d1 3B on Intel Core Ultra 5 225H NAS (32 GB)
Can the Intel Core Ultra 5 225H NAS (32 GB) run d1 3B?
Yes, it runs well
Runs well. At Q6_K it needs about 4.7 GB of 18.2 GB usable and makes one decision in about 183 ms.
- Best quant
Q6_K- Time per decision
- 183 ms
- Decisions per second
- 5.5/s
- Input assumed
- 256 tokens
- Returns
- Probability or score
Download d1 3B
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run d1:3bQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
huggingface.co/LiquidAI/d1-3B-GGUF (opens in a new tab)
ollama run hf.co/LiquidAI/d1-3B-GGUFOriginal weights · Hugging Face
Full-precision files from Liquid AI, for Transformers, Sentence Transformers, Text Embeddings Inference, Infinity or vLLM.
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.
| Precision | 36.5 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 11.1 / 15 | |
| Clarity | 15.0 / 15 | |
| Match score | 87.6 / 100 |
Every quantization on the Intel Core Ultra 5 225H NAS (32 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q4_K_M | 4.0 GB | 18.2 GB | 172 ms | Runs well | 77Great quality (A) · 77 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 4.3 GB | 18.2 GB | 178 ms | Runs well | 79Great quality (A) · 79 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q6_K | 4.7 GB | 18.2 GB | 183 ms | Runs well | 81Great quality (A) · 81 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q8_0 | 5.4 GB | 18.2 GB | 197 ms | Runs well | 82Great quality (A) · 82 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 8.3 GB | 18.2 GB | 255 ms | Runs well | 82Great quality (A) · 82 of 100: how capable the model is at F16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Times are for one request with a 256-token input and about 1 tokens written. Batching servers process many requests at once.
Other hardware that runs it
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82Great quality (A) · 82 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
82Great quality (A) · 82 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
82Great quality (A) · 82 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.
AMD Ryzen AI Max+ 395 (128 GB)
-
82Great quality (A) · 82 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.
Apple M2 Ultra (192 GB)
-
82Great quality (A) · 82 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.
Apple M3 Ultra (256 GB)
-
82Great quality (A) · 82 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.
Apple M3 Ultra (512 GB)
Quick answers
How much memory does d1 3B need on the Intel Core Ultra 5 225H NAS 32GB?
At Q6_K it needs about 4.7 GB. The Intel Core Ultra 5 225H NAS 32GB has 18.2 GB usable.
How fast is d1 3B on the Intel Core Ultra 5 225H NAS 32GB?
It makes one decision in about 183 ms at Q6_K, an estimate from the hardware and the size of the model.
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.