From f892d22849b45eda2084aa450d89ff265e3f8a45 Mon Sep 17 00:00:00 2001
From: liam <yzwliam@126.com>
Date: Mon, 10 Feb 2025 11:45:46 +0800
Subject: [PATCH] :zap: update v3

---
 README.md                        | 4 ++--
 doc/en/DeepseekR1_V3_tutorial.md | 6 ++++--
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 92c7766..4c85e1f 100644
--- a/README.md
+++ b/README.md
@@ -42,10 +42,10 @@ https://github.com/user-attachments/assets/ebd70bfa-b2c1-4abb-ae3b-296ed38aa285
 </p>
 
 - **[NEW!!!] Local 671B DeepSeek-Coder-V3/R1:** Running its Q4_K_M version using only 14GB VRAM and 382GB DRAM.
-	- Prefill Speed: 
+	- Prefill Speed (tokens/s): 
  		- KTransfermor: 54.21 (32 cores) → 74.362 (dual-socket, 2×32 cores) → 255.26 (optimized AMX-based MoE kernel, V0.3 only) → 286.55 (selectively using 6 experts, V0.3 only)  
  		- Compared to 4.51 tokens/s in llama.cpp with 2×32 cores, achieving up to **63.53× speedup**.  
- 	- Decode Speed(tokens/s):  
+ 	- Decode Speed (tokens/s):  
  		- KTransfermor: 8.73 (32 cores) → 11.26 (dual-socket, 2×32 cores) → 13.69 (selectively using 6 experts, V0.3 only)  
  		- Compared to 4.51 tokens/s in llama.cpp with 2×32 cores, achieving up to **3.03× speedup**.  
 	- Upcoming Open Source Release:
diff --git a/doc/en/DeepseekR1_V3_tutorial.md b/doc/en/DeepseekR1_V3_tutorial.md
index e65e1d1..b69b304 100644
--- a/doc/en/DeepseekR1_V3_tutorial.md
+++ b/doc/en/DeepseekR1_V3_tutorial.md
@@ -1,15 +1,17 @@
 # GPT-4/o1-level Local VSCode Copilot on a Desktop with only 24GB VRAM
 # SUMMARY
 
+- **Fed 10, 2025**: Support DeepseekR1 and V3 on single (24GB VRAM)/multi gpu and 382G DRAM, up to 3~64x speedup.<br>
+
 https://github.com/user-attachments/assets/ebd70bfa-b2c1-4abb-ae3b-296ed38aa285
 
 </p>
 
 - **[NEW!!!] Local 671B DeepSeek-Coder-V3/R1:** Running its Q4_K_M version using only 14GB VRAM and 382GB DRAM.
-	- Prefill Speed: 
+	- Prefill Speed (tokens/s): 
  		- KTransfermor: 54.21 (32 cores) → 74.362 (dual-socket, 2×32 cores) → 255.26 (optimized AMX-based MoE kernel, V0.3 only) → 286.55 (selectively using 6 experts, V0.3 only)  
  		- Compared to 4.51 tokens/s in llama.cpp with 2×32 cores, achieving up to **63.53× speedup**.  
- 	- Decode Speed(tokens/s):  
+ 	- Decode Speed (tokens/s):  
  		- KTransfermor: 8.73 (32 cores) → 11.26 (dual-socket, 2×32 cores) → 13.69 (selectively using 6 experts, V0.3 only)  
  		- Compared to 4.51 tokens/s in llama.cpp with 2×32 cores, achieving up to **3.03× speedup**.  
 	- Upcoming Open Source Release: