Hermes 3 (Llama 3.1 8B) on NVIDIA RTX 2000 Ada Generation Laptop GPU
Can the NVIDIA RTX 2000 Ada Generation Laptop GPU run Hermes 3 (Llama 3.1 8B)?
Yes, it runs well (tight fit)
Runs well (tight fit). At Q4_K_M it needs about 7.0 GB of 8.0 GB usable, with an estimated speed of 39.1 tok/s.
- Best quant
Q4_K_M- Generation speed
- 39.1 tok/s
- Prompt processing
- 1,300 tok/s
- First token (1K prompt)
- 0.8 s
- Largest safe context
- 15K
Best app to run it on the NVIDIA RTX 2000 Ada Generation Laptop GPU
On Windows
- One command with Ollama’s own build of this model.
- Serves an OpenAI-compatible API that other apps and coding tools can use.
ollama run hermes3:8b-llama3.1-q4_K_MOn Linux
- One command with Ollama’s own build of this model.
- Serves an OpenAI-compatible API that other apps and coding tools can use.
ollama run hermes3:8b-llama3.1-q4_K_MDownload Hermes 3 (Llama 3.1 8B)
Recommended for the NVIDIA RTX 2000 Ada Generation Laptop GPU: Q4_K_M. Every other quantization has its own download link in the table below.
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run hermes3:8b-llama3.1-q4_K_MQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q4_K_M file (opens in a new tab)
huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B-GGUF (opens in a new tab)
ollama run hf.co/NousResearch/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_MOriginal weights · Hugging Face
Full-precision files from Nous Research, for fine-tuning, vLLM, Transformers.
huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B (opens in a new tab)
How it’s rated
Match score
To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.
| Model quality | 20.5 / 45 | |
|---|---|---|
| Memory fit | 24.0 / 25 | |
| Speed | 14.8 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 74.4 / 100 |
Every quantization on the NVIDIA RTX 2000 Ada Generation Laptop GPU
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 5.3 GB | 8.0 GB | 64.3 tok/s | Runs great | 33Basic quality (D) · 33 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. | |
Q3_K_M | 6.0 GB | 8.0 GB | 50.6 tok/s | Runs great | 40Fair quality (C) · 40 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. | |
Q4_K_M | 7.0 GB | 8.0 GB | 39.1 tok/s | Runs welltight fit | 45Fair quality (C) · 45 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 7.8 GB | 8.0 GB | 32.3 tok/s | Runs welltight fit | 46Fair quality (C) · 46 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 8.7 GB | 8.0 GB | 21.1 tok/s | Runs welloffloads to RAM | 47Fair quality (C) · 47 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 57/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 10.6 GB | 8.0 GB | 10.7 tok/s | Slowheavy RAM offload | 48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 48/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 18.1 GB | 8.0 GB | 3.3 tok/s | Slowheavy RAM offload | 48Fair quality (C) · 48 of 100: how capable the model is at F16, whatever it runs on. Match score 44/100 (quality, fit, speed and memory use) sets the ranking. | Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5080
-
47Fair quality (C) · 47 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
Quick answers
How much memory does Hermes 3 (Llama 3.1 8B) need on the NVIDIA RTX 2000 Ada Generation Laptop GPU 8GB?
At Q4_K_M it needs about 7.0 GB. The NVIDIA RTX 2000 Ada Generation Laptop GPU 8GB has 8.0 GB usable.
How fast is Hermes 3 (Llama 3.1 8B) on the NVIDIA RTX 2000 Ada Generation Laptop GPU 8GB?
About 39.1 tok/s at Q4_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Hermes 3 (Llama 3.1 8B) should I use on the NVIDIA RTX 2000 Ada Generation Laptop GPU 8GB?
Q4_K_M. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.