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[VOTE] Release Apache TVM v0.25.0.rc1 #19802
Description
Dear TVM community,
This is a call for vote to release Apache TVM version v0.25.0.
This v0.25.0.rc1 candidate supersedes v0.25.0.rc0, incorporating additional commits merged onto the release branch since rc0.
Release highlights:
- Deeper tvm-ffi integration: the arithmetic
Analyzeris now a tvm-ffiObject, structural APIs and IRModule JSON serialization are routed directly through tvm-ffi, and related FFI/header cleanups across the codebase. - TIRx infrastructure bring-up: initial TIRx infra with op-dispatch / codegen / TVMScript follow-ups and updated scoped ops and CUDA launch bounds.
- Major Relax TFLite frontend expansion: LSTM / RNN / SVDF, Conv3D and CONV_3D_TRANSPOSE, REDUCE_WINDOW, quantized import via QDQ decomposition, resource variables / static hashtables, embedding-lookup-sparse, segment ops, and StableHLO + control-flow multi-subgraph support.
- Relax ONNX correctness and ONNX Runtime parity: NaN/Inf handling for Sign / Cast / Clip / Div, RMSNormalization (opset 23), TopK scalar-K, Gather negative indices, ScatterElements reduction, NonMaxSuppression defaults, plus systematic ONNX backend tests.
- Relax PyTorch fixes: segfault in
from_exported_programwithindex_put_,correctionin std/var, multi-axisflip,logical_not, and integerpowdecomposition. - TIR / codegen: cooperative_tensor builtins with a
metal.cooperative_tensorstorage scope; CUDA fast-math intrinsic lowering gated behind a target/PassContext option; LLVM transcendental functions (sinh/cosh/atan/asin/acos/erf) routed through libm; Vulkan barrier fix. - Arithmetic robustness: memoized IntervalSet variable relaxation to avoid exponential blowup, and a canonical-simplify correctness fix.
- Runtime / build: device runtime modularized into per-backend DSOs.
- WebGPU/WASM: OPFS synchronous access handles and committed records, and persistent URL→hash mapping across page loads.
- Security: fix missing
exportedflag in AndroidManifest; bound RPC tracker message size.
Link to release candidate:
https://dist.apache.org/repos/dist/dev/tvm/tvm-v0.25.0-rc1/
Link to GitHub pre-release page (full release notes):
https://github.com/apache/tvm/releases/tag/v0.25.0.rc1
Everyone is welcomed to vote. Please vote by replying to this thread explicitly. According to release procedure, for the dev@ vote, there must be at least 3 binding +1 votes and more +1 votes than -1 votes.
+1 = approve
+0 = no opinion
-1 = disapprove (provide reason)
NOTE: this thread is being mirrored in dev@
As we are carrying over the votes from the v0.25.0.rc0 voting thread, this vote will remain open for 48 hours.
Activity
tlopex commentedon Jun 16, 2026
+1
tqchen commentedon Jun 17, 2026
+1
MasterJH5574 commentedon Jun 17, 2026
Source build check for v0.25.0.rc1, with
tests/scripts/release/test_release_package.shas shipped in the release candidate:https://github.com/apache/tvm/blob/v0.25.0.rc1/tests/scripts/release/test_release_package.sh
LGTM — md5 (github vs apache.org) identical, GPG signature good (verified against the dev KEYS), sha512 OK, no binaries in source, full compile, and
import tvmsucceeds.MasterJH5574 commentedon Jun 17, 2026
Hello folks, I added a cmake fix into rc1 that only affects wheel packaging build. Since this patch does not affect most of the cases, I retagged v0.25.0.rc1 to move it one commit forward.
mshr-h commentedon Jun 17, 2026
+1
Verified locally on DGX Spark.
MasterJH5574 commentedon Jun 17, 2026
Wheel install check for v0.25.0.rc1 — PyPI.
Pre-release wheels are also published on PyPI for testing:
pip install --pre apache-tvm==0.25.0rc1All four platform wheels published for
apache-tvm==0.25.0rc1(macOS arm64, Linux x86_64 + aarch64 manylinux_2_28, Windows AMD64). Installed the Linux x86_64 wheel in a clean venv — dependencies (includingapache-tvm-ffi) resolve automatically, no source build:LGTM — wheel installs with the declared dependencies (
apache-tvm-ffi>=0.1.12) and imports at the expected version. (It is a pre-release, so a barepip install apache-tvmstill resolves the latest stable; testers opt into the RC by pinning==0.25.0rc1or using--pre.)guan404ming commentedon Jun 19, 2026
+1
spectrometerHBH commentedon Jun 19, 2026
+1
MasterJH5574 commentedon Jun 19, 2026
Thank everyone for voting! The result is posted in #19844.