Nemotron Mini 4B Instruct on Intel Arc B580
Can the Intel Arc B580 run Nemotron Mini 4B Instruct?
Yes, it runs well
Runs well. At Q8_0 it needs about 6.2 GB of 12.0 GB usable, with an estimated speed of 52.0 tok/s.
- Best quant
Q8_0- Generation speed
- 52.0 tok/s
- Prompt processing
- 3,584 tok/s
- First token (1K prompt)
- 0.3 s
- Largest safe context
- 4K
Download Nemotron Mini 4B Instruct
Recommended for the Intel Arc B580: Q8_0. 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 nemotron-mini:4b-instruct-q8_0Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q8_0 file (opens in a new tab)
huggingface.co/bartowski/Nemotron-Mini-4B-Instruct-GGUF (opens in a new tab)
ollama run hf.co/bartowski/Nemotron-Mini-4B-Instruct-GGUF:Q8_0Original weights · Hugging Face
Full-precision files from NVIDIA, for fine-tuning, vLLM, Transformers.
huggingface.co/nvidia/Nemotron-Mini-4B-Instruct (opens in a new tab)
How the B grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 9.9 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 11.9 / 15 | |
| Total | 61.8 / 100 | 61 ptsGood (B) · 61 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.9/15 |
Every quantization on the Intel Arc B580
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 3.4 GB | 12.0 GB | 168 tok/s | Runs well | 53 ptsUsable (C) · 53 of 100 points: Model quality 6.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.6/15 | |
Q3_K_M | 3.8 GB | 12.0 GB | 132 tok/s | Runs well | 55 ptsUsable (C) · 55 of 100 points: Model quality 8.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.3/15 | GGUF (Q3_K_L) (opens in a new tab) |
Q4_K_M | 4.3 GB | 12.0 GB | 102 tok/s | Runs well | 57 ptsUsable (C) · 57 of 100 points: Model quality 9.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.3/15 | GGUF (opens in a new tab) |
Q5_K_M | 4.7 GB | 12.0 GB | 84.3 tok/s | Runs well | 58 ptsGood (B) · 58 of 100 points: Model quality 9.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.1/15 | GGUF (opens in a new tab) |
Q6_K | 5.2 GB | 12.0 GB | 70.8 tok/s | Runs well | 59 ptsGood (B) · 59 of 100 points: Model quality 9.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.9/15 | GGUF (opens in a new tab) |
Q8_0 | 6.2 GB | 12.0 GB | 52.0 tok/s | Runs well | 61 ptsGood (B) · 61 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.9/15 | GGUF (opens in a new tab) |
F16 | 10.1 GB | 12.0 GB | 23.9 tok/s | Runs well | 61 ptsGood (B) · 61 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 11.6/15, Memory use 15.0/15 | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 4K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
- 64 ptsGood (B) · 64 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4060
- 64 ptsGood (B) · 64 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 NVIDIA GeForce RTX 4070 Ti SUPER
- 64 ptsGood (B) · 64 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 NVIDIA GeForce RTX 4080 SUPER
- 64 ptsGood (B) · 64 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 NVIDIA GeForce RTX 5070 Ti
- 64 ptsGood (B) · 64 of 100 points: Model quality 9.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 NVIDIA GeForce RTX 5080
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.