# Accelerate v1.11.0 — v1.11.0: TE MXFP8, FP16/BF16 with MPS, Python 3.10 - Product: Accelerate (https://whatsnew.fyi/product/accelerate) - Vendor: Hugging Face - Date: 2025-10-20 - Version: v1.11.0 - Original notes: https://github.com/huggingface/accelerate/releases/tag/v1.11.0 - Permalink: https://whatsnew.fyi/product/accelerate/releases/v1.11.0 What's New is an index, not a publisher: every entry below links to the vendor's own release notes, which are the authoritative source. Entries are labelled where they are hand-curated sample data, pre-releases, or drawn from a secondary source such as a developer blog. Reuse: the summaries, labels and curation here are © What's New. Quote freely with attribution and a link back; wholesale republication of the corpus is not permitted — terms: https://whatsnew.fyi/terms. The vendors' own release notes remain their publishers'. --- - **added** — Support for MXFP8 in TransformerEngine integration with use_mxfp8_block_scaling option in fp8_config - **added** — BF16 and FP16 mixed precision support for MPS devices on Mac - **added** — Support for ignored_params in FSDPv2 - **added** — Support for no_sync() gradient synchronization control in FSDPv2 - **added** — Allow mixed precision policy as dtype string from accelerate CLI flag or fsdp_config - **added** — Add to_json method for nd-parallelism - **changed** — Make torch_native_parallelism examples device agnostic - **changed** — Update nd-parallel examples and cleanup - **changed** — Refactor Accelerator.autocast() to use with statement instead of __enter__() and __exit__() methods - **changed** — Drop support for Python 3.9 and bump minimum version to Python 3.10 - **fixed** — CPU RAM efficient loading for nd or HSDP parallelisms - **fixed** — XPU INT64 all_gather issue - **fixed** — Specify device_ids in torch.distributed.barrier for PartialState - **fixed** — Specify device for process_tensor in example usage - **fixed** — Reduce complexity of get_balanced_memory by adding a set - **fixed** — Skip CUDA cache flush when origin device is cpu and offloaded to meta - **fixed** — Convert LayerNorm without bias to FP8 - **fixed** — FSDP2 test case failure on XPU - **fixed** — SWANLAB_MODE and swanlab tracking - **removed** — Remove deprecated FindTiedParametersResult ##### TE MXFP8 support We've added support for MXFP8 in our TransformerEngine integration. To use that, you need to set `use_mxfp8_block_scaling` in `fp8_config`. See nvidia docs [here]. (https://docs.nvidia.com/deeplearning/transformer-engine/user-guide/examples/fp8_primer.html#MXFP8-and-block-scaling) * Add support for TE MXFP8 recipe in accelerate by @pstjohn in https://github.com/huggingface/accelerate/pull/3688 ##### FP16/BF16 Training for MPS devices BF16 and FP16 support for MPS devices is finally here. You can now pass `mixed_precision = "fp16" or "bf16"` when training on a mac (`fp16` requires torch 2.8 and `bf16` requires torch 2.6) * Add bf16/fp16 support for amp with mps device by @SunMarc in https://github.com/huggingface/accelerate/pull/3373 ##### FSDP updates The following PRs add respectively support to `ignored_params` and `no_sync()` for FSDPv2: * feat: add ignored_params support for fsdp2 by @kmehant in https://github.com/huggingface/accelerate/pull/3731 * fix: model.set_requires_gradient_sync(False) should be called to turn off gradient synchronization in FSDP2 by @EquationWalker in https://github.com/huggingface/accelerate/pull/3762 Mixed precision can now be passed as a dtype string from accelerate cli flag or `fsdp_config` in accelerate config file: * feat: allow mixed precision policy as dtype by @kmehant in https://github.com/huggingface/accelerate/pull/3751 ##### Nd-parallel updates Some minor updates concerning nd-parallelism. * Context Parallelism docs typos fixed by @sergiopaniego in https://github.com/huggingface/accelerate/pull/3761 * Feat: add to_json by @S1ro1 in https://github.com/huggingface/accelerate/pull/3743 * make torch_native_parallelism examples device agnostic by @yao-matrix in https://github.com/huggingface/accelerate/pull/3759 * [ND Parallel] Update examples, cleanup by @S1ro1 in https://github.com/huggingface/accelerate/pull/3737 ##### Bump to Python 3.10 We've dropped support for python 3.9 as it reached EOL in October. * Bump to python3.10 + update linter by @SunMarc in https://github.com/huggingface/accelerate/pull/3809 ###### Lots of minor fixes: * fix: CPU RAM efficient loading for nd or HSDP parallelisms by @kmehant in https://github.com/huggingface/accelerate/pull/3740 * xpu INT64 all_gather issue fixed in 2.9 by @yao-matrix in https://github.com/huggingface/accelerate/pull/3756 * Specify device_ids in torch.distributed.barrier for PartialState by @qgallouedec in https://github.com/huggingface/accelerate/pull/3744 * fix: specify device for process_tensor in example usage by @qgallouedec in https://github.com/huggingface/accelerate/pull/3755 * Lower complexity of get_balanced_memory by adding a set by @SamuelBarryCS in https://github.com/huggingface/accelerate/pull/3776 * Fix (skip) cuda cache flush when origin device is `cpu` and offloaded to `meta` by @Qubitium in https://github.com/huggingface/accelerate/pull/3796 * Fix convert LayerNorm without bias to fp8 by @mjun0812 in https://github.com/huggingface/accelerate/pull/3725 * Add optional typing by @cyyever in https://github.com/huggingface/accelerate/pull/3769 * refactor: Use `with` in Accelerator.autocast()instead of ` __enter__()` and` __exit__()` for more elegant style. by @EquationWalker in https://github.com/huggingface/accelerate/pull/3767 * switch XPU ccl backend to torch-builtin xccl in test_zero3_integration by @yao-matrix in https://github.com/huggingface/accelerate/pull/3773 * fix FSDP2 test case failure on XPU by @yao-matrix in https://github.com/huggingface/accelerate/pull/3771 * Fix tests by @SunMarc in https://github.com/huggingface/accelerate/pull/3722 * Protect import for device_mesh by @SunMarc in https://github.com/huggingface/accelerate/pull/3742 * Fix `SWANLAB_MODE` by @SunMarc in https://github.com/huggingface/accelerate/pull/3808 * Fix tracking swanlab by @SunMarc in https://github.com/huggingface/accelerate/pull/3810 * refacto _[Truncated at 4000 characters — full notes: https://github.com/huggingface/accelerate/releases/tag/v1.11.0]_