[CP V1 Deprecation 5/5] Update prefill CP documentation (#36230)

docs/cookbook/autoregressive/GLM/GLM-5.1.mdx

@@ -100,6 +100,9 @@ import { GLM51Deployment } from '/src/snippets/autoregressive/glm-51-deployment.
 - **B300 and GB300**: NVFP4 is the recommended deployment path. Use `nvidia/GLM-5.1-NVFP4` with `--quantization modelopt_fp4`. Use `tp=8` on B300 and `tp=4` on GB300. The CUDA 13 image variant is required for B300 and GB300.
 - **AMD GPUs**: BF16 and FP8 checkpoints run on MI300X/MI325X/MI355X at tp=8. On MI355X (gfx950), the MXFP4 checkpoint `amd/GLM-5.1-MXFP4` is also supported at tp=4 with `--kv-cache-dtype fp8_e4m3`. All AMD paths pass `--dsa-prefill-backend tilelang --dsa-decode-backend tilelang`, `--chunked-prefill-size 131072`, and `--watchdog-timeout 1200` (20 minutes for weight loading). FP8 uses approximately half the memory of BF16 (~89 GB/GPU vs ~175 GB/GPU). EAGLE speculative decoding is supported on AMD GPUs: MI300X/MI325X (gfx942) and MI355X (gfx950), but it **requires `--disable-custom-all-reduce`** — the aiter custom all-reduce kernel deadlocks during EAGLE verify at high concurrency, so without this flag the server will hang.
 - For other configuration tips (MTP, DSA kernel, Context Parallel, HiSparse, NVFP4, Index Cache), see the [DeepSeek-V3.2 cookbook page](../DeepSeek/DeepSeek-V3_2). GLM-5.1 and DeepSeek-V3.2 share the same model structure, so the optimization techniques are common.
+
+- **Prefill CP on CUDA**: Zigzag (`--cp-strategy zigzag`) is temporarily unavailable for GLM-5.1. Use `--enable-prefill-cp --cp-strategy interleave` with `--dp 1`.
+
 - Use `--json-model-override-args '{"index_topk_pattern": "FFSFSSSFSSFFFSSSFFFSFSSSSSSFFSFFSFFSSFFFFFFSFFFFFSFFSSSSSSFSFFFSFSSSFSFFSFFSSS"}'` to enable the [IndexCache](https://github.com/THUDM/IndexCache) method for GLM-5.1. This can improve serving efficiency with only a small accuracy loss. If you are running rigorous accuracy evaluations, do not enable this feature.
 
 ## 4. Model Invocation

docs/cookbook/autoregressive/GLM/GLM-5.2.mdx

@@ -254,6 +254,10 @@ For the full setup (streaming, tool-use, count_tokens, persisting env in `~/.cla
 
 ### 3.5 Context Parallelism
 
+<Warning>
+Zigzag prefill CP (`--cp-strategy zigzag`) is temporarily unavailable for GLM-5.2. For prefill CP on CUDA, use `interleave` with `--dp 1` as shown below.
+</Warning>
+
 Prefill context parallelism can help with reduction of TTFT under long context. To enable prefill context parallelism for GLM 5.2, please append the following arguments:
 ```bash
 --attn-cp-size 8 \

docs/cookbook/autoregressive/GLM/GLM-5.3.mdx

@@ -242,6 +242,10 @@ For the full setup (streaming, tool-use, count_tokens, persisting env in `~/.cla
 
 ### 3.5 Context Parallelism
 
+<Warning>
+Zigzag prefill CP (`--cp-strategy zigzag`) is temporarily unavailable for GLM-5.3. For prefill CP on CUDA, use `interleave` with `--dp 1` as shown below.
+</Warning>
+
 Prefill context parallelism can help with reduction of TTFT under long context. To enable prefill context parallelism for GLM 5.3, please append the following arguments:
 ```bash
 --attn-cp-size 8 \

docs/cookbook/autoregressive/GLM/GLM-5.mdx

@@ -93,6 +93,9 @@ import { GLM5Deployment } from '/src/snippets/autoregressive/glm-5-deployment.js
 
 - **AMD GPUs**: Use `--dsa-prefill-backend tilelang --dsa-decode-backend tilelang` for the DSA attention backend. Add `--chunked-prefill-size 131072` and `--watchdog-timeout 1200` (20 minutes for weight loading). EAGLE speculative decoding is not currently supported on AMD for GLM-5.
 - For other configuration tips (MTP, DSA kernel, Context Parallel, HiSparse, NVFP4, Index Cache), see the [DeepSeek-V3.2 cookbook page](../DeepSeek/DeepSeek-V3_2). GLM-5 and DeepSeek-V3.2 share the same model structure, so the optimization techniques are common.
+
+- **Prefill CP on CUDA**: Zigzag (`--cp-strategy zigzag`) is temporarily unavailable for GLM-5. Use `--enable-prefill-cp --cp-strategy interleave` with `--dp 1`.
+
 - Use `--json-model-override-args '{"index_topk_pattern": "FFSFSSSFSSFFFSSSFFFSFSSSSSSFFSFFSFFSSFFFFFFSFFFFFSFFSSSSSSFSFFFSFSSSFSFFSFFSSS"}'` for GLM-5-FP8 if you want to enable the [IndexCache](https://github.com/THUDM/IndexCache) method. This feature is supported through [this PR](https://github.com/sgl-project/sglang/pull/21405) and introduces only a small accuracy loss. However, if you are running rigorous accuracy evaluations, it is not recommended to enable this feature.
 
 ## 4. Model Invocation