From 22514767c3e139fcd658d2309107a8b232ebfd8e Mon Sep 17 00:00:00 2001
From: richardhuo-nv <rihuo@nvidia.com>
Date: Mon, 15 Jun 2026 12:30:12 -0700
Subject: [PATCH 1/2] add configs

add env var

update install configs

update model and container configs

rm ep
---
 .../b300-fp8/1k1k/1p1d-dep2-tep8-1k1k.yaml    | 80 ++++++++++++++++++
 .../b300-fp8/1k1k/1p2d-dep2-dep4-1k1k.yaml    | 81 +++++++++++++++++++
 .../b300-fp8/1k1k/2p1d-dep2-dep8-1k1k.yaml    | 81 +++++++++++++++++++
 .../b300-fp8/1k1k/2p1d-dep2-tep8-1k1k.yaml    | 80 ++++++++++++++++++
 .../b300-fp8/1k1k/2p2d-dep2-tep8-1k1k.yaml    | 80 ++++++++++++++++++
 .../b300-fp8/1k1k/3p2d-dep2-tep8-1k1k.yaml    | 80 ++++++++++++++++++
 6 files changed, 482 insertions(+)
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/1k1k/1p1d-dep2-tep8-1k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/1k1k/1p2d-dep2-dep4-1k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-dep8-1k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-tep8-1k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/1k1k/2p2d-dep2-tep8-1k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/1k1k/3p2d-dep2-tep8-1k1k.yaml

diff --git a/recipes/vllm/minimax-m3/b300-fp8/1k1k/1p1d-dep2-tep8-1k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/1k1k/1p1d-dep2-tep8-1k1k.yaml
new file mode 100644
index 000000000..7f93d1aa1
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/1k1k/1p1d-dep2-tep8-1k1k.yaml
@@ -0,0 +1,80 @@
+name: "minimax-m3-vllm-disagg-b300-1p1d-fp8-dep2-tep8-1k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 1
+  decode_workers: 1
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  decode_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 2048
+
+    decode:
+      tensor-parallel-size: 8
+      enable-expert-parallel: true
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 4096
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 8196
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 1024
+  osl: 1024
+  concurrencies: "4x16x64x128x4096"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/1k1k/1p2d-dep2-dep4-1k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/1k1k/1p2d-dep2-dep4-1k1k.yaml
new file mode 100644
index 000000000..8dc458eab
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/1k1k/1p2d-dep2-dep4-1k1k.yaml
@@ -0,0 +1,81 @@
+name: "minimax-m3-vllm-disagg-b300-1p2d-fp8-dep2-dep4-1k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 1
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 4
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  decode_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 2048
+
+    decode:
+      tensor-parallel-size: 1
+      data-parallel-size: 4
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 8196
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 1024
+  osl: 1024
+  concurrencies: "2048"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-dep8-1k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-dep8-1k1k.yaml
new file mode 100644
index 000000000..afe1c3e49
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-dep8-1k1k.yaml
@@ -0,0 +1,81 @@
+name: "minimax-m3-vllm-disagg-b300-2p1d-fp8-dep2-dep8-1k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 2
+  decode_workers: 1
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  decode_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 2048
+
+    decode:
+      tensor-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 4096
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 8196
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 1024
+  osl: 1024
+  concurrencies: "512x4096"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-tep8-1k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-tep8-1k1k.yaml
new file mode 100644
index 000000000..7a2d87740
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p1d-dep2-tep8-1k1k.yaml
@@ -0,0 +1,80 @@
+name: "minimax-m3-vllm-disagg-b300-2p1d-fp8-dep2-tep8-1k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 2
+  decode_workers: 1
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  decode_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 2048
+
+    decode:
+      tensor-parallel-size: 8
+      enable-expert-parallel: true
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 4096
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 8196
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 1024
+  osl: 1024
+  concurrencies: "32"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p2d-dep2-tep8-1k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p2d-dep2-tep8-1k1k.yaml
new file mode 100644
index 000000000..33435b328
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/1k1k/2p2d-dep2-tep8-1k1k.yaml
@@ -0,0 +1,80 @@
+name: "minimax-m3-vllm-disagg-b300-2p2d-fp8-dep2-tep8-1k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 2
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  decode_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 2048
+
+    decode:
+      tensor-parallel-size: 8
+      enable-expert-parallel: true
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 4096
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 8196
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 1024
+  osl: 1024
+  concurrencies: "16"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/1k1k/3p2d-dep2-tep8-1k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/1k1k/3p2d-dep2-tep8-1k1k.yaml
new file mode 100644
index 000000000..ac98b9cc8
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/1k1k/3p2d-dep2-tep8-1k1k.yaml
@@ -0,0 +1,80 @@
+name: "minimax-m3-vllm-disagg-b300-3p2d-fp8-dep2-tep8-1k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 3
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  decode_environment:
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+    VLLM_FLOAT32_MATMUL_PRECISION: "high"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 2048
+
+    decode:
+      tensor-parallel-size: 8
+      enable-expert-parallel: true
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 2304
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 4096
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 8196
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 1024
+  osl: 1024
+  concurrencies: "4"
+  req_rate: "inf"

From 5caabe364e1ef531fab9926c75e32ae8927b1553 Mon Sep 17 00:00:00 2001
From: richardhuo-nv <rihuo@nvidia.com>
Date: Tue, 16 Jun 2026 10:38:28 -0700
Subject: [PATCH 2/2] add 8k1k receipes

---
 .../b300-fp8/8k1k/1p2d-dep2-dep8-8k1k.yaml    | 81 +++++++++++++++++++
 .../b300-fp8/8k1k/2p2d-dep2-dep8-8k1k.yaml    | 81 +++++++++++++++++++
 .../b300-fp8/8k1k/2p2d-dep2-tep8-8k1k.yaml    | 80 ++++++++++++++++++
 .../b300-fp8/8k1k/3p2d-dep2-dep8-8k1k.yaml    | 81 +++++++++++++++++++
 .../b300-fp8/8k1k/3p2d-dep2-tep8-8k1k.yaml    | 80 ++++++++++++++++++
 .../b300-fp8/8k1k/4p2d-dep2-dep8-8k1k.yaml    | 81 +++++++++++++++++++
 .../b300-fp8/8k1k/4p3d-dep2-dep4-8k1k.yaml    | 81 +++++++++++++++++++
 .../b300-fp8/8k1k/5p2d-dep2-tep8-8k1k.yaml    | 80 ++++++++++++++++++
 8 files changed, 645 insertions(+)
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/1p2d-dep2-dep8-8k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-dep8-8k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-tep8-8k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-dep8-8k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-tep8-8k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/4p2d-dep2-dep8-8k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/4p3d-dep2-dep4-8k1k.yaml
 create mode 100644 recipes/vllm/minimax-m3/b300-fp8/8k1k/5p2d-dep2-tep8-8k1k.yaml

diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/1p2d-dep2-dep8-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/1p2d-dep2-dep8-8k1k.yaml
new file mode 100644
index 000000000..cb9256e25
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/1p2d-dep2-dep8-8k1k.yaml
@@ -0,0 +1,81 @@
+name: "minimax-m3-vllm-disagg-b300-1p2d-fp8-dep2-dep8-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 1
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "128"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-dep8-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-dep8-8k1k.yaml
new file mode 100644
index 000000000..7a805df7f
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-dep8-8k1k.yaml
@@ -0,0 +1,81 @@
+name: "minimax-m3-vllm-disagg-b300-2p2d-fp8-dep2-dep8-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 2
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "256x512"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-tep8-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-tep8-8k1k.yaml
new file mode 100644
index 000000000..8dc4c5c06
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/2p2d-dep2-tep8-8k1k.yaml
@@ -0,0 +1,80 @@
+name: "minimax-m3-vllm-disagg-b300-2p2d-fp8-dep2-tep8-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 2
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 8
+      enable-expert-parallel: true
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "16"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-dep8-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-dep8-8k1k.yaml
new file mode 100644
index 000000000..8ff86e9d9
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-dep8-8k1k.yaml
@@ -0,0 +1,81 @@
+name: "minimax-m3-vllm-disagg-b300-3p2d-fp8-dep2-dep8-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 3
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "512"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-tep8-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-tep8-8k1k.yaml
new file mode 100644
index 000000000..a90bfcf32
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/3p2d-dep2-tep8-8k1k.yaml
@@ -0,0 +1,80 @@
+name: "minimax-m3-vllm-disagg-b300-3p2d-fp8-dep2-tep8-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 3
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 8
+      enable-expert-parallel: true
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "32"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/4p2d-dep2-dep8-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/4p2d-dep2-dep8-8k1k.yaml
new file mode 100644
index 000000000..8feb79b71
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/4p2d-dep2-dep8-8k1k.yaml
@@ -0,0 +1,81 @@
+name: "minimax-m3-vllm-disagg-b300-4p2d-fp8-dep2-dep8-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 4
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 1
+      data-parallel-size: 8
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "4096"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/4p3d-dep2-dep4-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/4p3d-dep2-dep4-8k1k.yaml
new file mode 100644
index 000000000..5639c2eda
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/4p3d-dep2-dep4-8k1k.yaml
@@ -0,0 +1,81 @@
+name: "minimax-m3-vllm-disagg-b300-4p3d-fp8-dep2-dep4-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 2
+  prefill_workers: 4
+  decode_workers: 3
+  gpus_per_prefill: 2
+  gpus_per_decode: 4
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 1
+      data-parallel-size: 4
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 512
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "4096"
+  req_rate: "inf"
diff --git a/recipes/vllm/minimax-m3/b300-fp8/8k1k/5p2d-dep2-tep8-8k1k.yaml b/recipes/vllm/minimax-m3/b300-fp8/8k1k/5p2d-dep2-tep8-8k1k.yaml
new file mode 100644
index 000000000..1f517d815
--- /dev/null
+++ b/recipes/vllm/minimax-m3/b300-fp8/8k1k/5p2d-dep2-tep8-8k1k.yaml
@@ -0,0 +1,80 @@
+name: "minimax-m3-vllm-disagg-b300-5p2d-fp8-dep2-tep8-8k1k"
+
+model:
+  path: "MiniMaxAI/MiniMax-M3-MXFP8"
+  container: "vllm/vllm-openai:minimax-m3"
+  precision: "fp8"
+
+resources:
+  gpu_type: "b300"
+  gpus_per_node: 8
+  prefill_nodes: 2
+  decode_nodes: 2
+  prefill_workers: 5
+  decode_workers: 2
+  gpus_per_prefill: 2
+  gpus_per_decode: 8
+
+dynamo:
+  install: true
+  version: 1.3.0.dev20260614
+
+frontend:
+  type: dynamo
+  enable_multiple_frontends: false
+
+backend:
+  type: vllm
+  connector: null
+
+  prefill_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  decode_environment:
+    VLLM_FLOAT32_MATMUL_PRECISION: high
+    UCX_NET_DEVICES: "all"
+    UCX_TLS: "rc,cuda_ipc,cuda_copy,sm,self,tcp"
+
+  vllm_config:
+    prefill:
+      tensor-parallel-size: 1
+      data-parallel-size: 2
+      data-parallel-rpc-port: 13345
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-cudagraph-capture-size: 2048
+      max-num-batched-tokens: 16384
+
+    decode:
+      tensor-parallel-size: 8
+      enable-expert-parallel: true
+      trust-remote-code: true
+      no-enable-prefix-caching: true
+      kv-transfer-config: '{"kv_connector": "NixlConnector", "kv_role": "kv_both"}'
+      block-size: 128
+      gpu-memory-utilization: 0.90
+      max-model-len: 9472
+      language-model-only: true
+      stream-interval: 32
+      max-num-seqs: 1024
+      max-num-batched-tokens: 16384
+      max-cudagraph-capture-size: 4096
+
+health_check:
+  max_attempts: 360
+  interval_seconds: 10
+
+benchmark:
+  type: "sa-bench"
+  isl: 8192
+  osl: 1024
+  concurrencies: "4x64"
+  req_rate: "inf"