willitrun·ai

Can Nous Hermes 1.0 run on NVIDIA A100 80GB?

YES — Runs Great

B70Good
Estimated from fit model

Nous Hermes 1.0 needs ~26.9 GB VRAM. NVIDIA A100 80GB has 80.0 GB. With Q4_K_M quantization, expect ~126 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) 26.9 GB, 126.0 tok/s, Runs well
26.9 GB required80.0 GB available
34% VRAM used

Fit status

Runs well

Decode

126.0 tok/s

TTFT

1537 ms

Safe context

16K

Memory

26.9 GB / 80.0 GB

Memory breakdown

Weights5.5 GB
KV Cache12.2 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsNous Hermes 1.0 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: 126.0 tok/s decode · 1.5s TTFT (warm) · 315 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 well126.0 tok/s838 ms16K
CodingBRuns well126.0 tok/s1537 ms16K
Agentic CodingARuns well126.0 tok/s2235 ms16K
ReasoningBRuns well126.0 tok/s1816 ms16K
RAGARuns well126.0 tok/s2794 ms16K

Inference speed

Nous Hermes 1.0 inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Nous Hermes 1.0 at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~126 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / MacMemoryQuantSpeed (tok/s)Fits?
NVIDIARTX 5090 32GB
32 GBQ4_K_M126.0Fits
NVIDIARTX 4090 24GB
24 GBQ4_K_M126.0Tight
RX 7900 XTX 24GB
24 GBQ4_K_M125.9Tight
NVIDIARTX 3090 24GB
24 GBQ4_K_M119.3Tight
Mac Studio M3 Ultra 256GB
256 GBQ4_K_M101.4Fits
Mac Studio M2 Ultra 128GB
128 GBQ4_K_M84.5Fits
Mac Studio M1 Ultra 128GB
128 GBQ4_K_M80.1Fits
MacBook Pro M4 Max 128GB
128 GBQ4_K_M68.3Fits
MacBook Pro M4 Max 64GB
64 GBQ4_K_M68.3Fits
NVIDIARTX 4080 Super 16GB
16 GBQ4_K_M49.5Too big
MacBook Pro M3 Max 64GB
64 GBQ4_K_M43.7Fits
MacBook Pro M1 Max 64GB
64 GBQ4_K_M40.1Fits
MacBook Pro M4 Pro 48GB
48 GBQ4_K_M35.2Fits
NVIDIARTX 4070 12GB
12 GBQ4_K_M17.4Too big
NVIDIARTX 3060 12GB
12 GBQ4_K_M11.0Too big
NVIDIARTX 4060 8GB
8 GBQ4_K_M5.4Too big

Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.

Quantization options

How Nous Hermes 1.0 (9B params) fits at each quantization level on NVIDIA A100 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.5 GB
LowB60
Q3_K_S
3
4.4 GB
LowB60
NVFP4
4
5.0 GB
MediumB60
Q4_K_M
4
5.5 GB
MediumB60
Q5_K_M
5
6.5 GB
HighB60
Q6_K
6
7.4 GB
HighB61
Q8_0
8
9.6 GB
Very HighB61
F16Best for your GPU
16
18.5 GB
MaximumB62

Get started

Copy-paste commands to run Nous Hermes 1.0 on your machine.

Run

lms load Nous-Hermes-1.0 && lms server start

Opciones de mejora

Hardware que ejecuta bien Nous Hermes 1.0

Frequently asked questions

Can NVIDIA A100 80GB run Nous Hermes 1.0?

Yes, NVIDIA A100 80GB can run Nous Hermes 1.0 with a B grade (Runs well). Expected decode speed: 126.0 tok/s.

How much VRAM does Nous Hermes 1.0 need?

Nous Hermes 1.0 (9B parameters) requires approximately 26.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Nous Hermes 1.0?

The recommended quantization for Nous Hermes 1.0 is Q4_K_M, which balances quality and memory efficiency.

What speed will Nous Hermes 1.0 run at on NVIDIA A100 80GB?

On NVIDIA A100 80GB, Nous Hermes 1.0 achieves approximately 126.0 tokens per second decode speed with a time-to-first-token of 1537ms using Q4_K_M quantization.

Can NVIDIA A100 80GB run Nous Hermes 1.0 for coding?

For coding workloads, Nous Hermes 1.0 on NVIDIA A100 80GB receives a B grade with 126.0 tok/s and 16K context.

What context window can Nous Hermes 1.0 use on NVIDIA A100 80GB?

On NVIDIA A100 80GB, Nous Hermes 1.0 can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.

See all results for NVIDIA A100 80GBSee all hardware for Nous Hermes 1.0
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<iframe src="https://willitrunai.com/embed/nous-hermes-1.0-on-a100-80gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

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