Will It Run AI

Can NousResearch Hermes 4 14B run on NVIDIA A16 64GB?

YES — Runs Great

C46Usable
Estimated from fit model

NousResearch Hermes 4 14B needs ~17.8 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~55 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: 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) — 17.8 GB, 54.8 tok/s, Runs well
17.8 GB required64.0 GB available
28% VRAM used

Fit status

Runs well

Decode

54.8 tok/s

TTFT

3533 ms

Safe context

467K

Memory

17.8 GB / 64.0 GB

Memory breakdown

Weights8.5 GB
KV Cache1.6 GB
Runtime1.2 GB
Headroom6.4 GB

See how fast it feels

See how fast it feelsNousResearch Hermes 4 14B on NVIDIA A16 64GB
1st promptCold start — includes initialization
>What is local AI inference?
Local AI inference means running an AI language model directly on your own hardware — your laptop, desktop, or server — instead of sending requests to a remote cloud API. When you run inference locally the model weights are loaded into your GPU or unified memory. Each token you generate requires reading those weights from memory, so memory bandwidth is the main bottleneck for decode speed. Key benefits of running locally: - Full privacy: your prompts never leave your machine - No per-token cost or rate limits - Works offline once the model is downloaded - Latency depends only on your hardware
2nd promptWarm — model ready, no init overhead
>How much VRAM do I need?
It depends on the model size and quantization level. A rough rule of thumb: Model size Q4 (4-bit) Q8 (8-bit) FP16 7B params ~4.3 GB ~7.5 GB ~14 GB 13B params ~7.9 GB ~13.9 GB ~26 GB 70B params ~42.7 GB ~74.9 GB ~140 GB Most people use 4-bit quantization (Q4_K_M) which gives 90-95% of full quality at a fraction of the memory. A 24 GB GPU can comfortably run most 7B-13B models.
Estimated: 54.8 tok/s decode · 3.5s TTFT (warm) · 137 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
ChatCRuns well54.8 tok/s1927 ms467K
CodingCRuns well54.8 tok/s3533 ms467K
Agentic CodingCRuns well54.8 tok/s5139 ms467K
ReasoningCRuns well54.8 tok/s4175 ms467K
RAGCRuns well54.8 tok/s6423 ms467K

Quantization options

How NousResearch Hermes 4 14B (14B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowC40
Q3_K_S
3
6.9 GB
LowC41
NVFP4
4
7.8 GB
MediumC41
Q4_K_M
4
8.5 GB
MediumC41
Q5_K_M
5
10.1 GB
HighC41
Q6_K
6
11.5 GB
HighC41
Q8_0
8
15.0 GB
Very HighC42
F16Best for your GPU
16
28.7 GB
MaximumC45

Get started

Copy-paste commands to run NousResearch Hermes 4 14B on your machine.

Run

lms load hf-bartowski--nousresearch-hermes-4-14b-gguf && lms server start

升级选项

能流畅运行 NousResearch Hermes 4 14B 的硬件

NVIDIARTX PRO 6000 Blackwell Workstation Edition 96GB经济之选
96 GB VRAM (+32)1792 GB/s (+1192)
C
Raises estimated decode speed by about 222%.176.3 tok/s 解码

Raises estimated decode speed by about 222%.

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

~$9,999 MSRP

NVIDIARTX PRO 6000 Blackwell Server Edition 96GB最佳性价比
96 GB VRAM (+32)1597 GB/s (+997)
C
Raises estimated decode speed by about 187%.157.1 tok/s 解码

Raises estimated decode speed by about 187%.

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

~$9,999 MSRP

NVIDIANVIDIA H20 96GBNVIDIA 升级
96 GB VRAM (+32)4000 GB/s (+3400)
C
Raises estimated decode speed by about 258%.196 tok/s 解码

Raises estimated decode speed by about 258%.

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

~$12,000 MSRP

Frequently asked questions

Can NVIDIA A16 64GB run NousResearch Hermes 4 14B?

Yes, NVIDIA A16 64GB can run NousResearch Hermes 4 14B with a C grade (Runs well). Expected decode speed: 54.8 tok/s.

How much VRAM does NousResearch Hermes 4 14B need?

NousResearch Hermes 4 14B (14B parameters) requires approximately 17.8 GB of memory with Q4_K_M quantization.

What is the best quantization for NousResearch Hermes 4 14B?

The recommended quantization for NousResearch Hermes 4 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will NousResearch Hermes 4 14B run at on NVIDIA A16 64GB?

On NVIDIA A16 64GB, NousResearch Hermes 4 14B achieves approximately 54.8 tokens per second decode speed with a time-to-first-token of 3533ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run NousResearch Hermes 4 14B for coding?

For coding workloads, NousResearch Hermes 4 14B on NVIDIA A16 64GB receives a C grade with 54.8 tok/s and 467K context.

What context window can NousResearch Hermes 4 14B use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, NousResearch Hermes 4 14B can safely use up to 467K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for NVIDIA A16 64GBSee all hardware for NousResearch Hermes 4 14B
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