Update README.md
Browse files
README.md
CHANGED
|
@@ -12,8 +12,10 @@ tags:
|
|
| 12 |
|
| 13 |
# DeepSeek-R1-Distill-Llama-8B-NexaQuant
|
| 14 |
|
| 15 |
-
##
|
| 16 |
-
|
|
|
|
|
|
|
| 17 |
|
| 18 |
---
|
| 19 |
|
|
|
|
| 12 |
|
| 13 |
# DeepSeek-R1-Distill-Llama-8B-NexaQuant
|
| 14 |
|
| 15 |
+
## Background + Overview
|
| 16 |
+
DeepSeek-R1 has been making headlines for rivaling OpenAI’s O1 reasoning model while remaining fully open-source. Many users want to run it locally to ensure data privacy, reduce latency, and maintain offline access. However, fitting such a large model onto personal devices typically requires quantization (e.g. Q4_K_M), which often sacrifices accuracy (up to ~22% accuracy loss) and undermines the benefits of the local reasoning model.
|
| 17 |
+
|
| 18 |
+
We’ve solved the trade-off by quantizing the DeepSeek R1 Distilled model to one-fourth its original size—without losing any accuracy. This lets you run powerful on-device reasoning wherever you are, with no compromises. Tests on an **HP Omnibook AIPC** with an **AMD Ryzen™ AI 9 HX 370 processor** showed a decoding speed of **66.40 tokens per second** and a peak RAM usage of just **1228 MB** in NexaQuant version—compared to only **25.28 tokens** per second and **3788 MB RAM** in the unquantized version—while **maintaining full precision model accuracy.**
|
| 19 |
|
| 20 |
---
|
| 21 |
|