Sarvam 30B on Intel Atom C3758 NAS (32 GB)
Can the Intel Atom C3758 NAS (32 GB) run Sarvam 30B?
Yes, it runs well
Runs well. At Q3_K_M it needs about 18.6 GB of 26.2 GB usable, with an estimated speed of 11.9 tok/s.
- Best quant
Q3_K_M- Generation speed
- 11.9 tok/s
- Prompt processing
- 17.5 tok/s
- First token (1K prompt)
- 58.5 s
- Largest safe context
- 128K
Best app to run it on the Intel Atom C3758 NAS (32 GB)
Download Sarvam 30B
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
huggingface.co/sarvamai/sarvam-30b-gguf (opens in a new tab)
ollama run hf.co/sarvamai/sarvam-30b-ggufOriginal weights · Hugging Face
Full-precision files from Sarvam AI, for fine-tuning, vLLM, Transformers.
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 | 26.5 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 8.2 / 15 | |
| Memory use | 15.0 / 15 | |
| Match score | 74.6 / 100 |
Every quantization on the Intel Atom C3758 NAS (32 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 15.7 GB | 26.2 GB | 14.9 tok/s | Runs well | 49Fair quality (C) · 49 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. | GGUF files (opens in a new tab) |
Q3_K_M | 18.6 GB | 26.2 GB | 11.9 tok/s | Runs well | 58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q4_K_M | 22.5 GB | 26.2 GB | 9.3 tok/s | Slowtight fit | 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. | GGUF · part 1 of 6 (opens in a new tab) |
Q5_K_M | 25.7 GB | 26.2 GB | 7.7 tok/s | Slowtight fit | 67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q6_K | 29.2 GB | 26.2 GB | 5.5 tok/s | Slowfar over memory limit | 69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
Q8_0 | 36.9 GB | 26.2 GB | — | Won't run | 70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. | GGUF files (opens in a new tab) |
F16 | 67.2 GB | 26.2 GB | — | Won't run | 70Great quality (A) · 70 of 100: how capable the model is at F16, whatever it runs on. Match score 9/100 (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
-
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
Apple M1 Max (64 GB)
-
70Great quality (A) · 70 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.
Apple M4 Max (128 GB)
-
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 Max (64 GB)
-
70Great quality (A) · 70 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.
NVIDIA RTX PRO 6000 Blackwell
-
69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.
Apple M4 Pro (48 GB)
-
67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5090
Quick answers
How much memory does Sarvam 30B need on the Intel Atom C3758 NAS 32GB?
At Q3_K_M it needs about 18.6 GB. The Intel Atom C3758 NAS 32GB has 26.2 GB usable.
How fast is Sarvam 30B on the Intel Atom C3758 NAS 32GB?
About 11.9 tok/s at Q3_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of Sarvam 30B should I use on the Intel Atom C3758 NAS 32GB?
Q3_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.