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[Release] Add 0.9.2rc1 release note (#1725)

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Add release note for 0.9.2rc1, we'll release soon









- vLLM version: v0.9.2
- vLLM main:
7bd4c37ae7

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2025-07-11 17:36:05 +08:00
committed by GitHub
parent 1b4a2f3817
commit 9c560b009a
8 changed files with 68 additions and 16 deletions
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18
docs/source/faqs.md
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@@ -3,19 +3,19 @@
## Version Specific FAQs
- [[v0.7.3.post1] FAQ & Feedback](https://github.com/vllm-project/vllm-ascend/issues/1007)
- [[v0.9.1rc1] FAQ & Feedback](https://github.com/vllm-project/vllm-ascend/issues/1351)
- [[v0.9.2rc1] FAQ & Feedback](https://github.com/vllm-project/vllm-ascend/issues/1742)
## General FAQs
### 1. What devices are currently supported?
Currently, **ONLY Atlas A2 series** (Ascend-cann-kernels-910b) are supported:
Currently, **ONLY** Atlas A2 series(Ascend-cann-kernels-910b) and Atlas 300I(Ascend-cann-kernels-310p) series are supported:
- Atlas A2 Training series (Atlas 800T A2, Atlas 900 A2 PoD, Atlas 200T A2 Box16, Atlas 300T A2)
- Atlas 800I A2 Inference series (Atlas 800I A2)
- Atlas 300I Inference series (Atlas 300I Duo)
Below series are NOT supported yet:
- Atlas 300I Duo、Atlas 300I Pro (Ascend-cann-kernels-310p) might be supported on 2025.Q2
- Atlas 200I A2 (Ascend-cann-kernels-310b) unplanned yet
- Ascend 910, Ascend 910 Pro B (Ascend-cann-kernels-910) unplanned yet
@@ -35,7 +35,7 @@ docker pull m.daocloud.io/quay.io/ascend/vllm-ascend:$TAG
### 3. What models does vllm-ascend supports?
Find more details [<u>here</u>](https://vllm-ascend.readthedocs.io/en/latest/user_guide/supported_models.html).
Find more details [<u>here</u>](https://vllm-ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_models.html).
### 4. How to get in touch with our community?
@@ -48,7 +48,7 @@ There are many channels that you can communicate with our community developers /
### 5. What features does vllm-ascend V1 supports?
Find more details [<u>here</u>](https://github.com/vllm-project/vllm-ascend/issues/414).
Find more details [<u>here</u>](https://vllm-ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html).
### 6. How to solve the problem of "Failed to infer device type" or "libatb.so: cannot open shared object file"?
@@ -69,7 +69,7 @@ If all above steps are not working, feel free to submit a GitHub issue.
### 7. How does vllm-ascend perform?
Currently, only some models are improved. Such as `Qwen2 VL`, `Deepseek V3`. Others are not good enough. From 0.9.0rc2, Qwen and Deepseek works with graph mode to play a good performance. What's more, you can install `mindie-turbo` with `vllm-ascend v0.7.3` to speed up the inference as well.
Currently, only some models are improved. Such as `Qwen2.5 VL`, `Qwen3`, `Deepseek V3`. Others are not good enough. From 0.9.0rc2, Qwen and Deepseek works with graph mode to play a good performance. What's more, you can install `mindie-turbo` with `vllm-ascend v0.7.3` to speed up the inference as well.
### 8. How vllm-ascend work with vllm?
vllm-ascend is a plugin for vllm. Basically, the version of vllm-ascend is the same as the version of vllm. For example, if you use vllm 0.7.3, you should use vllm-ascend 0.7.3 as well. For main branch, we will make sure `vllm-ascend` and `vllm` are compatible by each commit.
@@ -84,7 +84,7 @@ Currently, w8a8 quantization is already supported by vllm-ascend originally on v
### 11. How to run w8a8 DeepSeek model?
Please following the [quantization inferencing tutorail](https://vllm-ascend.readthedocs.io/en/main/tutorials/multi_npu_quantization.html) and replace model to DeepSeek.
Please following the [inferencing tutorail](https://vllm-ascend.readthedocs.io/en/latest/tutorials/multi_node.html) and replace model to DeepSeek.
### 12. There is no output in log when loading models using vllm-ascend, How to solve it?
@@ -94,9 +94,9 @@ If you're using vllm 0.7.3 version, this is a known progress bar display issue i
vllm-ascend is tested by functional test, performance test and accuracy test.
- **Functional test**: we added CI, includes portion of vllm's native unit tests and vllm-ascend's own unit tests，on vllm-ascend's test, we test basic functionality、popular models availability and [supported features](https://vllm-ascend.readthedocs.io/en/latest/user_guide/suppoted_features.html) via e2e test
- **Functional test**: we added CI, includes portion of vllm's native unit tests and vllm-ascend's own unit tests，on vllm-ascend's test, we test basic functionality、popular models availability and [supported features](https://vllm-ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html) via e2e test
- **Performance test**: we provide [benchmark](https://github.com/vllm-project/vllm-ascend/tree/main/benchmarks) tools for end-to-end performance benchmark which can easily to re-route locally, we'll publish a perf website like [vllm](https://simon-mo-workspace.observablehq.cloud/vllm-dashboard-v0/perf) does to show the performance test results for each pull request
- **Performance test**: we provide [benchmark](https://github.com/vllm-project/vllm-ascend/tree/main/benchmarks) tools for end-to-end performance benchmark which can easily to re-route locally, we'll publish a perf website to show the performance test results for each pull request
- **Accuracy test**: we're working on adding accuracy test to CI as well.