diff --git a/docs/advanced/lora.md b/docs/advanced/lora.md
index 4233407091..28ed547364 100644
--- a/docs/advanced/lora.md
+++ b/docs/advanced/lora.md
@@ -68,7 +68,7 @@ full-scale experiment evidence. It is not an exhaustive model whitelist.
 | Implementation | Model family | Architecture exercised | Evidence | Notes |
 |---|---|---|---|---|
 | Bridge | Qwen2.5 0.5B / 3B | Dense | [0.5B CUDA and ROCm E2E](https://github.com/radixark/miles/blob/main/tests/e2e/lora/test_lora_qwen2.5_0.5B.py), [3B disaggregated recipe](https://github.com/radixark/miles/blob/main/examples/lora/run-qwen2.5-3B-megatron-lora-disaggregated.sh) | The simplest starting point; `all-linear` works. |
-| Bridge | Qwen3 4B | Dense | [Single-LoRA recipe](https://github.com/radixark/miles/blob/main/examples/lora/run-qwen3-4B-megatron-lora.sh), [multi-LoRA recipe](https://github.com/radixark/miles/tree/main/examples/multi_lora) | Used by the current multi-adapter example. |
+| Bridge | Qwen3 4B | Dense | [Single-LoRA recipe](https://github.com/radixark/miles/blob/main/examples/lora/run-qwen3-4B-megatron-lora.sh), [AMD launcher](https://github.com/radixark/miles/blob/main/scripts/amd/run_qwen3_4b_lora.py), [multi-LoRA recipe](https://github.com/radixark/miles/tree/main/examples/multi_lora) | The AMD launcher uses Triton attention and LoRA backends. |
 | Bridge | GPT-OSS 20B | MoE | [Recipe](https://github.com/radixark/miles/blob/main/examples/lora/run-gpt-oss-20B-megatron-moe-lora.sh), [MoE LoRA E2E](https://github.com/radixark/miles/blob/main/tests/e2e/megatron/model_scripts/test_gpt_oss_20b_moe_lora_ci.py) | Uses the SGLang `triton` LoRA backend. |
 | Bridge | Kimi K2.5 | Multimodal MoE + MLA | [16-node recipe](https://github.com/radixark/miles/blob/main/examples/lora/run-kimi-k25-megatron-lora.sh) | Demonstrates shared-outer expert LoRA and an INT4 rollout / fake-QAT setup. |
 | Bridge | GLM-5 / 5.1 / 5.2 744B-A40B | MoE + MLA + DSA | [GLM-5.1 launcher](https://github.com/radixark/miles/blob/main/scripts/run_glm5_1_744b_a40b_lora.py), [GLM-5.2 launcher](https://github.com/radixark/miles/blob/main/scripts/run_glm5_2_744b_a40b_lora.py) | CI covers reduced 6-layer / 5-layer checkpoints; historical full-744B results are described below. |
diff --git a/scripts/amd/run_qwen3_4b_lora.py b/scripts/amd/run_qwen3_4b_lora.py
new file mode 100644
index 0000000000..bf9a7ddc52
--- /dev/null
+++ b/scripts/amd/run_qwen3_4b_lora.py
@@ -0,0 +1,250 @@
+"""Qwen3-4B GRPO LoRA training script for AMD (MI350X / MI355X).
+
+This is the AMD counterpart of
+``examples/lora/run-qwen3-4b-megatron-lora-result.sh``. It keeps the validated
+Megatron-Bridge LoRA recipe and pins SGLang's attention and LoRA backends to Triton,
+because the CUDA-only rollout backends are unavailable on ROCm.
+
+The checkpoint is loaded directly from Hugging Face through Megatron-Bridge; no converted
+Megatron checkpoint is required. ``full-train`` downloads the checkpoint and datasets
+before submitting the training job.
+
+Args:
+  --hardware: MI350X or MI355X, which fixes the default GPU count per node.
+  --num-gpus-per-node: Override the GPU count when only some devices are visible.
+  --wandb-team: W&B entity (personal account or team); needed if the API key has no
+    default entity.
+  --model-dir / --data-dir / --output-dir: Model, dataset, and run output directories.
+  --enable-eval: Evaluate AIME 2024 every 20 optimizer steps (default: on).
+
+Examples:
+  python scripts/amd/run_qwen3_4b_lora.py prepare
+  python scripts/amd/run_qwen3_4b_lora.py train --hardware MI355X --wandb-team my-entity
+  python scripts/amd/run_qwen3_4b_lora.py full-train --hardware MI355X --wandb-team my-entity
+"""
+
+import os
+import shlex
+from dataclasses import dataclass
+from typing import Literal
+
+import typer
+
+import miles.utils.external_utils.command_utils as U
+
+app = typer.Typer()
+
+_HF_REPO = "Qwen/Qwen3-4B"
+
+
+@dataclass
+class ScriptArgs(U.ExecuteTrainConfig):
+    run_id: str = U.create_run_id()
+    model_name: str = "Qwen3-4B"
+    megatron_model_type: str = "qwen3-4B"
+    hardware: Literal["auto", "MI350X", "MI355X"] = "auto"
+    num_gpus_per_node: int | None = None
+
+    model_dir: str = "/root/models"
+    data_dir: str = "/root/datasets"
+    megatron_path: str = "/root/Megatron-LM"
+    save_interval: int = 50
+
+    # LoRA: inherited from the validated Qwen3-4B Megatron LoRA recipe.
+    lora_rank: int = 64
+    lora_alpha: int = 32
+    lora_dropout: float = 0.0
+    target_modules: str = "all-linear"
+    lora_base_cpu_backup: bool = True
+
+    # Rollout and optimizer shape: 8 prompts x 8 samples = one 64-sample update.
+    num_rollout: int = 100
+    rollout_batch_size: int = 8
+    n_samples_per_prompt: int = 8
+    rollout_max_response_len: int = 8192
+    global_batch_size: int = 64
+    lr: float = 2e-5
+
+    # One 4B rollout engine per GPU.
+    rollout_num_gpus_per_engine: int = 1
+    sglang_mem_fraction_static: float = 0.4
+
+    enable_eval: bool = True
+    enable_wandb: bool = True
+    wandb_team: str | None = None
+    extra_args: str = ""
+
+
+def _set_rocm_environment() -> None:
+    """Preserve the caller's ROCm device selection through Ray startup."""
+    os.environ.setdefault("RAY_EXPERIMENTAL_NOSET_HIP_VISIBLE_DEVICES", "1")
+    os.environ.setdefault("RAY_EXPERIMENTAL_NOSET_CUDA_VISIBLE_DEVICES", "1")
+    if hip_visible_devices := os.environ.get("HIP_VISIBLE_DEVICES"):
+        os.environ["CUDA_VISIBLE_DEVICES"] = hip_visible_devices
+    # Avoid execute_train's NVIDIA topology probe and disable unsupported NVLink SHARP.
+    os.environ.setdefault("NCCL_NVLS_ENABLE", "0")
+
+
+def _resolve_num_gpus(args: ScriptArgs) -> tuple[str, int]:
+    hardware = U.resolve_hardware(args)
+    num_gpus = args.num_gpus_per_node or U.NUM_GPUS_OF_HARDWARE[hardware]
+    return hardware, num_gpus
+
+
+def _download_inputs(args: ScriptArgs) -> None:
+    U.exec_command_cpu(f"mkdir -p {args.model_dir} {args.data_dir}")
+    U.exec_command_cpu(f"hf download {_HF_REPO} --local-dir {args.model_dir}/{args.model_name}")
+    U.hf_download_dataset("zhuzilin/dapo-math-17k", data_dir=args.data_dir)
+    if args.enable_eval:
+        U.hf_download_dataset("zhuzilin/aime-2024", data_dir=args.data_dir)
+
+
+def _get_wandb_args(args: ScriptArgs) -> str:
+    if not args.enable_wandb:
+        return ""
+    wandb_args = U.get_default_wandb_args(__file__, run_id=args.run_id)
+    if wandb_args and args.wandb_team:
+        wandb_args += f"--wandb-team {shlex.quote(args.wandb_team)} "
+    return wandb_args
+
+
+def _execute(args: ScriptArgs) -> None:
+    _set_rocm_environment()
+    hardware, num_gpus = _resolve_num_gpus(args)
+    print(f"[run] Qwen3-4B LoRA on {hardware}: {num_gpus} GPUs, rollout TP=1")
+
+    checkpoint_dir = f"{args.output_dir}/{args.run_id}/checkpoints"
+    ckpt_args = (
+        f"--hf-checkpoint {args.model_dir}/{args.model_name} "
+        "--megatron-to-hf-mode bridge "
+        f"--save {checkpoint_dir} "
+        f"--save-interval {args.save_interval} "
+    )
+
+    lora_args = (
+        f"--lora-rank {args.lora_rank} "
+        f"--lora-alpha {args.lora_alpha} "
+        f"--lora-dropout {args.lora_dropout} "
+        f'--target-modules "{args.target_modules}" '
+    )
+    if args.lora_base_cpu_backup:
+        lora_args += "--lora-base-cpu-backup "
+
+    rollout_args = (
+        f"--prompt-data {args.data_dir}/dapo-math-17k/dapo-math-17k.jsonl "
+        "--input-key prompt "
+        "--label-key label "
+        "--apply-chat-template "
+        "--rollout-shuffle "
+        "--balance-data "
+        "--rm-type deepscaler "
+        f"--num-rollout {args.num_rollout} "
+        f"--rollout-batch-size {args.rollout_batch_size} "
+        f"--n-samples-per-prompt {args.n_samples_per_prompt} "
+        f"--rollout-max-response-len {args.rollout_max_response_len} "
+        "--rollout-temperature 1 "
+        f"--global-batch-size {args.global_batch_size} "
+    )
+
+    eval_args = ""
+    if args.enable_eval:
+        eval_args = (
+            "--eval-interval 20 "
+            f"--eval-prompt-data aime24 {args.data_dir}/aime-2024/aime-2024.jsonl "
+            "--n-samples-per-eval-prompt 16 "
+            "--eval-max-response-len 16384 "
+            "--eval-top-p 1 "
+        )
+
+    optimizer_args = (
+        "--optimizer adam "
+        f"--lr {args.lr} "
+        "--lr-decay-style constant "
+        "--weight-decay 0.1 "
+        "--adam-beta1 0.9 "
+        "--adam-beta2 0.98 "
+    )
+
+    grpo_args = (
+        "--advantage-estimator grpo "
+        "--kl-loss-coef 0.00 "
+        "--kl-loss-type low_var_kl "
+        "--kl-coef 0.00 "
+        "--entropy-coef 0.00 "
+        "--eps-clip 0.2 "
+        "--eps-clip-high 0.28 "
+    )
+
+    sglang_args = (
+        f"--rollout-num-gpus-per-engine {args.rollout_num_gpus_per_engine} "
+        f"--sglang-mem-fraction-static {args.sglang_mem_fraction_static} "
+        "--sglang-decode-log-interval 1000 "
+        "--sglang-chunked-prefill-size 4096 "
+        "--sglang-lora-backend triton "
+        "--sglang-attention-backend triton "
+    )
+
+    misc_args = (
+        "--train-backend megatron "
+        "--attention-dropout 0.0 "
+        "--hidden-dropout 0.0 "
+        "--accumulate-allreduce-grads-in-fp32 "
+        "--attention-softmax-in-fp32 "
+        "--calculate-per-token-loss "
+        f"--actor-num-nodes {args.num_nodes} "
+        f"--actor-num-gpus-per-node {num_gpus} "
+        f"--num-gpus-per-node {num_gpus} "
+        "--colocate "
+    )
+
+    train_args = (
+        f"{ckpt_args} "
+        f"{lora_args} "
+        f"{rollout_args} "
+        f"{eval_args} "
+        f"{optimizer_args} "
+        f"{grpo_args} "
+        f"{_get_wandb_args(args)} "
+        f"{sglang_args} "
+        f"{misc_args} "
+        f"{args.extra_args} "
+    )
+
+    U.execute_train(
+        train_args=train_args,
+        config=args,
+        num_gpus_per_node=num_gpus,
+        megatron_model_type=args.megatron_model_type,
+        megatron_path=args.megatron_path,
+    )
+
+
+@app.command()
+@U.dataclass_cli
+def prepare(args: ScriptArgs) -> None:
+    """Download Qwen3-4B and the configured training/evaluation datasets."""
+    _download_inputs(args)
+
+
+@app.command()
+@U.dataclass_cli
+def train(args: ScriptArgs) -> None:
+    """Run GRPO LoRA training using inputs already present on the node."""
+    _execute(args)
+
+
+@app.command()
+@U.dataclass_cli
+def full_train(args: ScriptArgs) -> None:
+    """Download the inputs and run GRPO LoRA training."""
+    _download_inputs(args)
+    _execute(args)
+
+
+@app.callback()
+def _callback() -> None:
+    pass
+
+
+if __name__ == "__main__":
+    app()
diff --git a/tests/manual/launch_scripts/test_py_launch_scripts.py b/tests/manual/launch_scripts/test_py_launch_scripts.py
index 3d215e2e32..326cbcae9a 100644
--- a/tests/manual/launch_scripts/test_py_launch_scripts.py
+++ b/tests/manual/launch_scripts/test_py_launch_scripts.py
@@ -70,6 +70,7 @@ _SCRIPTS_WHOSE_DEFAULTS_ARE_UNSUPPORTED: dict[str, Callable[[Path], dict[str, ob
 _HARDWARE_A_RECORDING_REPRESENTS = {
     "scripts/amd/run_qwen3_30b_a3b.py": "MI355X",
     "scripts/amd/run_qwen3_4b.py": "MI355X",
+    "scripts/amd/run_qwen3_4b_lora.py": "MI355X",
     "scripts/run_deepseek_v32.py": "B200",
     "scripts/run_glm45_355b_a32b.py": "GB200",
     "scripts/run_joy_ai_llm_flash.py": "B200",
diff --git a/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/full_train.txt b/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/full_train.txt
new file mode 100644
index 0000000000..5f2ddb309c
--- /dev/null
+++ b/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/full_train.txt
@@ -0,0 +1,109 @@
+### 0
+mkdir -p /root/models /root/datasets
+
+### 1
+hf download Qwen/Qwen3-4B
+  --local-dir /root/models/Qwen3-4B
+
+### 2
+hf download
+  --repo-type dataset zhuzilin/dapo-math-17k
+  --local-dir /root/datasets/dapo-math-17k
+
+### 3
+hf download
+  --repo-type dataset zhuzilin/aime-2024
+  --local-dir /root/datasets/aime-2024
+
+### 4
+pkill -9 sglang; sleep 3; ray stop
+  --force; pkill -9 ray; pkill -9 miles; sleep 3; pkill -9 ray; pkill -9 miles; pkill -9 redis; true; 
+
+### 5
+export PYTHONUNBUFFERED=1 && ray start
+  --head
+  --node-ip-address 127.0.0.1
+  --num-gpus 8
+  --disable-usage-stats
+
+### 6
+export no_proxy=127.0.0.1 && export PYTHONUNBUFFERED=1 && ray job submit
+  --address="http://127.0.0.1:8265"
+  --runtime-env-json='{"env_vars": {"PYTHONUNBUFFERED": "1", "CUDA_DEVICE_MAX_CONNECTIONS": "1", "NCCL_NVLS_ENABLE": "0", "no_proxy": "127.0.0.1,127.0.0.1", "MASTER_ADDR": "127.0.0.1", "PYTHONPATH": "<REPO_ROOT>:/root/Megatron-LM:/frozen/pythonpath"}}'
+  -- python3 <REPO_ROOT>/train.py
+  --swiglu
+  --num-layers 36
+  --hidden-size 2560
+  --ffn-hidden-size 9728
+  --num-attention-heads 32
+  --group-query-attention
+  --num-query-groups 8
+  --use-rotary-position-embeddings
+  --disable-bias-linear
+  --normalization RMSNorm
+  --norm-epsilon 1e-6
+  --rotary-base 1000000
+  --vocab-size 151936
+  --kv-channels 128
+  --qk-layernorm
+  --hf-checkpoint /root/models/Qwen3-4B
+  --megatron-to-hf-mode bridge
+  --save /root/shared_data/260101-000000-000/checkpoints
+  --save-interval 50 
+  --lora-rank 64
+  --lora-alpha 32
+  --lora-dropout 0.0
+  --target-modules "all-linear"
+  --lora-base-cpu-backup 
+  --prompt-data /root/datasets/dapo-math-17k/dapo-math-17k.jsonl
+  --input-key prompt
+  --label-key label
+  --apply-chat-template
+  --rollout-shuffle
+  --balance-data
+  --rm-type deepscaler
+  --num-rollout 100
+  --rollout-batch-size 8
+  --n-samples-per-prompt 8
+  --rollout-max-response-len 8192
+  --rollout-temperature 1
+  --global-batch-size 64 
+  --eval-interval 20
+  --eval-prompt-data aime24 /root/datasets/aime-2024/aime-2024.jsonl
+  --n-samples-per-eval-prompt 16
+  --eval-max-response-len 16384
+  --eval-top-p 1 
+  --optimizer adam
+  --lr 2e-05
+  --lr-decay-style constant
+  --weight-decay 0.1
+  --adam-beta1 0.9
+  --adam-beta2 0.98 
+  --advantage-estimator grpo
+  --kl-loss-coef 0.00
+  --kl-loss-type low_var_kl
+  --kl-coef 0.00
+  --entropy-coef 0.00
+  --eps-clip 0.2
+  --eps-clip-high 0.28 
+  --use-wandb
+  --wandb-project miles-run_qwen3_4b_lora
+  --wandb-group 260101-000000-000
+  --wandb-key 'frozen-wandb-api-key'
+  --disable-wandb-random-suffix 
+  --rollout-num-gpus-per-engine 1
+  --sglang-mem-fraction-static 0.4
+  --sglang-decode-log-interval 1000
+  --sglang-chunked-prefill-size 4096
+  --sglang-lora-backend triton
+  --sglang-attention-backend triton 
+  --train-backend megatron
+  --attention-dropout 0.0
+  --hidden-dropout 0.0
+  --accumulate-allreduce-grads-in-fp32
+  --attention-softmax-in-fp32
+  --calculate-per-token-loss
+  --actor-num-nodes 1
+  --actor-num-gpus-per-node 8
+  --num-gpus-per-node 8
+  --colocate   
diff --git a/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/prepare.txt b/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/prepare.txt
new file mode 100644
index 0000000000..d44879608a
--- /dev/null
+++ b/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/prepare.txt
@@ -0,0 +1,16 @@
+### 0
+mkdir -p /root/models /root/datasets
+
+### 1
+hf download Qwen/Qwen3-4B
+  --local-dir /root/models/Qwen3-4B
+
+### 2
+hf download
+  --repo-type dataset zhuzilin/dapo-math-17k
+  --local-dir /root/datasets/dapo-math-17k
+
+### 3
+hf download
+  --repo-type dataset zhuzilin/aime-2024
+  --local-dir /root/datasets/aime-2024
diff --git a/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/train.txt b/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/train.txt
new file mode 100644
index 0000000000..d280735657
--- /dev/null
+++ b/tests/snapshots/launch_scripts/py/scripts/amd/run_qwen3_4b_lora.py/train.txt
@@ -0,0 +1,92 @@
+### 0
+pkill -9 sglang; sleep 3; ray stop
+  --force; pkill -9 ray; pkill -9 miles; sleep 3; pkill -9 ray; pkill -9 miles; pkill -9 redis; true; 
+
+### 1
+export PYTHONUNBUFFERED=1 && ray start
+  --head
+  --node-ip-address 127.0.0.1
+  --num-gpus 8
+  --disable-usage-stats
+
+### 2
+export no_proxy=127.0.0.1 && export PYTHONUNBUFFERED=1 && ray job submit
+  --address="http://127.0.0.1:8265"
+  --runtime-env-json='{"env_vars": {"PYTHONUNBUFFERED": "1", "CUDA_DEVICE_MAX_CONNECTIONS": "1", "NCCL_NVLS_ENABLE": "0", "no_proxy": "127.0.0.1,127.0.0.1", "MASTER_ADDR": "127.0.0.1", "PYTHONPATH": "<REPO_ROOT>:/root/Megatron-LM:/frozen/pythonpath"}}'
+  -- python3 <REPO_ROOT>/train.py
+  --swiglu
+  --num-layers 36
+  --hidden-size 2560
+  --ffn-hidden-size 9728
+  --num-attention-heads 32
+  --group-query-attention
+  --num-query-groups 8
+  --use-rotary-position-embeddings
+  --disable-bias-linear
+  --normalization RMSNorm
+  --norm-epsilon 1e-6
+  --rotary-base 1000000
+  --vocab-size 151936
+  --kv-channels 128
+  --qk-layernorm
+  --hf-checkpoint /root/models/Qwen3-4B
+  --megatron-to-hf-mode bridge
+  --save /root/shared_data/260101-000000-000/checkpoints
+  --save-interval 50 
+  --lora-rank 64
+  --lora-alpha 32
+  --lora-dropout 0.0
+  --target-modules "all-linear"
+  --lora-base-cpu-backup 
+  --prompt-data /root/datasets/dapo-math-17k/dapo-math-17k.jsonl
+  --input-key prompt
+  --label-key label
+  --apply-chat-template
+  --rollout-shuffle
+  --balance-data
+  --rm-type deepscaler
+  --num-rollout 100
+  --rollout-batch-size 8
+  --n-samples-per-prompt 8
+  --rollout-max-response-len 8192
+  --rollout-temperature 1
+  --global-batch-size 64 
+  --eval-interval 20
+  --eval-prompt-data aime24 /root/datasets/aime-2024/aime-2024.jsonl
+  --n-samples-per-eval-prompt 16
+  --eval-max-response-len 16384
+  --eval-top-p 1 
+  --optimizer adam
+  --lr 2e-05
+  --lr-decay-style constant
+  --weight-decay 0.1
+  --adam-beta1 0.9
+  --adam-beta2 0.98 
+  --advantage-estimator grpo
+  --kl-loss-coef 0.00
+  --kl-loss-type low_var_kl
+  --kl-coef 0.00
+  --entropy-coef 0.00
+  --eps-clip 0.2
+  --eps-clip-high 0.28 
+  --use-wandb
+  --wandb-project miles-run_qwen3_4b_lora
+  --wandb-group 260101-000000-000
+  --wandb-key 'frozen-wandb-api-key'
+  --disable-wandb-random-suffix 
+  --rollout-num-gpus-per-engine 1
+  --sglang-mem-fraction-static 0.4
+  --sglang-decode-log-interval 1000
+  --sglang-chunked-prefill-size 4096
+  --sglang-lora-backend triton
+  --sglang-attention-backend triton 
+  --train-backend megatron
+  --attention-dropout 0.0
+  --hidden-dropout 0.0
+  --accumulate-allreduce-grads-in-fp32
+  --attention-softmax-in-fp32
+  --calculate-per-token-loss
+  --actor-num-nodes 1
+  --actor-num-gpus-per-node 8
+  --num-gpus-per-node 8
+  --colocate