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Merge pull request #1493 from Azure-Tang/main

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Support kimi-k2-0905
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2025-09-05 11:56:39 +08:00
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README.md
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@@ -23,6 +23,7 @@ Our vision for KTransformers is to serve as a flexible platform for experimentin
<h2 id="Updates">🔥 Updates</h2>
* **July 11, 2025**: Support Kimi-K2-0905. ([Tutorial](./doc/en/Kimi-K2.md))
* **July 26, 2025**: Support SmallThinker and GLM4-MoE. ([Tutorial](./doc/en/SmallThinker_and_Glm4moe.md))
* **July 11, 2025**: Support Kimi-K2. ([Tutorial](./doc/en/Kimi-K2.md))
* **June 30, 2025**: Support 3-layer (GPU-CPU-Disk) [prefix cache](./doc/en/prefix_cache.md) reuse.

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doc/en/Kimi-K2.md
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## Introduction
### Overview
We are very pleased to announce that Ktransformers now supports Kimi-K2.
We are very pleased to announce that Ktransformers now supports Kimi-K2 and Kimi-K2-0905.
On a single-socket CPU with one consumer-grade GPU, running the Q4_K_M model yields roughly 10 TPS and requires about 600 GB of DRAM.
With a dual-socket CPU and sufficient system memory, enabling NUMA optimizations increases performance to about 14 TPS.
@@ -14,6 +14,10 @@ With a dual-socket CPU and sufficient system memory, enabling NUMA optimizations
- https://huggingface.co/collections/moonshotai/kimi-k2-6871243b990f2af5ba60617d
- GGUF Format(quantized models):
- https://huggingface.co/KVCache-ai/Kimi-K2-Instruct-GGUF
- Official Kimi-K2-0905 Release:
- https://huggingface.co/moonshotai/Kimi-K2-Instruct-0905
- GGUF Format(quantized models):
- Uploading...
## Installation Guide