diff --git a/docs/usage/v1_guide.md b/docs/usage/v1_guide.md
index 7c4909cb5d91..baeb5411bcfd 100644
--- a/docs/usage/v1_guide.md
+++ b/docs/usage/v1_guide.md
@@ -55,7 +55,7 @@ This living user guide outlines a few known **important changes and limitations*
| **Spec Decode** | 🚧 WIP ([PR #13933](https://github.com/vllm-project/vllm/pull/13933))|
| **Prompt Logprobs with Prefix Caching** | 🟡 Planned ([RFC #13414](https://github.com/vllm-project/vllm/issues/13414))|
| **Structured Output Alternative Backends** | 🟡 Planned |
-| **Embedding Models** | 🚧 WIP ([PR #18015](https://github.com/vllm-project/vllm/pull/18015)) |
+| **Embedding Models** | 🚧 WIP ([PR #16188](https://github.com/vllm-project/vllm/pull/16188)) |
| **Mamba Models** | 🟡 Planned |
| **Encoder-Decoder Models** | 🟠Delayed |
| **Request-level Structured Output Backend** | 🔴 Deprecated |
@@ -145,9 +145,9 @@ vLLM V1 currently excludes model architectures with the `SupportsV0Only` protoco
and the majority fall into the following categories. V1 support for these models will be added eventually.
**Embedding Models**
-Initially, we will create a [separate model runner](https://github.com/vllm-project/vllm/pull/18015) to provide V1 support without conflicting with other ongoing work.
+The initial support will be provided by [PR #16188](https://github.com/vllm-project/vllm/pull/16188).
-Later, we will consider using [hidden states processor](https://github.com/vllm-project/vllm/issues/12249), which is based on [global logits processor](https://github.com/vllm-project/vllm/pull/13360) to enable simultaneous generation and embedding using the same engine instance in V1. [PR #16188](https://github.com/vllm-project/vllm/pull/16188) is the first step towards enabling this.
+Later, we will consider using [hidden states processor](https://github.com/vllm-project/vllm/issues/12249), which is based on [global logits processor](https://github.com/vllm-project/vllm/pull/13360) to enable simultaneous generation and embedding using the same engine instance in V1.
**Mamba Models**
Models using selective state-space mechanisms (instead of standard transformer attention)