Data and AI releases

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Ray-2.60.0

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Ray 2.60.0 released shuffle v2 as default for joins and aggregations, updated Parquet task sizing from row-group metadata, added rolling update surge controls in Ray Serve, and patched security vulnerabilities.

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Also shipped Nov 4, 2026Anyscale in November 2026 →

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Ray-2.59.1

Ray 2.59.1 released security fixes updating bundled certifi, pip, and virtualenv dependencies following the eMudhra intermediate CA compromise, along with updating aiohttp to 3.14.4.

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Ray-2.58.1

Fixes Ray Data - Fix out-of-scope block callbacks being registered on blocks passed through from input to output (\#66369, cherry-pick \#66404). Fixes spurious callback errors on passthrough datasets. Images - google-cloud-cli is now installed in the base-extra images (\#65757, pick \#66611). Contributors Thanks to everyone who contributed to this release!

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Ray-2.57.1

Fixes Ray Data - Fix out-of-scope block callbacks being registered on blocks passed through from input to output (\#66369, cherry-pick \#66403). Fixes spurious callback errors on passthrough datasets. Images - google-cloud-cli is now installed in the base-extra images (\#65757, pick \#66610). Contributors Thanks to everyone who contributed to this release!

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Ray-2.59.0

Highlights > * Ray Data LLM & Ray Serve LLM are GA/Stable: the LLM APIs graduate to general availability this release (\#65194), alongside an upgrade to vLLM 0.27.0 (\#65351).

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Ray-2.58.0

Highlights Ray Serve LLM: In this release we've completed KV cache and token aware request routing, which was previewed in 2.57. Tokenization now happens in-process on the LLMRouter ingress replica, the routing decision is made there, tokens are transmitted out-of-band so the engine does not re-tokenize, KV lifecycle events are broadcast to every ingress...

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Ray-2.57.0

Highlights Ray Data: In this Ray release, we've enabled DataSourceV2 by default ( #64821 ), so read_parquet and friends use the new scan/listing infrastructure with row-group-aware chunking and predicate splitting. Hash Shuffle V2 eliminates the aggregator actor pool.

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Ray-2.56.1

Highlights Ray Data : We added fixes for several to_pandas regressions introduced in 2.56: an opt-out flag ( RAY_DATA_ENABLE_ARROW_BACKED_PANDAS_CONVERSION ) for Arrow-backed conversion, an int64/ double[pyarrow] overflow crash on concatenation, and a TensorDtype.__from_arrow__ crash on empty tensor columns ( #64793 , #64794 ).

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Ray-2.56.0

Highlights Ray Data Stability: In this Ray release, we've added a variety of stability improvements, including running multiple datasets in a cluster, adding automatic batch size selection to CPU-based map-batches, and default logical memory configuration to prevent OOMs.

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