Can Gemma 2 27B run on NVIDIA L20 48GB?

YES — Runs Great

A74Great

Estimated from fit model

Gemma 2 27B needs ~33.7 GB VRAM. NVIDIA L20 48GB has 48.0 GB. With Q4_K_M quantization, expect ~40 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) — 33.7 GB, 40.2 tok/s, Runs well

33.7 GB required48.0 GB available

70% VRAM used

Fit status

Runs well

Decode

40.2 tok/s

TTFT

4815 ms

Safe context

Memory

33.7 GB / 48.0 GB

Memory breakdown

Weights16.5 GB

KV Cache11.2 GB

Runtime1.2 GB

Headroom4.8 GB

See how fast it feels

See how fast it feelsGemma 2 27B on NVIDIA L20 48GB
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: 40.2 tok/s decode · 4.8s TTFT (warm) · 101 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	40.2 tok/s	2626 ms	8K
Coding	A	Runs well	40.2 tok/s	4815 ms	8K
Agentic Coding	A	Tight fit	40.2 tok/s	7003 ms	8K
Reasoning	A	Runs well	40.2 tok/s	5690 ms	8K
RAG	A	Tight fit	40.2 tok/s	8754 ms	8K

Quantization options

How Gemma 2 27B (27B params) fits at each quantization level on NVIDIA L20 48GB (48.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	10.5 GB	Low	B63
Q3_K_S	3	13.2 GB	Low	B64
NVFP4	4	15.1 GB	Medium	B64
Q4_K_M	4	16.5 GB	Medium	B65
Q5_K_M	5	19.4 GB	High	B66
Q6_K	6	22.1 GB	High	B66
Q8_0Best for your GPU	8	28.9 GB	Very High	B68
F16	16	55.4 GB	Maximum	F0

Get started

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

Run

ollama run gemma2:27b

Your hardware

More models your NVIDIA L20 48GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	95.4 tok/s
Qwen 3.6 35B A3B	35B	S	85.8 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	98.6 tok/s
Qwen 3.5 35B A3B	35B	S	93.3 tok/s
Qwen 3 32B	32B	S	35.1 tok/s

Frequently asked questions

Can NVIDIA L20 48GB run Gemma 2 27B?

Yes, NVIDIA L20 48GB can run Gemma 2 27B with a A grade (Runs well). Expected decode speed: 40.2 tok/s.

How much VRAM does Gemma 2 27B need?

Gemma 2 27B (27B parameters) requires approximately 33.7 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 L20 48GB?

On NVIDIA L20 48GB, Gemma 2 27B achieves approximately 40.2 tokens per second decode speed with a time-to-first-token of 4815ms using Q4_K_M quantization.

Can NVIDIA L20 48GB run Gemma 2 27B for coding?

For coding workloads, Gemma 2 27B on NVIDIA L20 48GB receives a A grade with 40.2 tok/s and 8K context.

What context window can Gemma 2 27B use on NVIDIA L20 48GB?

On NVIDIA L20 48GB, 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 L20 48GB See all hardware for Gemma 2 27B

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