Who contributed to Google on July 16, 2026?

8 developers shipped this update, including copybara-service, mattjj, release-please[bot], release-please, Annie Luc, Heba Alazzeh, parthea, and noahdietz.

What were the notable Google updates?

Add end-to-end support for FP6 formats (float6_e2m3fn and float6_e3m2fn) across CPU and GPU, [Mosaic:GPU] Use XLA runtime API to run multi-device barrier kernel, and [pallas] VJP rule for the einshape primitive.

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The Wire · Showcase

JAX ADDS FP6 SUPPORT END-TO-END, PYTHON-GENAI SHIPS AGENT CONFIG

By RepoJournal · Filed 06:59 UTC on July 16, 2026 · About Google

8 people shipped this

copybara-service @copybara-service 3 cited

parthea @parthea 2 cited

release-please[bot] @release-please[bot] 1 cited

Heba Alazzeh @hebaalazzeh 1 cited

noahdietz @noahdietz 1 cited

mattjj @mattjj

release-please @release-please

Annie Luc @Annhiluc

JAX landed full float6 format support across CPU and GPU backends, while the AI SDK gains AntigravityAgentConfig and a trigger resource in v2.12.0.

In brief

JAX adds end-to-end FP6 support (float6_e2m3fn and float6_e3m2fn) across CPU and GPU. compression and speed without the usual accuracy trade-off headaches. worth a look if you're model-serving at scale.
JAX Mosaic:GPU now uses XLA runtime API for multi-device barrier kernels. stops the sync thrashing between GPUs on distributed runs.
Pallas VJP rule for einshape lands in JAX. means backward passes through shape-preserving ops stop being a pain to hand-code.
python-genai hits v2.12.0. agent config support is in. building multi-step reasoning flows just got less boilerplate-heavy.

The JAX team shipped comprehensive FP6 support [1] spanning IFRT dtype definitions, PJRT C API bindings bumped to API version 114, and Python-level exposure of both float6_e2m3fn and float6_e3m2fn formats. This lands infrastructure for the memory-efficient training and inference everyone's been waiting for. On the experimental side, Mosaic GPU got multi-device barrier kernel support via XLA runtime APIs [2], and Pallas now has VJP rules for einshape [3], unblocking more gradient compute patterns. Google-cloud-python initiated PEP 0810 lazy imports for gapic v1 [5], deferring grpcio and other heavy C-extensions to reduce init latency and peak memory. The python-genai SDK bumped to v2.12.0 [4] with AntigravityAgentConfig additions and a new Triggers resource, while google-cloud-pubsub, google-cloud-spanner, and google-cloud-bigtable all regenerated against updated googleapis definitions [6] [7] [8].

Action items

→ Upgrade python-genai to v2.12.0 if you're using triggers or agent configs googleapis/python-genai [plan]
→ Start testing FP6 formats in JAX for memory-critical workloads google/jax [monitor]
→ Review lazy import changes in google-api-core and profile your startup time googleapis/google-cloud-python [plan]

References

[1] Add end-to-end support for FP6 formats (float6_e2m3fn and float6_e3m2fn) across CPU and GPU. ↗ google/jax
[2] [Mosaic:GPU] Use XLA runtime API to run multi-device barrier kernel ↗ google/jax
[3] [pallas] VJP rule for the einshape primitive ↗ google/jax
[4] v2.12.0 ↗ googleapis/python-genai
[5] feat: lazy imports gapic v1 (#17673) googleapis/google-cloud-python
[6] chore: regenerate google-cloud-pubsub and google-cloud-spanner ↗ googleapis/google-cloud-python
[7] chore: regenerate google-cloud-bigtable ↗ googleapis/google-cloud-python
[8] feat: update googleapis and regenerate ↗ googleapis/google-cloud-python

Quick answers

What shipped in Google on July 16, 2026?: JAX landed full float6 format support across CPU and GPU backends, while the AI SDK gains AntigravityAgentConfig and a trigger resource in v2.12.0. In total, 45 commits, 42 pull requests, and 1 releases landed.
Who contributed to Google on July 16, 2026?: 8 developers shipped this update, including copybara-service, mattjj, release-please[bot], release-please, Annie Luc, Heba Alazzeh, parthea, and noahdietz.
What were the notable Google updates?: Add end-to-end support for FP6 formats (float6_e2m3fn and float6_e3m2fn) across CPU and GPU, [Mosaic:GPU] Use XLA runtime API to run multi-device barrier kernel, and [pallas] VJP rule for the einshape primitive.

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