Weight Refit: Choosing a Transport#

Weight refit copies updated policy weights into the rollout model. Choose the topology first, then select one non-colocated transport with policy.generation.refit_transport.

Pick a Transport#

Topology	`refit_transport`	Transport	Use when
`colocated.enabled: true`	`null`	CUDA IPC or HTTP	Policy and rollout workers share GPUs; vLLM uses IPC and SGLang uses HTTP.
`colocated.enabled: false`	`null`	NCCL broadcast	You want the default full-weight path without extra dependencies.
`colocated.enabled: false`	`nccl_reshard`	NCCL reshard	Provides the best performance for large models (>100s B models).
`colocated.enabled: false`	`vllm_zmq_sparse`	Sparse delta over ZeroMQ	The link is bandwidth-limited and workers can reach a relay over TCP.
`colocated.enabled: false`	`vllm_s3_sparse`	Sparse delta through S3	Workers communicate through shared object storage.
`colocated.enabled: false`	`nixl`	NIXL checkpoint engine	The cluster has a fast UCX/RDMA fabric for full-weight refit.

null is the default. The sparse transports read only refit_cfg.sparse; NIXL reads only refit_cfg.nixl. Because one selector chooses the transport, sparse delta and NIXL cannot both be active.

Constraints#

Transport	Generation backend	Policy backend	Quantization and MoE
Colocated IPC/HTTP	vLLM or SGLang	DTensor or Megatron	Uses the generation backend’s standard loader.
NCCL	vLLM or Megatron	DTensor or Megatron	Uses the standard full-weight loader.
NCCL reshard	vLLM	Megatron	Requires matching BF16 or blockwise FP8 precision; Megatron ETP must be 1. Currently supporting Megatron+vLLM backends.
Sparse delta	vLLM	Megatron	BF16/FP16, unquantized rollout only.
NIXL, full weights	vLLM	DTensor or Megatron	Supports the standard full-weight FP8 loader. DTensor FP8 KV-cache scale transfer is not yet supported.
NIXL, sharded experts	vLLM	DTensor or Megatron	Unquantized BF16/FP16 Triton MoE only; FP8/MXFP8 and dynamic expert placement are rejected.

Non-colocated SGLang generation is not supported. The NIXL restrictions are on the generation backend; both Megatron and DTensor policy workers can send weights. Sparse delta is currently limited to GRPO. NIXL is initialized by the GRPO and distillation setup paths; PPO currently requires colocated generation.

Minimal Configuration#

Colocated refit needs no transport configuration:

policy:
  generation:
    colocated:
      enabled: true
    refit_transport: null

For non-colocated NCCL, change the topology and leave the selector unset:

policy:
  generation:
    colocated:
      enabled: false
    refit_transport: null

For NCCL reshard with Megatron policy training and vLLM generation:

policy:
  generation:
    colocated:
      enabled: false
    refit_transport: nccl_reshard

For sparse delta, select one data plane and configure its scope:

policy:
  generation:
    colocated:
      enabled: false
    refit_transport: vllm_zmq_sparse  # or vllm_s3_sparse
    refit_cfg:
      sparse:
        delta_compression:
          encoding: xor
        storage:
          s3_bucket: null  # required for vllm_s3_sparse

For NIXL, select the checkpoint engine and configure its scope:

policy:
  generation:
    colocated:
      enabled: false
    refit_transport: nixl
    refit_cfg:
      nixl:
        update_weights_bucket_memory_ratio: 0.05
        device: cuda
        backend_name: UCX
        release_after_refit: false
        shard_expert_weights: false

Learn More#

NCCL Reshard Refit describes its requirements, architecture, and shard-to-shard transfer.
Sparse Delta Refit explains baseline, compression, ZeroMQ, and S3 behavior.
Checkpoint-Engine Refit covers NIXL setup, performance tuning, FP8, sharded experts, and fault tolerance.
Checkpoint Engines describes the checkpoint-engine protocol and implementation.
Training and Generation Backends summarizes backend compatibility.