDIA H100 PCIe 80GB?

On NVIDIA H100 PCIe 80GB, Qwen 2.5 14B achieves approximately 196.0 tokens per second decode speed with a time-to-first-token of 988ms using Q4_K_M quantization.

Can NVIDIA H100 PCIe 80GB run Qwen 2.5 14B for coding?

For coding workloads, Qwen 2.5 14B on NVIDIA H100 PCIe 80GB receives a A grade with 196.0 tok/s and 131K context.

What context window can Qwen 2.5 14B use on NVIDIA H100 PCIe 80GB?

On NVIDIA H100 PCIe 80GB, Qwen 2.5 14B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA H100 PCIe 80GB See all hardware for Qwen 2.5 14B

Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/qwen-2.5-14b-on-h100-pcie-80gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: