diff --git a/apps/grpo/qwen3_32b.yaml b/apps/grpo/qwen3_32b.yaml
index 593a2e1fb..e7a0cf509 100644
--- a/apps/grpo/qwen3_32b.yaml
+++ b/apps/grpo/qwen3_32b.yaml
@@ -3,10 +3,10 @@
 # NOTE - This has not been tested for correctness yet! All testing so far has been only for infrastructure stability
 
 # Global configuration
-group_size: 2
-local_batch_size: 8 # per-device batch size
-max_req_tokens: 512
-max_res_tokens: 512
+group_size: 16
+local_batch_size: 32 # per-device batch size
+max_req_tokens: 1024
+max_res_tokens: 1024
 model: "Qwen/Qwen3-32B"
 off_by_n: 1 # Off by one by default
 
@@ -14,7 +14,7 @@ provisioner:
   launcher: slurm
 
 # Main loop configuration
-rollout_threads: 1   # Recommended to set equal to policy.num_replicas
+rollout_threads: 32 # make this 4x the number of policy replicas seems to work well
 
 # Observability configuration
 metric_logging:
@@ -69,8 +69,8 @@ trainer:
     enable: false
   parallelism:
     data_parallel_replicate_degree: 1
-    data_parallel_shard_degree: -1
-    tensor_parallel_degree: 1
+    data_parallel_shard_degree: 1
+    tensor_parallel_degree: 8
     pipeline_parallel_degree: 1
     context_parallel_degree: 1
     expert_parallel_degree: 1
@@ -90,7 +90,7 @@ replay_buffer:
   batch_size: ${local_batch_size}
   max_policy_age: ${off_by_n}
   # dp_size: ${trainer.parallelism.data_parallel_shard_degree} # Must equal trainer DP degree
-  dp_size: 8
+  dp_size: 1
 
 # Reference model configuration
 ref_model:
@@ -119,7 +119,7 @@ ref_model:
 services:
   policy:
     procs: ${policy.engine_args.tensor_parallel_size}
-    num_replicas: 1
+    num_replicas: 4
     hosts: 1
     with_gpus: true
     mesh_name: policy