Can Falcon 40B Instruct run on NVIDIA A100 80GB?

YES — Runs Great

A72Great

○Estimated from fit model

Falcon 40B Instruct needs ~39.8 GB VRAM. NVIDIA A100 80GB has 80.0 GB. With Q5_K_M quantization, expect ~61 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

Q5_K_M (High quality) — 39.8 GB, 66.0 tok/s, Runs well

39.8 GB required80.0 GB available

50% VRAM used

Fit status

Runs well

Decode

66.0 tok/s

TTFT

2935 ms

Safe context

Memory

39.8 GB / 80.0 GB

Memory breakdown

Weights28.8 GB

KV Cache1.8 GB

Runtime1.2 GB

Headroom8.0 GB

See how fast it feels

See how fast it feelsFalcon 40B Instruct on NVIDIA A100 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: 66.0 tok/s decode · 2.9s TTFT (warm) · 165 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	60.7 tok/s	1741 ms	8K
Coding	A	Runs well	60.7 tok/s	3192 ms	8K
Agentic Coding	A	Runs well	60.7 tok/s	4642 ms	8K
Reasoning	A	Runs well	60.7 tok/s	3772 ms	8K
RAG	A	Runs well	60.7 tok/s	5803 ms	8K

Quantization options

How Falcon 40B Instruct (40B params) fits at each quantization level on NVIDIA A100 80GB (80.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	15.6 GB	Low	B62
Q3_K_S	3	19.6 GB	Low	B62
NVFP4	4

Get started

Copy-paste commands to run Falcon 40B Instruct on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
 --hf-repo "tiiuae/falcon-40b-instruct" \
 --hf-file "falcon-40b-instruct-Q5_K_M.gguf" \
 -c 4096 -ngl 99

Your hardware

More models your NVIDIA A100 80GB can run

Model	Params	Grade	Decode	Capabilities
👁 Mistral Devstral 2 123B Instruct	123B	A	17.6 tok/s
👁 Alibaba Qwen 3.5 122B A10B	122B	A

Frequently asked questions

See all results for NVIDIA A100 80GB See all hardware for Falcon 40B Instruct

URL: https://willitrunai.com/can-run/falcon-40b-instruct-on-a100-80gb

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