Version 1.0.0

Author: ausimian

CHANGELOG.md

@@ -7,6 +7,37 @@ and this project adheres to [Semantic Versioning](https://semver.org/).
 
 <!-- %% CHANGELOG_ENTRIES %% -->
 
+## 1.0.0 - 2026-07-08
+
+First stable release. Emily runs `Nx` computations on Apple Silicon
+through MLX — set it as the default Nx backend and Bumblebee models run
+on the Metal GPU with no further integration. With 1.0 the public API is
+stable and follows semantic versioning from here; there are no breaking
+changes from 0.7.x, so existing code keeps working. The headline this
+cycle is quantized inference — 4-bit layers now stream through the fused
+`mx::quantized_matmul` kernel, making native quantized generation ~13×
+faster end-to-end and, for the first time, faster than dense (details
+below).
+
+### Changed
+
+- The precompiled NIF now declares an explicit minimum macOS per variant —
+  macOS 14 for the AOT build, macOS 26.2 for the JIT build — instead of
+  inheriting whatever macOS the release runner happened to be on. Published
+  artifacts now have a deterministic macOS compatibility floor, and CI
+  asserts it on every build.
+- Updated the pinned MLX to 0.32.0. This is a maintenance bump that also
+  picks up faster small-batch quantized matvec (`qmv_wide`) — accelerating
+  the fused quantized path — and broader fused SDPA coverage (asymmetric
+  Q/V head dims), both transparently. No API changes.
+- Quantized dense layers now use the fused `mx::quantized_matmul` kernel
+  instead of dequantizing the full weight to bf16 and running a dense
+  matmul. The packed low-bit weights are streamed directly, so a decode
+  step no longer re-dequantizes the entire model on every token. On a
+  4-bit Qwen3-0.6B this makes native quantized generation roughly 13×
+  faster end-to-end — and quantized inference is now *faster* than dense,
+  as it should be, rather than slower.
+
 ## 0.7.2 - 2026-06-13
 
 ### Fixed

RELEASE.md

@@ -1,28 +0,0 @@
-First stable release. Emily runs `Nx` computations on Apple Silicon
-through MLX — set it as the default Nx backend and Bumblebee models run
-on the Metal GPU with no further integration. With 1.0 the public API is
-stable and follows semantic versioning from here; there are no breaking
-changes from 0.7.x, so existing code keeps working. The headline this
-cycle is quantized inference — 4-bit layers now stream through the fused
-`mx::quantized_matmul` kernel, making native quantized generation ~13×
-faster end-to-end and, for the first time, faster than dense (details
-below).
-
-### Changed
-
-- The precompiled NIF now declares an explicit minimum macOS per variant —
-  macOS 14 for the AOT build, macOS 26.2 for the JIT build — instead of
-  inheriting whatever macOS the release runner happened to be on. Published
-  artifacts now have a deterministic macOS compatibility floor, and CI
-  asserts it on every build.
-- Updated the pinned MLX to 0.32.0. This is a maintenance bump that also
-  picks up faster small-batch quantized matvec (`qmv_wide`) — accelerating
-  the fused quantized path — and broader fused SDPA coverage (asymmetric
-  Q/V head dims), both transparently. No API changes.
-- Quantized dense layers now use the fused `mx::quantized_matmul` kernel
-  instead of dequantizing the full weight to bf16 and running a dense
-  matmul. The packed low-bit weights are streamed directly, so a decode
-  step no longer re-dequantizes the entire model on every token. On a
-  4-bit Qwen3-0.6B this makes native quantized generation roughly 13×
-  faster end-to-end — and quantized inference is now *faster* than dense,
-  as it should be, rather than slower.

mix.exs

@@ -2,7 +2,7 @@ defmodule Emily.MixProject do
   use Mix.Project
 
   @app :emily
-  @version "0.7.2"
+  @version "1.0.0"
   @source_url "https://github.com/ausimian/emily"
 
   # MLX pin. Drives the git tag the `:mlx_src` dep is cloned at (see