Can Nous Hermes 2 Mistral 7B DPO run on RTX 4500 Ada 24GB?

YES — Runs Great

C49Usable

Estimated from fit model

Nous Hermes 2 Mistral 7B DPO needs ~8.7 GB VRAM. RTX 4500 Ada 24GB has 24.0 GB. With Q4_K_M quantization, expect ~80 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) — 8.7 GB, 79.9 tok/s, Runs well

8.7 GB required24.0 GB available

36% VRAM used

Fit status

Runs well

Decode

79.9 tok/s

TTFT

2422 ms

Safe context

315K

Memory

8.7 GB / 24.0 GB

Memory breakdown

Weights4.3 GB

KV Cache0.8 GB

Runtime1.2 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsNous Hermes 2 Mistral 7B DPO on RTX 4500 Ada 24GB
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: 79.9 tok/s decode · 2.4s TTFT (warm) · 200 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	C	Runs well	79.9 tok/s	1321 ms	315K
Coding	C	Runs well	79.9 tok/s	2422 ms	315K
Agentic Coding	C	Runs well	79.9 tok/s	3523 ms	315K
Reasoning	C	Runs well	79.9 tok/s	2863 ms	315K
RAG	C	Runs well	79.9 tok/s	4404 ms	315K

Quantization options

How Nous Hermes 2 Mistral 7B DPO (7B params) fits at each quantization level on RTX 4500 Ada 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	C44
Q3_K_S	3	3.4 GB	Low	C45
NVFP4	4	3.9 GB	Medium	C45
Q4_K_M	4	4.3 GB	Medium	C45
Q5_K_M	5	5.0 GB	High	C45
Q6_K	6	5.7 GB	High	C46
Q8_0	8	7.5 GB	Very High	C47
F16Best for your GPU	16	14.3 GB	Maximum	C50

Get started

Copy-paste commands to run Nous Hermes 2 Mistral 7B DPO on your machine.

Run

lms load hf-nousresearch--nous-hermes-2-mistral-7b-dpo-gguf && lms server start

Opciones de mejora

Hardware que ejecuta bien Nous Hermes 2 Mistral 7B DPO

MacBook Pro M4 Max 36GBOpción económica

36 GB Unified (+12)

Este setup está bastante equilibrado para este modelo.65.9 tok/s decodificación

~$2,499 MSRP

Frequently asked questions

Can RTX 4500 Ada 24GB run Nous Hermes 2 Mistral 7B DPO?

Yes, RTX 4500 Ada 24GB can run Nous Hermes 2 Mistral 7B DPO with a C grade (Runs well). Expected decode speed: 79.9 tok/s.

How much VRAM does Nous Hermes 2 Mistral 7B DPO need?

Nous Hermes 2 Mistral 7B DPO (7B parameters) requires approximately 8.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Nous Hermes 2 Mistral 7B DPO?

The recommended quantization for Nous Hermes 2 Mistral 7B DPO is Q4_K_M, which balances quality and memory efficiency.

What speed will Nous Hermes 2 Mistral 7B DPO run at on RTX 4500 Ada 24GB?

On RTX 4500 Ada 24GB, Nous Hermes 2 Mistral 7B DPO achieves approximately 79.9 tokens per second decode speed with a time-to-first-token of 2422ms using Q4_K_M quantization.

Can RTX 4500 Ada 24GB run Nous Hermes 2 Mistral 7B DPO for coding?

For coding workloads, Nous Hermes 2 Mistral 7B DPO on RTX 4500 Ada 24GB receives a C grade with 79.9 tok/s and 315K context.

What context window can Nous Hermes 2 Mistral 7B DPO use on RTX 4500 Ada 24GB?

On RTX 4500 Ada 24GB, Nous Hermes 2 Mistral 7B DPO can safely use up to 315K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for RTX 4500 Ada 24GB See all hardware for Nous Hermes 2 Mistral 7B DPO

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