diff --git a/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep4-dep8-c1024.yaml b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep4-dep8-c1024.yaml
new file mode 100644
index 000000000..5cb6c798b
--- /dev/null
+++ b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep4-dep8-c1024.yaml
@@ -0,0 +1,112 @@
+name: kimi-k2.6-vllm-disagg-b200-1p1d-dep4-dep8-c1024
+model:
+  path: kimi-k2.6-nvfp4
+  container: vllm/vllm-openai:v0.25.1
+  precision: fp4
+dynamo:
+  wheel: 1.3.0.dev20260721
+  install: true
+resources:
+  gpu_type: b200
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 1
+  decode_workers: 1
+  gpus_per_prefill: 4
+  gpus_per_decode: 8
+infra:
+  etcd_nats_dedicated_node: true
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+backend:
+  type: vllm
+  connector: null
+  dp_launch_mode: per_gpu
+  prefill_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: '900'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  decode_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  vllm_config:
+    prefill:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both", "engine_id": "kimi-k26-prefill-dep4"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 4
+      data-parallel-rpc-port: 13346
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      enforce-eager: true
+      compilation-config: '{"custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      attention-config: '{"mla_prefill_backend": "TRTLLM_RAGGED"}'
+      gpu-memory-utilization: 0.94
+    decode:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      async-scheduling: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      gpu-memory-utilization: 0.9
+      stream-interval: 50
+      max-cudagraph-capture-size: 1024
+benchmark:
+  type: sa-bench
+  isl: 8192
+  osl: 1024
+  concurrencies: '1024'
+  req_rate: inf
+  use_chat_template: true
diff --git a/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep8-dep8-c2048.yaml b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep8-dep8-c2048.yaml
new file mode 100644
index 000000000..e3c08dc47
--- /dev/null
+++ b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep8-dep8-c2048.yaml
@@ -0,0 +1,112 @@
+name: kimi-k2.6-vllm-disagg-b200-1p1d-dep8-dep8-c2048
+model:
+  path: kimi-k2.6-nvfp4
+  container: vllm/vllm-openai:v0.25.1
+  precision: fp4
+dynamo:
+  wheel: 1.3.0.dev20260721
+  install: true
+resources:
+  gpu_type: b200
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 1
+  decode_workers: 1
+  gpus_per_prefill: 8
+  gpus_per_decode: 8
+infra:
+  etcd_nats_dedicated_node: true
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+backend:
+  type: vllm
+  connector: null
+  dp_launch_mode: per_gpu
+  prefill_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: '900'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  decode_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  vllm_config:
+    prefill:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both", "engine_id": "kimi-k26-prefill-dep8"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13346
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      enforce-eager: true
+      compilation-config: '{"custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      max-num-batched-tokens: 16384
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      attention-config: '{"mla_prefill_backend": "TRTLLM_RAGGED"}'
+      gpu-memory-utilization: 0.9
+    decode:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      async-scheduling: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      gpu-memory-utilization: 0.9
+      stream-interval: 50
+      max-cudagraph-capture-size: 1024
+benchmark:
+  type: sa-bench
+  isl: 8192
+  osl: 1024
+  concurrencies: '2048'
+  req_rate: inf
+  use_chat_template: true
diff --git a/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep8-tp8-c1.yaml b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep8-tp8-c1.yaml
new file mode 100644
index 000000000..1c0abe2fa
--- /dev/null
+++ b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p1d-dep8-tp8-c1.yaml
@@ -0,0 +1,110 @@
+name: kimi-k2.6-vllm-disagg-b200-1p1d-dep8-tp8-c1
+model:
+  path: kimi-k2.6-nvfp4
+  container: vllm/vllm-openai:v0.25.1
+  precision: fp4
+dynamo:
+  wheel: 1.3.0.dev20260721
+  install: true
+resources:
+  gpu_type: b200
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 1
+  decode_workers: 1
+  gpus_per_prefill: 8
+  gpus_per_decode: 8
+infra:
+  etcd_nats_dedicated_node: true
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+backend:
+  type: vllm
+  connector: null
+  dp_launch_mode: per_gpu
+  prefill_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: '900'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  decode_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '0'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  vllm_config:
+    prefill:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both", "engine_id": "kimi-k26-prefill-dep8"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13346
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      enforce-eager: true
+      compilation-config: '{"custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      max-num-batched-tokens: 16384
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      attention-config: '{"mla_prefill_backend": "TRTLLM_RAGGED"}'
+      gpu-memory-utilization: 0.9
+    decode:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 8
+      pipeline-parallel-size: 1
+      disable-custom-all-reduce: true
+      max-model-len: 9216
+      max-num-seqs: 1024
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      async-scheduling: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      gpu-memory-utilization: 0.9
+      stream-interval: 50
+      max-cudagraph-capture-size: 256
+benchmark:
+  type: sa-bench
+  isl: 8192
+  osl: 1024
+  concurrencies: '1'
+  req_rate: inf
+  use_chat_template: true
diff --git a/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p4d-dep4-tp4-c512.yaml b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p4d-dep4-tp4-c512.yaml
new file mode 100644
index 000000000..1ca87ad9b
--- /dev/null
+++ b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p4d-dep4-tp4-c512.yaml
@@ -0,0 +1,109 @@
+name: kimi-k2.6-vllm-disagg-b200-1p4d-dep4-tp4-c512
+model:
+  path: kimi-k2.6-nvfp4
+  container: vllm/vllm-openai:v0.25.1
+  precision: fp4
+dynamo:
+  wheel: 1.3.0.dev20260721
+  install: true
+resources:
+  gpu_type: b200
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 1
+  decode_workers: 4
+  gpus_per_prefill: 4
+  gpus_per_decode: 4
+infra:
+  etcd_nats_dedicated_node: true
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+backend:
+  type: vllm
+  connector: null
+  dp_launch_mode: per_gpu
+  prefill_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: '900'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  decode_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  vllm_config:
+    prefill:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both", "engine_id": "kimi-k26-prefill-dep4"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 4
+      data-parallel-rpc-port: 13346
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      enforce-eager: true
+      compilation-config: '{"custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      attention-config: '{"mla_prefill_backend": "TRTLLM_RAGGED"}'
+      gpu-memory-utilization: 0.94
+    decode:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 4
+      pipeline-parallel-size: 1
+      max-model-len: 9216
+      max-num-seqs: 2048
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      async-scheduling: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      gpu-memory-utilization: 0.93
+      stream-interval: 50
+      max-cudagraph-capture-size: 2048
+benchmark:
+  type: sa-bench
+  isl: 8192
+  osl: 1024
+  concurrencies: '512'
+  req_rate: inf
+  use_chat_template: true
diff --git a/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p8d-dep4-tp4-c128.yaml b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p8d-dep4-tp4-c128.yaml
new file mode 100644
index 000000000..44f8ff784
--- /dev/null
+++ b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p8d-dep4-tp4-c128.yaml
@@ -0,0 +1,109 @@
+name: kimi-k2.6-vllm-disagg-b200-1p8d-dep4-tp4-c128
+model:
+  path: kimi-k2.6-nvfp4
+  container: vllm/vllm-openai:v0.25.1
+  precision: fp4
+dynamo:
+  wheel: 1.3.0.dev20260721
+  install: true
+resources:
+  gpu_type: b200
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 4
+  prefill_workers: 1
+  decode_workers: 8
+  gpus_per_prefill: 4
+  gpus_per_decode: 4
+infra:
+  etcd_nats_dedicated_node: true
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+backend:
+  type: vllm
+  connector: null
+  dp_launch_mode: per_gpu
+  prefill_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: '900'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  decode_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  vllm_config:
+    prefill:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both", "engine_id": "kimi-k26-prefill-dep4"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 4
+      data-parallel-rpc-port: 13346
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      enforce-eager: true
+      compilation-config: '{"custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      attention-config: '{"mla_prefill_backend": "TRTLLM_RAGGED"}'
+      gpu-memory-utilization: 0.94
+    decode:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 4
+      pipeline-parallel-size: 1
+      max-model-len: 9216
+      max-num-seqs: 2048
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      async-scheduling: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      gpu-memory-utilization: 0.93
+      stream-interval: 50
+      max-cudagraph-capture-size: 2048
+benchmark:
+  type: sa-bench
+  isl: 8192
+  osl: 1024
+  concurrencies: '128'
+  req_rate: inf
+  use_chat_template: true
diff --git a/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p8d-dep4-tp4-c32.yaml b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p8d-dep4-tp4-c32.yaml
new file mode 100644
index 000000000..c748107fe
--- /dev/null
+++ b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-1p8d-dep4-tp4-c32.yaml
@@ -0,0 +1,109 @@
+name: kimi-k2.6-vllm-disagg-b200-1p8d-dep4-tp4-c32
+model:
+  path: kimi-k2.6-nvfp4
+  container: vllm/vllm-openai:v0.25.1
+  precision: fp4
+dynamo:
+  wheel: 1.3.0.dev20260721
+  install: true
+resources:
+  gpu_type: b200
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 4
+  prefill_workers: 1
+  decode_workers: 8
+  gpus_per_prefill: 4
+  gpus_per_decode: 4
+infra:
+  etcd_nats_dedicated_node: true
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+backend:
+  type: vllm
+  connector: null
+  dp_launch_mode: per_gpu
+  prefill_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: '900'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  decode_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  vllm_config:
+    prefill:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both", "engine_id": "kimi-k26-prefill-dep4"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 4
+      data-parallel-rpc-port: 13346
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      enforce-eager: true
+      compilation-config: '{"custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      attention-config: '{"mla_prefill_backend": "TRTLLM_RAGGED"}'
+      gpu-memory-utilization: 0.93
+    decode:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 4
+      pipeline-parallel-size: 1
+      max-model-len: 9216
+      max-num-seqs: 2048
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      async-scheduling: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      gpu-memory-utilization: 0.93
+      stream-interval: 50
+      max-cudagraph-capture-size: 2048
+benchmark:
+  type: sa-bench
+  isl: 8192
+  osl: 1024
+  concurrencies: '32'
+  req_rate: inf
+  use_chat_template: true
diff --git a/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-2p1d-dep8-dep8-c8192.yaml b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-2p1d-dep8-dep8-c8192.yaml
new file mode 100644
index 000000000..54e623d76
--- /dev/null
+++ b/recipes/vllm/kimi-k2.6/b200-fp4/8k1k/disagg-b200-2p1d-dep8-dep8-c8192.yaml
@@ -0,0 +1,112 @@
+name: kimi-k2.6-vllm-disagg-b200-2p1d-dep8-dep8-c8192
+model:
+  path: kimi-k2.6-nvfp4
+  container: vllm/vllm-openai:v0.25.1
+  precision: fp4
+dynamo:
+  wheel: 1.3.0.dev20260721
+  install: true
+resources:
+  gpu_type: b200
+  gpus_per_node: 8
+  prefill_nodes: 2
+  decode_nodes: 1
+  prefill_workers: 2
+  decode_workers: 1
+  gpus_per_prefill: 8
+  gpus_per_decode: 8
+infra:
+  etcd_nats_dedicated_node: true
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+backend:
+  type: vllm
+  connector: null
+  dp_launch_mode: per_gpu
+  prefill_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: '900'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  decode_environment:
+    PYTHONUNBUFFERED: '1'
+    VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS: '0'
+    VLLM_USE_FLASHINFER_MOE_FP4: '1'
+    VLLM_USE_NCCL_SYMM_MEM: '0'
+    NCCL_CUMEM_ENABLE: '1'
+    NCCL_WATCHDOG_TIMEOUT: '1800'
+    TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC: '1800'
+    TORCH_CUDA_ARCH_LIST: '10.0'
+    PYTHONNOUSERSITE: '1'
+    UCX_MEMTYPE_CACHE: n
+    UCX_MEMTYPE_REG_WHOLE: n
+    UCX_CUDA_IPC_ENABLE_MNNVL: n
+    UCX_MAX_RMA_RAILS: '1'
+    UCX_MAX_RNDV_RAILS: '1'
+    UCX_RNDV_SCHEME: put_zcopy
+  vllm_config:
+    prefill:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13346
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      enforce-eager: true
+      compilation-config: '{"custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      max-num-batched-tokens: 16384
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      attention-config: '{"mla_prefill_backend": "TRTLLM_RAGGED"}'
+      gpu-memory-utilization: 0.9
+    decode:
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      served-model-name: nvidia/Kimi-K2.6-NVFP4
+      kv-cache-dtype: fp8
+      tensor-parallel-size: 1
+      pipeline-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      enable-expert-parallel: true
+      max-model-len: 10240
+      max-num-seqs: 2048
+      max-num-batched-tokens: 8192
+      safetensors-load-strategy: prefetch
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      no-enable-flashinfer-autotune: true
+      async-scheduling: true
+      attention-backend: FLASHINFER_MLA
+      block-size: 128
+      compilation-config: '{"cudagraph_mode":"FULL_DECODE_ONLY","custom_ops":["+quant_fp8","+rms_norm","+rotary_embedding"],"pass_config":{"fuse_attn_quant":true,"fuse_allreduce_rms":true}}'
+      gpu-memory-utilization: 0.9
+      stream-interval: 50
+      max-cudagraph-capture-size: 1024
+benchmark:
+  type: sa-bench
+  isl: 8192
+  osl: 1024
+  concurrencies: '8192'
+  req_rate: inf
+  use_chat_template: true