Measured model
Measured on a Mac Studio (M5 Max, 36GB)DeepSeek-R1-Distill-Qwen-32B
DeepSeek · Ollama name hf.co/unsloth/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
On a Mac Studio (M5 Max, 36GB), DeepSeek-R1-Distill-Qwen-32B answers a simple question in about 16.8 s, gets 81% of the Japanese knowledge questions right, 86% of the math problems, and uses 22.4GB of memory.
These numbers are from before the method changed on Oct 2, 2026 (see how it was measured).
Results
| Measure | Result | Among measured models | Note |
|---|---|---|---|
| Reply time | about 16.8 s | 29 of 30 | Until one simple common-sense question is answered (median of 50) |
| Knowledge (high school to university) | 81% | 9 of 30 | 200 questions, ±6, 7 cut off (counted wrong) |
| Math (word problems) | 86% | 7 of 30 | 100 questions, ±8 |
| Memory used | 22.4GB | 29 of 30 | |
| EN→JA translation | 31 pts | 16 of 28 | out of 100 (chrF), about 19.6 s a sentence |
| JA→EN translation | 57 pts | 10 of 28 | out of 100 (chrF), about 13.3 s a sentence |
"Among measured models" is the place among the 30 models measured on this site (lower is better for time and memory).
Try it on your Mac
- Install the Mac version of Ollama from ollama.com and start it.
- Type this in Terminal. The first time, the model downloads; then you can chat with it.
ollama run hf.co/unsloth/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
It used 22.4GB here. To use it comfortably alongside other apps, a Mac with 48GB of memory or more is a good guide (the model then takes about half the memory).
About the model
- Maker
- DeepSeek
- Size
- 32.8B parameters
- Quantization
- Q4_K_M
- Thinks before answering
- Yes
- Longest input at once
- 131,072 tokens
- Released (Hugging Face)
- Jan 20, 2025
- Generation speed
- 20.5 tok/s
- Start-up (loading)
- about 1.3 s
- Measured on
- Sep 30, 2026
- Ollama
- 0.34.3
- Hugging Face
- deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
- Series
- DeepSeek
Models of similar memory
- qwen3.6:35b-a3b (22.3GB of memory, knowledge 88%, reply about 8.8 s)
- NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 (22.7GB of memory, knowledge 77%, reply about 2 s)
- Ornith-1.5-35B-A3B (21.8GB of memory, knowledge 82%, reply about 1.9 s)
- Ornith-1.0-35B (21.6GB of memory, knowledge 88%, reply about 10.1 s)
- glm-4.7-flash:latest (19.5GB of memory, knowledge 77%, reply about 6.3 s)
Compare the main models on the text page. The series page lists every model measured.