Can NousResearch Hermes 4 14B run on NVIDIA T4 16GB?

YES — Runs Great

C52Usable

Estimated from fit model

NousResearch Hermes 4 14B needs ~13.0 GB VRAM. NVIDIA T4 16GB has 16.0 GB. With Q4_K_M quantization, expect ~24 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: 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) — 13.0 GB, 24.4 tok/s, Runs well

13.0 GB required16.0 GB available

81% VRAM used

Fit status

Runs well

Decode

24.4 tok/s

TTFT

7949 ms

Safe context

45K

Memory

13.0 GB / 16.0 GB

Memory breakdown

Weights8.5 GB

KV Cache1.6 GB

Runtime1.2 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsNousResearch Hermes 4 14B on NVIDIA T4 16GB
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: 24.4 tok/s decode · 7.9s TTFT (warm) · 61 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	C	Runs well	24.4 tok/s	4336 ms	45K
Coding	C	Runs well	24.4 tok/s	7949 ms	45K
Agentic Coding	C	Tight fit	24.4 tok/s	11562 ms	45K
Reasoning	C	Runs well	24.4 tok/s	9394 ms	45K
RAG	C	Tight fit	24.4 tok/s	14452 ms	45K

Quantization options

How NousResearch Hermes 4 14B (14B params) fits at each quantization level on NVIDIA T4 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	C49
Q3_K_S	3	6.9 GB	Low	C51
NVFP4	4

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

Upgrade options

Hardware that runs NousResearch Hermes 4 14B well

RTX 4000 Ada 20GBBudget pick

20 GB VRAM (+4)360 GB/s (+40)

Raises estimated decode speed by about 35%.32.9 tok/s decode

Raises estimated decode speed by about 35%.

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

~$1,250 MSRP

RTX 3090 24GBBest value

24 GB VRAM (+8)936 GB/s (+616)

Raises estimated decode speed by about 214%.76.7 tok/s decode

Raises estimated decode speed by about 214%.

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

~$1,499 MSRP

RTX PRO 4000 Blackwell 24GBNVIDIA upgrade

24 GB VRAM (+8)672 GB/s (+352)

Raises estimated decode speed by about 171%.66.1 tok/s decode

Raises estimated decode speed by about 171%.

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

~$1,599 MSRP

Frequently asked questions

Can NVIDIA T4 16GB run NousResearch Hermes 4 14B?

Yes, NVIDIA T4 16GB can run NousResearch Hermes 4 14B with a C grade (Runs well). Expected decode speed: 24.4 tok/s.

How much VRAM does NousResearch Hermes 4 14B need?

NousResearch Hermes 4 14B (14B parameters) requires approximately 13.0 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 T4 16GB?

On NVIDIA T4 16GB, NousResearch Hermes 4 14B achieves approximately 24.4 tokens per second decode speed with a time-to-first-token of 7949ms using Q4_K_M quantization.

Can NVIDIA T4 16GB run NousResearch Hermes 4 14B for coding?

For coding workloads, NousResearch Hermes 4 14B on NVIDIA T4 16GB receives a C grade with 24.4 tok/s and 45K context.

What context window can NousResearch Hermes 4 14B use on NVIDIA T4 16GB?

On NVIDIA T4 16GB, NousResearch Hermes 4 14B can safely use up to 45K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for NVIDIA T4 16GB See all hardware for NousResearch Hermes 4 14B

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