Can Nemotron 70B run on NVIDIA A16 64GB?

YES — Tight Fit

B69Good

Estimated from fit model

Nemotron 70B needs ~54.9 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~12 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: MediumStack: StandardBottleneck: 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) — 54.9 GB, 11.9 tok/s, Tight fit

54.9 GB required64.0 GB available

86% VRAM used

Fit status

Tight fit

Decode

11.9 tok/s

TTFT

16243 ms

Safe context

46K

Memory

54.9 GB / 64.0 GB

Memory breakdown

Weights42.7 GB

KV Cache4.9 GB

Runtime0.9 GB

Headroom6.4 GB

See how fast it feels

See how fast it feelsNemotron 70B on NVIDIA A16 64GB
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: 11.9 tok/s decode · 16.2s TTFT (warm) · 30 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	11.9 tok/s	8860 ms	46K
Coding	B	Tight fit	11.9 tok/s	16243 ms	46K
Agentic Coding	B	Tight fit	11.9 tok/s	23626 ms	46K
Reasoning	B	Tight fit	11.9 tok/s	19196 ms	46K
RAG	B	Tight fit	11.9 tok/s	29532 ms	46K

Quantization options

How Nemotron 70B (70B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	27.3 GB	Low	B68
Q3_K_S	3	34.3 GB	Low	B69
NVFP4	4

Get started

Copy-paste commands to run Nemotron 70B on your machine.

Run

ollama run nemotron

Upgrade options

Hardware that runs Nemotron 70B well

RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pick

96 GB VRAM (+32)1792 GB/s (+1192)

Raises estimated decode speed by about 222%.38.3 tok/s decode

Raises estimated decode speed by about 222%.

Adds memory headroom for longer context windows and future model growth.

~$9,999 MSRP

RTX PRO 6000 Blackwell Server Edition 96GBBest value

96 GB VRAM (+32)1597 GB/s (+997)

Raises estimated decode speed by about 187%.34.2 tok/s decode

Raises estimated decode speed by about 187%.

Adds memory headroom for longer context windows and future model growth.

~$9,999 MSRP

NVIDIA H20 96GBNVIDIA upgrade

96 GB VRAM (+32)4000 GB/s (+3400)

Raises estimated decode speed by about 593%.82.5 tok/s decode

Raises estimated decode speed by about 593%.

Adds memory headroom for longer context windows and future model growth.

~$12,000 MSRP

Frequently asked questions

Can NVIDIA A16 64GB run Nemotron 70B?

Yes, NVIDIA A16 64GB can run Nemotron 70B with a B grade (Tight fit). Expected decode speed: 11.9 tok/s.

How much VRAM does Nemotron 70B need?

Nemotron 70B (70B parameters) requires approximately 54.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Nemotron 70B?

The recommended quantization for Nemotron 70B is Q4_K_M, which balances quality and memory efficiency.

What speed will Nemotron 70B run at on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Nemotron 70B achieves approximately 11.9 tokens per second decode speed with a time-to-first-token of 16243ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run Nemotron 70B for coding?

For coding workloads, Nemotron 70B on NVIDIA A16 64GB receives a B grade with 11.9 tok/s and 46K context.

What context window can Nemotron 70B use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Nemotron 70B can safely use up to 46K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA A16 64GB See all hardware for Nemotron 70B

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