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README.md
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@ -41,7 +41,7 @@ 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 12GB VRAM and 382GB DRAM.
- **[NEW!!!] Local 671B DeepSeek-Coder-V3/R1:** Running its Q4_K_M version using only 14GB VRAM and 382GB DRAM.
- Prefill Speed:
- KTransfermor: 54.21 (32 cores) → 74.362 (dual-socket, 2×32 cores) → 255.26 (optimized AMX-based MoE kernel, v3 only) → 286.55 (selectively using 6 experts, v3 only)
- Compared to 4.51 tokens/s in llama.cpp with 2×32 cores, achieving up to **63.53× speedup**.

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doc/en/DeepseekR1_V3_tutorial.md
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# Report
# GPT-4/o1-level Local VSCode Copilot on a Desktop with only 24GB VRAM
# SUMMARY
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:
- KTransfermor: 54.21 (32 cores) → 74.362 (dual-socket, 2×32 cores) → 255.26 (optimized AMX-based MoE kernel, v3 only) → 286.55 (selectively using 6 experts, v3 only)
- Compared to 4.51 tokens/s in llama.cpp with 2×32 cores, achieving up to **63.53× speedup**.
- Decode Speed(tokens/s):
- KTransfermor: 8.73 (32 cores) → 11.26 (dual-socket, 2×32 cores) → 13.69 (selectively using 6 experts, v3 only)
- Compared to 4.51 tokens/s in llama.cpp with 2×32 cores, achieving up to **3.03× speedup**.
- Upcoming Open Source Release:
- AMX optimizations and selective expert activation will be open-sourced in v0.3.
- Currently available only in preview binary distribution, which can be found [here](xxx).
## Prerequisites
We run our best performance tests (V0.2) on <br>
CPU: Intel (R) Xeon (R) Gold 6454S 1T DRAM (2 NUMA nodes) <br>
@ -11,8 +29,8 @@ GPU: 4090D 24G VRAM <br>
- GPU: 4090D 24G VRAM
- We test after enough warm up
#### Memory consumption:
- Single socket: 382G DRAM, at least 12G VRAM
- Dual socket: 1T DRAM, at least 12G VRAM
- Single socket: 382G DRAM, at least 14GB VRAM
- Dual socket: 1T DRAM, at least 14GB VRAM
#### Benchmark Results
@ -32,7 +50,7 @@ GPU: 4090D 24G VRAM <br>
- GPU: (1~4)x 4090D 24GVRAM (requires more VRAM for longer prompt)
#### Memory consumptions:
- 644GB DRAM, at least 12GB VRAM
- 644GB DRAM, at least 14GB VRAM
#### Benchmark results
| Prompt length | 1K | 2K | 4K | 8K |