June 2026 monthly summary: In tenstorrent/tt-xla, fixed a critical JAX TT PJRT optimization_level pass-through bug, implemented fallback to a correct protobuf field, and added tests to verify propagation. Result: correct optimization behavior, improved reliability of PJRT integration and downstream model compilation for users relying on PJRT-enabled backends.

May 2026 monthly work summary focusing on TT-MLIR Gather Operation Enhancements with negative index handling and broader 32-bit index dtype acceptance. Implemented a fill-based semantics for negative indices to align with jax.lax.gather(mode='fill'), updated the verifier to accept any 32-bit integer index dtype, introduced a Gather Op WorkaroundPattern, and expanded tests to cover si32 and negative-index scenarios. This work improves interoperability, robustness, and flexibility of tensor gathering across backends.

April 2026: Delivered two major features in tenstorrent/tt-mlir, focusing on expanding tensor operation flexibility and safe type reinterpretation. Implemented StableHLO scatter flexibility and introduced bitcast_convert, with accompanying tests and robust validation. No major bug fixes reported for this repository this month. The work strengthens MLIR-based model compilation pipelines by enabling more flexible indexing, safer data reinterpretation, and stronger test coverage, improving reliability and downstream performance.

In March 2026, the tt-forge-models work focused on expanding model loading and testing coverage for bounty models. The team delivered new model loaders for LLama3.1-8b, Falcon3-7b, Mixtral-8x7b, Mistral-small, and Gemma3-27b, integrated into the existing testing framework to support automated nightly and weekly test runs. The work, anchored by commit 843095e6394cefc795fe12b2420835321b8d70aa, maps each model to loader functions and links to upstream PRs for traceability. Some models are expected to fail due to hardware limitations, but the test harness now surfaces these signals clearly early in CI. No critical bug fixes were closed this month; instead, the focus was on risk-managed feature delivery and improved validation coverage, which enhances confidence for model deployment and cross-repo collaboration with tt-xla.