### What this PR does / why we need it?
1. add PaddleOCR-VL.md in the `docs/source/tutorials/`
2. add PaddleOCR-VL index in `docs/source/tutorials/index.md`
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
by CI
- vLLM version: v0.13.0
- vLLM main:
7157596103
Signed-off-by: zouyizhou <zouyizhou@huawei.com>
### What this PR does / why we need it?
Add Qwen3-Omni-30B-A3B-Thinking Tutorials
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
5326c89803
---------
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
### What this PR does / why we need it?
This documentation provides a comprehensive technical guide for
deploying **vLLM-Ascend** using a **Prefill-Decode (PD) colocated
architecture** integrated with **Mooncake**, a high-performance
distributed KV Cache transfer engine. As Large Language Model (LLM)
serving scales, managing KV Cache efficiently across distributed nodes
is essential for reducing latency and optimizing hardware utilization.
The tutorial focuses on a multi-instance setup using Huawei **Atlas 800T
A2** nodes. By leveraging Mooncake’s distributed memory pooling, vLLM
instances can achieve seamless **cross-node KV Cache reuse**. This
capability allows an instance to retrieve precomputed cache from a
remote node's DRAM via high-speed **RoCE** networks, effectively
bypassing redundant prefill computations.
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: release/v0.13.0
- vLLM main:
0bfd7484fd
---------
Signed-off-by: zhangmuzhibangde <1037640609@qq.com>
Signed-off-by: zhangmuzhi_yuwan <1037640609@qq.com>
Co-authored-by: Yikun Jiang <yikunkero@gmail.com>
### What this PR does / why we need it?
add long_sequence feature user guide
- vLLM version: release/v0.13.0
- vLLM main:
bc0a5a0c08
---------
Signed-off-by: LookAround <lixushi@huawei.com>
### What this PR does / why we need it?
Provide sample guidance for running long-sequence DeepSeek across
multiple nodes
To guide users on using the context parallel feature, a practical
example is provided.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: release/v0.13.0
- vLLM main:
bc0a5a0c08
Signed-off-by: weiguihua2 <weiguihua2@huawei.com>
### What this PR does / why we need it?
This PR provides an introduction to the Qwen3-VL-235B-A22B-Instruct
model, details on the features supported by the model in the current
version, the model deployment process, as well as methods for
performance testing and accuracy testing.
With this document, the deployment and testing of the
Qwen3-VL-235B-A22B-Instruct model can be implemented more easily.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: luluxiu520 <l2625793@outlook.com>
### What this PR does / why we need it?
add qwen3 reranker tutorials
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.12.0
---------
Signed-off-by: TingW09 <944713709@qq.com>
### What this PR does / why we need it?
Correct more doc mistakes
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: lilinsiman <lilinsiman@gmail.com>
This PR clean up useless torchair logic in model runner. The moge doc is
only for torchair, it can be removed as well.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
### What this PR does / why we need it?
This document employs the qwen3-vl-8b model and qwen2.5-vl-32b to
demonstrate the primary verification steps for the Qwen-VL series dense
models, including supported features, feature configuration, environment
preparation, NPU deployment, and accuracy and performance evaluation.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: MrZ20 <2609716663@qq.com>
### What this PR does / why we need it?
This PR adds tutorials for the DeepSeeK-R1 series models, including the
A2 and A3 series, and provides accuracy validation results.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: Gongdayao <gongdayao@foxmail.com>
### What this PR does / why we need it?
This PR adds tutorials for the Qwen3-Dense series models, including the
A2 and A3 series, and provides accuracy validation results.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: wind-all <anyuting@h-partners.com>
### What this PR does / why we need it?
Adds W4A16 quantization method for the Kimi-K2-Thinking model and
updates relevant modules to support the new quantization method.
- Implements complete W4A16 quantization method including weight
packing/unpacking, per-group quantization parameter generation,
post-processing logic and MoE method application.
- Adds parameters `use_int4_w4a16`, `w1_offset` and `w2_offset`, adjusts
`with_quant` conditional logic to support W4A16 matrix multiplication.
- Adds `packed_modules_model_mapping` for Kimi-K2-Thinking model and
processing logic for `weight_packed` field.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: zhoux77899 <zhouxiang100@huawei.com>
Signed-off-by: Ruri <33858552+zhoux77899@users.noreply.github.com>
Signed-off-by: Ruri <zhouxiang100@huawei.com>
### What this PR does / why we need it?
As support for the mooncake connector is now available, the llmdatadist
connector is no longer being maintained, so the llmdatadist-related
files need to be retired.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By ci
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
Signed-off-by: liziyu <liziyu16@huawei.com>
Co-authored-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
Add Qwen3-235B tutorial including the following examples
- Single-node Online Deployment for 128k context inference
- Multi-node Deployment with MP
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: xuyexiong <xuyexiong@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Add readme for PD separation
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By ci
- vLLM version: v0.11.0
- vLLM main:
2918c1b49c
---------
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
Signed-off-by: liziyu <liziyu16@huawei.com>
Co-authored-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
add single node PD disaggregation instructions for Qwen 2.5VL model.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
2918c1b49c
---------
Signed-off-by: mazhixin <mazhixin7@huawei.com>
Signed-off-by: mazhixin000 <mazhixinkorea@163.com>
Co-authored-by: mazhixin <mazhixin7@huawei.com>
### What this PR does / why we need it?
v0.11.0rc1 will introduce w4a4 quantization feature, so add this
tutorial.
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: 22dimensions <waitingwind@foxmail.com>
### What this PR does / why we need it?
Refactor the DeepSeek-V3.2-Exp tutorial.
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: menogrey <1299267905@qq.com>
### What this PR does / why we need it?
Resolve the issue where, in the case of unequal TP (Tensor Parallelism),
the TP size is larger than the number of model attention kvcache heads,
causing the KV cache to generate duplicates, which leads to transmission
errors in the original code.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By ci
- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0
---------
Signed-off-by: nwpu-zxr <zhouxuerong2@huawei.com>
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
Co-authored-by: nwpu-zxr <zhouxuerong2@huawei.com>
### What this PR does / why we need it?
This PR provides user guide documents for Qwen3-VL 4B and
Qwen3-VL-235B-A22B.
### Does this PR introduce _any_ user-facing change?
None
### How was this patch tested?
- vLLM version: v0.10.2
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.0
---------
Signed-off-by: booker123456 <945658361@qq.com>
### What this PR does / why we need it?
Add multi-node ray backend tutorial for Qwen235B-A3B
### How was this patch tested?
- vLLM version: v0.10.2
- vLLM main:
f4cd80f944
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
The PR is for the document of the prefiller&decoder disaggregation
deloyment guide.
The scenario of the guide is:
- Use 3 nodes totally and 2 NPUs on each node
- Qwen3-30B-A3B
- 1P2D
- Expert Parallel
The deployment can be used to verify PD Disggregation / Expert Parallel
features with a slightly less resources.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
No.
- vLLM version: v0.10.1.1
- vLLM main:
e599e2c65e
---------
Signed-off-by: paulyu12 <507435917@qq.com>
### What this PR does / why we need it?
Add a new single npu quantization tutorial, and using the latest qwen3
model.
- vLLM version: v0.10.0
- vLLM main:
8e8e0b6af1
Signed-off-by: 22dimensions <waitingwind@foxmail.com>
### What this PR does / why we need it?
In fact, the kimi-k2 model is similar to the deepseek model, and we only
need to make a few changes to support it. what does this pr do:
1. Add kimi-k2-w8a8 deployment doc
2. Update quantization doc
3. Upgrade torchair support list
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.10.0
- vLLM main:
9edd1db02b
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
1. Add the tutorials for qwen3-embedding-8b
2. Remove VLLM_USE_V1=1 in docs, it's useless any more from 0.9.2
- vLLM version: v0.9.2
- vLLM main:
5923ab9524
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Cleanup ununsed doc for MoGE model, we will add back this when MoGE
model ready.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
Run vllm-ascend on Single NPU
What this PR does / why we need it?
Add vllm-ascend tutorial doc for Qwen/Qwen2.5-VL-7B-Instruct model
Inference/Serving doc
Does this PR introduce any user-facing change?
no
How was this patch tested?
no
Signed-off-by: xiemingda <xiemingda1002@gmail.com>
### What this PR does / why we need it?
Re-arch on tutorials, move singe npu / multi npu / multi node to index.
- Unifiy docker run cmd
- Use dropdown to hide build from source installation doc
- Re-arch tutorials to include Qwen/QwQ/DeepSeek
- Make QwQ doc works
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI test
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
