Will It Run AI

Can NousResearch Hermes 4 14B run on RTX 5060 Ti 16GB?

YES — Runs Great

C53Usable
Estimated from fit model

NousResearch Hermes 4 14B needs ~13.0 GB VRAM. RTX 5060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~33 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: Balanced
Share:

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, 32.5 tok/s, Runs well
13.0 GB required16.0 GB available
81% VRAM used

Fit status

Runs well

Decode

32.5 tok/s

TTFT

5952 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 RTX 5060 Ti 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: 32.5 tok/s decode · 6.0s TTFT (warm) · 81 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 well32.5 tok/s3247 ms45K
CodingCRuns well32.5 tok/s5952 ms45K
Agentic CodingCTight fit32.5 tok/s8658 ms45K
ReasoningCRuns well32.5 tok/s7035 ms45K
RAGCTight fit32.5 tok/s10823 ms45K

Quantization options

How NousResearch Hermes 4 14B (14B params) fits at each quantization level on RTX 5060 Ti 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowC49
Q3_K_S
3
6.9 GB
LowC51
NVFP4
4
7.8 GB
MediumC51
Q4_K_M
4
8.5 GB
MediumC51
Q5_K_M
5
10.1 GB
HighC51
Q6_KBest for your GPU
6
11.5 GB
HighC51
Q8_0
8
15.0 GB
Very HighF0
F16
16
28.7 GB
MaximumF0

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

Opciones de mejora

Hardware que ejecuta bien NousResearch Hermes 4 14B

NVIDIARTX 3090 24GBOpción económica
24 GB VRAM (+8)936 GB/s (+488)
C
Sube la velocidad estimada de decodificación alrededor de un 136%.76.7 tok/s decodificación

Sube la velocidad estimada de decodificación alrededor de un 136%.

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$1,499 MSRP

NVIDIARTX 4090 24GBMejor relación calidad-precio
24 GB VRAM (+8)1008 GB/s (+560)
C
Sube la velocidad estimada de decodificación alrededor de un 176%.89.7 tok/s decodificación

Sube la velocidad estimada de decodificación alrededor de un 176%.

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$1,599 MSRP

NVIDIARTX 3090 Ti 24GBMejora NVIDIA
24 GB VRAM (+8)1008 GB/s (+560)
C
Sube la velocidad estimada de decodificación alrededor de un 158%.83.8 tok/s decodificación

Sube la velocidad estimada de decodificación alrededor de un 158%.

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$1,999 MSRP

Frequently asked questions

Can RTX 5060 Ti 16GB run NousResearch Hermes 4 14B?

Yes, RTX 5060 Ti 16GB can run NousResearch Hermes 4 14B with a C grade (Runs well). Expected decode speed: 32.5 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 RTX 5060 Ti 16GB?

On RTX 5060 Ti 16GB, NousResearch Hermes 4 14B achieves approximately 32.5 tokens per second decode speed with a time-to-first-token of 5952ms using Q4_K_M quantization.

Can RTX 5060 Ti 16GB run NousResearch Hermes 4 14B for coding?

For coding workloads, NousResearch Hermes 4 14B on RTX 5060 Ti 16GB receives a C grade with 32.5 tok/s and 45K context.

What context window can NousResearch Hermes 4 14B use on RTX 5060 Ti 16GB?

On RTX 5060 Ti 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 RTX 5060 Ti 16GBSee all hardware for NousResearch Hermes 4 14B
Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/hf-bartowski--nousresearch-hermes-4-14b-gguf-on-rtx-5060-ti-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: