Will It Run AI

Can Gemma 2 27B run on NVIDIA H100 80GB?

YES — Runs Great

A71Great
Estimated from fit model

Gemma 2 27B needs ~36.9 GB VRAM. NVIDIA H100 80GB has 80.0 GB. With Q4_K_M quantization, expect ~179 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: 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) 36.9 GB, 179.4 tok/s, Runs well
36.9 GB required80.0 GB available
46% VRAM used

Fit status

Runs well

Decode

179.4 tok/s

TTFT

1079 ms

Safe context

8K

Memory

36.9 GB / 80.0 GB

Memory breakdown

Weights16.5 GB
KV Cache11.2 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsGemma 2 27B on NVIDIA H100 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: 179.4 tok/s decode · 1.1s TTFT (warm) · 449 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

WorkloadGradeFitDecodeTTFTContext
ChatBRuns well179.4 tok/s589 ms8K
CodingARuns well179.4 tok/s1079 ms8K
Agentic CodingARuns well179.4 tok/s1570 ms8K
ReasoningARuns well179.4 tok/s1275 ms8K
RAGARuns well179.4 tok/s1962 ms8K

Quantization options

How Gemma 2 27B (27B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
10.5 GB
LowB60
Q3_K_S
3
13.2 GB
LowB60
NVFP4
4
15.1 GB
MediumB61
Q4_K_M
4
16.5 GB
MediumB61
Q5_K_M
5
19.4 GB
HighB61
Q6_K
6
22.1 GB
HighB62
Q8_0
8
28.9 GB
Very HighB63
F16Best for your GPU
16
55.4 GB
MaximumB67

Get started

Copy-paste commands to run Gemma 2 27B on your machine.

Run

ollama run gemma2:27b

Your hardware

More models your NVIDIA H100 80GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BA28.9 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS425.5 tok/s
AlibabaQwen 3.5 122B A10B122BS85.5 tok/s
AlibabaQwen 3.6 35B A3B35BS357.6 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS440.1 tok/s

Frequently asked questions

Can NVIDIA H100 80GB run Gemma 2 27B?

Yes, NVIDIA H100 80GB can run Gemma 2 27B with a A grade (Runs well). Expected decode speed: 179.4 tok/s.

How much VRAM does Gemma 2 27B need?

Gemma 2 27B (27B parameters) requires approximately 36.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Gemma 2 27B?

The recommended quantization for Gemma 2 27B is Q4_K_M, which balances quality and memory efficiency.

What speed will Gemma 2 27B run at on NVIDIA H100 80GB?

On NVIDIA H100 80GB, Gemma 2 27B achieves approximately 179.4 tokens per second decode speed with a time-to-first-token of 1079ms using Q4_K_M quantization.

Can NVIDIA H100 80GB run Gemma 2 27B for coding?

For coding workloads, Gemma 2 27B on NVIDIA H100 80GB receives a A grade with 179.4 tok/s and 8K context.

What context window can Gemma 2 27B use on NVIDIA H100 80GB?

On NVIDIA H100 80GB, Gemma 2 27B 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 NVIDIA H100 80GBSee all hardware for Gemma 2 27B
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