SmolLM 135M Instruct on AMD Ryzen AI Max+ 395 (96 GB)
Can the AMD Ryzen AI Max+ 395 (96 GB) run SmolLM 135M Instruct?
Yes, it runs great
Runs great. At F16 it needs about 6.7 GB of 72.0 GB usable, with an estimated speed of 488 tok/s.
- Best quant
F16- Generation speed
- 488 tok/s
- Prompt processing
- 283,292 tok/s
- First token (1K prompt)
- 0.3 s
- Largest safe context
- 2K
Best app to run it on the AMD Ryzen AI Max+ 395 (96 GB)
On Windows
- Built for Ryzen AI and Strix Halo, including NPU + iGPU modes on Windows.
lemonade pull QuantFactory/SmolLM-135M-Instruct-GGUF:F16Download SmolLM 135M Instruct
Recommended for the AMD Ryzen AI Max+ 395 (96 GB): F16. 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 smollm:135m-instruct-v0.2-fp16Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
huggingface.co/QuantFactory/SmolLM-135M-Instruct-GGUF (opens in a new tab)
ollama run hf.co/QuantFactory/SmolLM-135M-Instruct-GGUFOriginal weights · Hugging Face
Full-precision files from Hugging Face, for fine-tuning, vLLM, Transformers.
huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct (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 | 0.9 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 2.1 / 15 | |
| Match score | 43.0 / 100 |
Every quantization on the AMD Ryzen AI Max+ 395 (96 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 6.5 GB | 72.0 GB | 3,419 tok/s | Runs great | 1Basic quality (D) · 1 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q3_K_M | 6.5 GB | 72.0 GB | 2,691 tok/s | Runs great | 1Basic quality (D) · 1 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4_K_M | 6.5 GB | 72.0 GB | 2,082 tok/s | Runs great | 1Basic quality (D) · 1 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 6.5 GB | 72.0 GB | 1,720 tok/s | Runs great | 1Basic quality (D) · 1 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 6.5 GB | 72.0 GB | 1,444 tok/s | Runs great | 1Basic quality (D) · 1 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 6.5 GB | 72.0 GB | 1,060 tok/s | Runs great | 2Basic quality (D) · 2 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 6.7 GB | 72.0 GB | 488 tok/s | Runs great | 2Basic quality (D) · 2 of 100: how capable the model is at F16, whatever it runs on. Match score 43/100 (quality, fit, speed and memory use) sets the ranking. | Original weights (opens in a new tab) |
Memory figures assume 2K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
-
2Basic quality (D) · 2 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.
Apple M1 (16 GB)
-
2Basic quality (D) · 2 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.
Apple M4 (16 GB)
-
2Basic quality (D) · 2 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.
NVIDIA GeForce RTX 4060
-
2Basic quality (D) · 2 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.
Apple M4 (24 GB)
-
2Basic quality (D) · 2 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.
Apple M4 Pro (24 GB)
-
2Basic quality (D) · 2 of 100: how capable the model is at F16, whatever it runs on. Match score 43/100 (quality, fit, speed and memory use) sets the ranking.
Intel Arc B580
Quick answers
How much memory does SmolLM 135M Instruct need on the AMD Ryzen AI Max+ 395 96GB?
At F16 it needs about 6.7 GB. The AMD Ryzen AI Max+ 395 96GB has 72.0 GB usable.
How fast is SmolLM 135M Instruct on the AMD Ryzen AI Max+ 395 96GB?
About 488 tok/s at F16, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of SmolLM 135M Instruct should I use on the AMD Ryzen AI Max+ 395 96GB?
F16. 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.