# Meilisearch v1.12.0 — Release & Upgrade Intelligence
- **Product:** Meilisearch (https://meilisearch.com)
- **Version:** v1.12.0
- **Released:** Dec 23, 2024
- **Impact Score:** 7/10
- **Breaking Changes:** Source flagged
- **Canonical Analysis:** https://changelogs.us/meilisearch/updates/v1.12.0/

## Executive Summary (TL;DR)
Meilisearch v1.12.0. Source highlight: Meilisearch v1.12 introduces significant indexing speed improvements, almost halving the time required to index large datasets. This release also introduces new settings to customize and potentially further increase indexing speed.

## Breaking Changes & Deprecations
- ⚠️ Breaking `vectorStore` change: field distribution no longer contains `_vectors`. Its value used to be incorrect, and there is no current use case for the fixed, most likely empty, value. Done as part of #4900

## New Features
- Add image source label to Dockerfile by @wuast94 in #4990

## Improvements
- Performance is maintained or better on smaller machines
- On bigger machines with multiple cores and good IO, Meilisearch v1.12 is much faster than Meilisearch v1.11
- More than twice as fast for raw document insertion tasks.
- More than x4 as fast for incrementally updating documents in a large database.
- Embeddings generation was also improved up to x1.5 for some workloads.
- New query parameter for `GET` `/tasks`: `reverse`. If `reverse` is set to `true`, tasks will be returned in reversed order, from oldest to newest tasks. Done by @irevoire in #5048

## Bug Fixes
- ⚠️ Breaking `vectorStore` change: field distribution no longer contains `_vectors`. Its value used to be incorrect, and there is no current use case for the fixed, most likely empty, value. Done as part of #4900
- Return appropriate error when primary key is greater than 512 bytes, by @flevi29 in #4930
- Fix issue where numbers were segmented in different ways depending on tokenizer,
- Fix pagination when embedding fails
- Fix issue causing Meilisearch to ignore stop words in some cases by @ManyTheFish in #5062
- Fix phrase search with `attributesToSearchOn` in #5062