diff --git a/src/content/docs/workers-ai/features/batch-api/index.mdx b/src/content/docs/workers-ai/features/batch-api/index.mdx
index 45ac9970b5d76d3..77044c1f827caae 100644
--- a/src/content/docs/workers-ai/features/batch-api/index.mdx
+++ b/src/content/docs/workers-ai/features/batch-api/index.mdx
@@ -33,9 +33,4 @@ This will create a repository in your GitHub account and deploy a ready-to-use W
 
 ## Supported Models
 
-- [@cf/meta/llama-3.3-70b-instruct-fp8-fast](/workers-ai/models/llama-3.3-70b-instruct-fp8-fast/)
-- [@cf/baai/bge-small-en-v1.5](/workers-ai/models/bge-small-en-v1.5/)
-- [@cf/baai/bge-base-en-v1.5](/workers-ai/models/bge-base-en-v1.5/)
-- [@cf/baai/bge-large-en-v1.5](/workers-ai/models/bge-large-en-v1.5/)
-- [@cf/baai/bge-m3](/workers-ai/models/bge-m3/)
-- [@cf/meta/m2m100-1.2b](/workers-ai/models/m2m100-1.2b/)
+Refer to our [model catalog](/workers-ai/models/?capabilities=Batch) for supported models.
diff --git a/src/content/docs/workers-ai/features/fine-tunes/loras.mdx b/src/content/docs/workers-ai/features/fine-tunes/loras.mdx
index 518480bb2a9a5c3..546a2874f19211a 100644
--- a/src/content/docs/workers-ai/features/fine-tunes/loras.mdx
+++ b/src/content/docs/workers-ai/features/fine-tunes/loras.mdx
@@ -17,18 +17,7 @@ Workers AI supports fine-tuned inference with adapters trained with [Low-Rank Ad
 
 ## Limitations
 
-- We only support LoRAs for the following models (must not be quantized):
-
-  - `@cf/meta/llama-3.2-11b-vision-instruct`
-  - `@cf/meta/llama-3.3-70b-instruct-fp8-fast`
-  - `@cf/meta/llama-guard-3-8b`
-  - `@cf/meta/llama-3.1-8b-instruct-fast (soon)`
-  - `@cf/deepseek-ai/deepseek-r1-distill-qwen-32b`
-  - `@cf/qwen/qwen2.5-coder-32b-instruct`
-  - `@cf/qwen/qwq-32b`
-  - `@cf/mistralai/mistral-small-3.1-24b-instruct`
-  - `@cf/google/gemma-3-12b-it`
-
+- We only support LoRAs for a [variety of models](/workers-ai/models/?capabilities=LoRA) (must not be quantized)
 - Adapter must be trained with rank `r <=8` as well as larger ranks if up to 32. You can check the rank of a pre-trained LoRA adapter through the adapter's `config.json` file
 - LoRA adapter file must be < 300MB
 - LoRA adapter files must be named `adapter_config.json` and `adapter_model.safetensors` exactly