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Changes in 2.6.4

## PyTorch Lightning

Removed - Removed support for Neptune logger ([#21572](https://github.com/Lightning-AI/pytorch-lightning/pull/21572)). >*Note*: We usually don't remove features in a patch release, however in this case it's an exception since even without removing it the integration would be broken due to [Neptune being acquired and sunsetting public service](https://openai.com/index/openai-to-acquire-neptune/?utm_source=neptune-website-redirect)
Changed - Raised minimum `LitLogger` version to `2026-03-17` ([#21591](https://github.com/Lightning-AI/pytorch-lightning/pull/21591))
Fixed - Fixed `val_check_interval` raising `ValueError` when `limit_val_batches=0` and interval exceeds training batches ([#21560](https://github.com/Lightning-AI/pytorch-lightning/pull/21560)) - Fixed FSDP mixed precision (`bf16-mixed`, `16-mixed`) initializing model parameters in half precision instead of fp32 ([#21586](https://github.com/Lightning-AI/pytorch-lightning/pull/21586)) - Fixed `device_mesh` type hint in `FSDPStrategy` to accept a 2-element tuple via the CLI ([#21581](https://github.com/Lightning-AI/pytorch-lightning/pull/21581)) - Fixed `RichModelSummary` model size display formatting ([#21467](https://github.com/Lightning-AI/pytorch-lightning/pull/21467)) - Fixed floating-point precision in `SimpleProfiler` duration aggregation by using `math.fsum` ([#21525](https://github.com/Lightning-AI/pytorch-lightning/pull/21525))

## Lightning Fabric

Fixed - Fixed FSDP mixed precision (`bf16-mixed`, `16-mixed`) initializing model parameters in half precision instead of fp32 ([#21586](https://github.com/Lightning-AI/pytorch-lightning/pull/21586)) - Fixed `device_mesh` type hint in `FSDPStrategy` to accept a 2-element tuple via the CLI ([#21581](https://github.com/Lightning-AI/pytorch-lightning/pull/21581))


Full commit list: 2.6.1 -> 2.6.4

# Contributors New Contributors

We thank all folks who submitted issues, features, fixes and doc changes. It's the only way we can collectively make Lightning :zap: better for everyone, nice job!

In particular, we would like to thank the authors and co-authors of the pull-requests above:

@AsherJingkongChen, @Borda, @bhimrazy, @deependujha, @justusschock, @littlebullGit, @ManasVardhan, @taha-yassine

Source: README.md, updated 2026-05-20