Compatibility matrix#
This page lists the exact versions Infera 0.1.0 has been validated against. Everything here is what we have tested — combinations not listed are outside the validated set for this release, not necessarily unsupported.
Two ROCm baselines are covered. ROCm 7.2 is the release baseline: all three engines, every scenario. ROCm 10.1 is an early-enablement preview on nightly vendor bases, validated over a deliberately narrow scope — see ROCm 10.1 preview for exactly how narrow.
How to read this page
Where a component is pinned to a specific image tag, use that exact artifact. The
validated engine images bundle the Infera connector, the sitecustomize hook,
and the RDMA transport shims on top of the vendor ROCm base — so the tag is the
tested unit, not just the engine version inside it.
Engines#
Infera orchestrates one or more engines. Install at least one. The 0.1.0 release is validated against these engine versions and images.
vLLM |
SGLang |
ATOM |
|
|---|---|---|---|
Engine version |
0.25.1 |
0.5.18 (MI355X) / 0.5.16 (MI325X) |
0.1.4 |
Docker image |
|
|
|
ROCm (image base) |
7.2.3 |
7.2.0 |
7.2.4 |
OS (image base) |
Ubuntu 22.04.5 |
Ubuntu 22.04.5 |
Ubuntu 24.04.4 |
Python (image base) |
3.12.13 |
3.10.12 |
3.12.3 |
PyTorch (image base) |
2.11.0 |
2.9.1 |
2.10.0 |
vLLM |
SGLang |
ATOM |
|
|---|---|---|---|
Engine version |
0.26.1.dev0 ( |
0.5.15.post1 ( |
not validated |
Docker image |
|
|
— |
ROCm (image base) |
10.1.0 (nightly |
10.1.0 (nightly |
— |
OS (image base) |
Ubuntu 24.04.4 |
Ubuntu 24.04.4 |
— |
Python (image base) |
3.14.7 |
3.14.6 |
— |
PyTorch (image base) |
2.12.0+rocm10.1.0a20260807 |
2.12.0+rocm10.1.0a20260811 |
— |
Build date |
2026-08-08 |
2026-08-11 |
— |
These are nightly tags in an access-gated repository, so the tag alone is not a version. Build against the digest:
rocm/ufb-private:vllm-0.26.0-ubuntu24.04-py3.14-nightlies-device-all-cdna-rocm10.1.0a20260807-568afb3a1@sha256:11657b464b9c2b7f285a68ca1f622f2cdf3c5ef30a48cc6e560c4141acca8556
rocm/ufb-private:sglang-v0.5.15.post1-ubuntu24.04-py3.14-nightlies-device-all-rocm10.1.0a20260811-e35a33b34a@sha256:e87ecda2624687727d253e0c74863dd7f5008759ab09a9f7bc14e3360de181b6
OS / Python / PyTorch above were read from inside each validated base image (not the tag). See the platform table below for the baseline that applies across all engines.
Engine images bundle more than the engine
The validated engine images layer the Infera connector, the sitecustomize
hook, and the Mooncake / ionic RDMA shims on top of the vendor ROCm base. For
serving, prefer the prebuilt image over a manual pip install of the engine.
See Deployment → Engine images.
Platform#
Component |
Validated version |
|---|---|
GPU |
AMD Instinct MI355X ( |
ROCm |
7.2 — plus a 10.1 nightly preview (below) |
Operating system |
Ubuntu 24.04 (Linux x86-64) |
Python |
3.10+ |
Docker |
Required — runs |
RDMA NIC |
AMD AINIC — required only for cross-node prefill-decode |
ROCm 10.1 preview#
ROCm 10.1 changes how ROCm itself ships. It arrives as a pip wheel
(_rocm_sdk_devel under site-packages, with ROCM_HOME pointing at it) and the
bases carry no /opt/rocm; Python moves to 3.14. The Infera engine images
restore /opt/rocm as a symlink, because third-party code that hardcodes the
path degrades silently rather than erroring.
Validated with gpt-oss-120b on 2 × 8 MI355X (gfx950), both engines, both
serving topologies:
Scenario |
vLLM |
SGLang |
|---|---|---|
Aggregated — prefill + decode in one worker |
✅ PASS · 169 s |
✅ PASS · 342 s |
Disaggregated — prefill and decode on separate nodes |
✅ PASS · 166 s |
✅ PASS · 367 s |
Both disaggregated runs were confirmed to carry KV over RDMA rather than silently falling back to TCP, and all four runs’ correctness probes passed.
Outside the ROCm 10.1 preview scope
Models — gpt-oss-120b only. GLM-5.2 and DeepSeek-v4 are not covered: the 10.1 SGLang base is v0.5.15.post1, while the DSA patch set Infera applies for those models is pinned against v0.5.17.
aiter sampling (vLLM) — every 10.1 vLLM run passes
--use-fp64-gumbel. aiter’s top-k/top-p kernel does not build against 10.1’s hipCUB, so sampling falls to the PyTorch implementation. This is an upstream aiter issue; MXFP4 MoE still runs through aiter.kvd GPU-direct tier — not built into the 10.1 images.
ATOM — not exercised on 10.1.
gfx942— the same bases and scenarios also passed on 8 × MI300X, but that path needs image-side patches and aiter overrides which are not part of this release’s images.
Infera#
Package |
Validated version |
|---|---|
|
0.1.0 |