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description: The fortnightly newsletter for the Turing.jl probabilistic programming language
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categories:
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- Newsletter
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author:
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- name: The TuringLang team
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url: /team/
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date: 2025-11-07
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---
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**Faster model evaluation**
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[This PR](https://github.com/TuringLang/DynamicPPL.jl/pull/1132) makes Turing faster by about 2-10x depending on the size of the model.
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(Not kidding, see the PR for examples!)
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Smaller models benefit the most, larger models less so because for those a larger proportion of your time is spent just calculating `logpdf`.
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The main impact is probably in inference.
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The PR contains an example where NUTS sampling on eight-schools is cut from ~ 8 seconds to ~ 1.5 seconds.
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The general strategy should lead to speedups for other operations as well such as `returned` and `predict`, although those will be less marked as reading from / constructing a chain will be the main bottlenecks.
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It's not released yet, but should hopefully be in the near future!
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**Mooncake @ 1.12**
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Just a note to say that there is now a newly released version of Mooncake that works on 1.12, and Turing should be perfectly compatible with it!
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