Hunyuan 7B Instruct on Intel Core i3-1215U / i3-1315U NAS (8 GB)
Can the Intel Core i3-1215U / i3-1315U NAS (8 GB) run Hunyuan 7B Instruct?
Yes, but slowly (tight fit)
Slow (tight fit). At Q2_K it needs about 5.1 GB of 5.2 GB usable, with an estimated speed of 8.6 tok/s.
- Best quant
Q2_K- Generation speed
- 8.6 tok/s
- Prompt processing
- 20.0 tok/s
- First token (1K prompt)
- 51.2 s
- Largest safe context
- 8K
Best app to run it on the Intel Core i3-1215U / i3-1315U NAS (8 GB)
Download Hunyuan 7B Instruct
Recommended for the Intel Core i3-1215U / i3-1315U NAS (8 GB): Q2_K. Every other quantization has its own download link in the table below.
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q2_K file (opens in a new tab)
huggingface.co/bartowski/tencent_Hunyuan-7B-Instruct-GGUF (opens in a new tab)
ollama run hf.co/bartowski/tencent_Hunyuan-7B-Instruct-GGUF:Q2_KOriginal weights · Hugging Face
Full-precision files from Tencent, for fine-tuning, vLLM, Transformers.
huggingface.co/tencent/Hunyuan-7B-Instruct (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from Tencent. The weights themselves download from Hugging Face.
github.com/Tencent-Hunyuan/Hunyuan-7B (opens in a new tab)
git clone https://github.com/Tencent-Hunyuan/Hunyuan-7BHow 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 | 16.4 / 45 | |
|---|---|---|
| Memory fit | 24.0 / 25 | |
| Speed | 7.0 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 62.3 / 100 |
Every quantization on the Intel Core i3-1215U / i3-1315U NAS (8 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 5.1 GB | 5.2 GB | 8.6 tok/s | Slowtight fit | 36Basic quality (D) · 36 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q3_K_M | 5.8 GB | 5.2 GB | 5.8 tok/s | Slowfar over memory limit | 43Fair quality (C) · 43 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 44/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4_K_M | 6.7 GB | 5.2 GB | — | Won't run | 49Fair quality (C) · 49 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 7.4 GB | 5.2 GB | — | Won't run | 50Fair quality (C) · 50 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 8.2 GB | 5.2 GB | — | Won't run | 51Fair quality (C) · 51 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 10.0 GB | 5.2 GB | — | Won't run | 52Fair quality (C) · 52 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 7/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 17.1 GB | 5.2 GB | — | Won't run | 52Fair quality (C) · 52 of 100: how capable the model is at F16, whatever it runs on. Match score 7/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) 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
-
52Fair quality (C) · 52 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
52Fair quality (C) · 52 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
52Fair quality (C) · 52 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
52Fair quality (C) · 52 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
-
52Fair quality (C) · 52 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5080
-
51Fair quality (C) · 51 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3060 12GB
Quick answers
How much memory does Hunyuan 7B Instruct need on the Intel Core i3-1215U / i3-1315U NAS 8GB?
At Q2_K it needs about 5.1 GB. The Intel Core i3-1215U / i3-1315U NAS 8GB has 5.2 GB usable.
How fast is Hunyuan 7B Instruct on the Intel Core i3-1215U / i3-1315U NAS 8GB?
About 8.6 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Hunyuan 7B Instruct should I use on the Intel Core i3-1215U / i3-1315U NAS 8GB?
Q2_K. 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.