Can my computer run DeepSeek R1 Distill 1.5B?
Lightweight reasoning model distilled from DeepSeek R1. DeepSeek R1 Distill 1.5B needs about 1.6 GB of memory. It runs comfortably on Macs with 8 GB or more, and on PCs with 8 GB of RAM or more, even without a graphics card.
DeepSeek R1 Distill 1.5B on common computers
Graded with Toskar 1.12.1's own estimate: the model file plus working memory at an 8K context.
| Computer | Fit | What to expect |
|---|---|---|
| Mac, 8 GB | Excellent fit | Plenty of memory to spare. |
| Mac, 16 GB | Excellent fit | Plenty of memory to spare. |
| Mac, 24 GB | Excellent fit | Plenty of memory to spare. |
| Mac, 32 GB | Excellent fit | Plenty of memory to spare. |
| Mac, 48 GB | Excellent fit | Plenty of memory to spare. |
| Mac, 64 GB | Excellent fit | Plenty of memory to spare. |
| Mac, 128 GB | Excellent fit | Plenty of memory to spare. |
| PC, 8 GB, no graphics card | Excellent fit | Plenty of memory to spare. |
| PC, 16 GB, no graphics card | Excellent fit | Plenty of memory to spare. |
| PC, 32 GB, no graphics card | Excellent fit | Plenty of memory to spare. |
| PC, 16 GB + 8 GB graphics card | Excellent fit | Plenty of memory to spare. Good GPU fit. |
| PC, 32 GB + 12 GB graphics card | Excellent fit | Plenty of memory to spare. Good GPU fit. |
| PC, 32 GB + 16 GB graphics card | Excellent fit | Plenty of memory to spare. Good GPU fit. |
| PC, 64 GB + 24 GB graphics card | Excellent fit | Plenty of memory to spare. Good GPU fit. |
About DeepSeek R1 Distill 1.5B
- Memory needed
- ≈ 1.6 GB
- Download size
- 1.0 GB
- Parameters
- 1.5B
- Quantization
- Q4_K_M
- Longest conversation
- 32K tokens
- License
- MIT
Good at
- Chat and writing
- Step-by-step reasoning
Similar models to compare
- Phi 3.5 Mini≈ 3.0 GB
Compact Microsoft model good for reasoning and light coding.
- DeepSeek R1 Distill 7B≈ 5.3 GB
Stronger reasoning for analysis and multi-step problems.
- Qwen 2.5 14B≈ 10.2 GB
Largest curated quality pick when your machine has headroom.
- Muse Glimmer 30B≈ 17.1 GB
Meta's large model that sees pictures, codes, and reasons well; for 32 GB Macs or 24 GB graphics cards.
Questions
- How much memory does DeepSeek R1 Distill 1.5B need?
- About 1.6 GB with Toskar's default 8K context: the 1.0 GB model file plus room for the conversation. After it has run once, Toskar measures what it really uses on your computer.
- Can DeepSeek R1 Distill 1.5B run on a Mac with 8 GB?
- Yes. DeepSeek R1 Distill 1.5B runs comfortably on a Mac with 8 GB, using about 1.6 GB.
- Can DeepSeek R1 Distill 1.5B run without a graphics card?
- Yes. DeepSeek R1 Distill 1.5B runs comfortably on a PC with 16 GB of RAM and no graphics card, using about 1.6 GB. Without a graphics card it runs on the processor, so it answers more slowly than with one. On a Mac with Apple silicon, the graphics share the Mac's memory, so no separate card is needed.
- Is DeepSeek R1 Distill 1.5B free to use?
- Yes. Toskar Core is free and open source, and it downloads DeepSeek R1 Distill 1.5B for you at no cost. The model's own license is MIT. Everything runs on your computer, so there's no per-question bill.
Every model
- Llama 3.2 1B≈ 1.3 GB
- Qwen 2.5 Coder 1.5B≈ 1.6 GB
- DeepSeek R1 Distill 1.5B≈ 1.6 GB
- Gemma 2 2B≈ 2.2 GB
- Qwen 2.5 3B≈ 2.5 GB
- Llama 3.2 3B≈ 2.6 GB
- Phi 3.5 Mini≈ 3.0 GB
- Gemma 3 4B≈ 3.9 GB
- Qwen 3.5 4B≈ 3.9 GB
- Mistral 7B Instruct≈ 5.0 GB
- Qwen 2.5 Coder 7B≈ 5.3 GB
- Qwen 2.5 7B≈ 5.3 GB
- DeepSeek R1 Distill 7B≈ 5.3 GB
- Qwen 2.5 VL 7B≈ 6.1 GB
- Gemma 2 9B≈ 6.5 GB
- Qwen 3.5 9B≈ 7.2 GB
- Qwen 2.5 Coder 14B≈ 9.7 GB
- Qwen 2.5 14B≈ 10.2 GB
- Muse Glimmer 30B≈ 17.1 GB
- Qwen 3.8 27B≈ 20.4 GB
- Qwen 2.5 32B≈ 21.5 GB
Run DeepSeek R1 Distill 1.5B with Toskar
Toskar Core is free and open source for Mac, Windows, and Linux. It checks what your computer can run, downloads the model for you, and keeps every question on your computer.