7. Key Quality Metrics#

Performance-related metrics must remain key acceptance criteria throughout Stages 3-6. Stage 3 focuses on operator performance, and Stage 4 focuses on inference accuracy and end-to-end performance.

Stage

Acceptance criteria

Pass standard

Required hardware

Stage 0

MOU signing

Effective after both parties sign or seal

N/A

Stage 1

Environment readiness

Chip is recognized by the OS and PyTorch can recognize the backend

1 development board

Stage 2

Triton kernel compilation pass rate

>=95%, CI machine availability >=99%

1 CI machine

Stage 3

FlagGems operator test pass rate

>=80%, core operators 100%

2 CI machines and 1 debug machine

Stage 4

Model accuracy deviation

<2% relative to the NVIDIA baseline

2 CI machines and 1 debug machine

Stage 5

CTS core tests passed

100% passed or waiver approved

2 CI machines and 2 SVT machines

Stage 6

Number of models released through FlagRelease

>=10 models

1 dedicated FR machine