Runtimes & apps Published:
Ollama 0.40.9 adds local text-to-speech on Apple Silicon, d3 decision models, and Flint on Linux and Windows
What happened
Ollama v0.40.9, released on October 22, can generate speech with the Phonon model on Apple Silicon: `ollama run` reads text or a chat model's reply aloud as the audio is generated, and apps can stream audio from the OpenAI-compatible `/v1/audio/speech` endpoint. The default Phonon model uses Gradium's 31M-parameter English checkpoint, takes up to 4,096 characters per request and returns 24 kHz mono WAV or PCM. The release also adds d3, vLLM Semantic Router's Apache 2.0 decision models in 2B, 4B, 9B and 27B sizes, which classify, answer yes or no, or score options with probabilities from text, structured state or a still image. Recursive's Flint coding model, macOS-only in 0.40.8, now also runs on Linux and Windows.
Why it matters locally: Voice output and yes-or-no routing decisions used to mean calling a cloud API; now both run on the same local server you already use for chat.
Three ways to read it
For the market
Speech through an OpenAI-compatible endpoint means apps written for cloud text-to-speech could point at a Mac on the desk instead, which likely widens Ollama's role from a chat runner to a general local AI server. Small decision models like d3 also suggest a trend toward routing each request to the cheapest model that can handle it.
In plain words
Ollama, a free app for running AI on your own computer, can now read answers out loud on Apple Silicon Macs, without sending your text anywhere. It also gets a new family of small models that answer simple questions like "is this a billing complaint?" with a yes, a no or a score.
For practitioners
Phonon's default checkpoint is English only and accepts `wav` or `pcm` at 24 kHz; other formats, speeds or `instructions` return a 400 error, so check your client before swapping it in for a cloud voice. Ollama suggests 8, 16, 32 and 64 GB of system memory for the d3 2B, 4B, 9B and 27B packages, which run with a 4,096-token context, so test them on your own labelled examples before putting one in front of a larger model as a router.
Sprout's insight
Sprout compares this with other brands and with where real applications are heading. Free for members.
Sign in free to read it →Subscribe to Sprout's weekly
One email a week: the top stories and a taste of Sprout’s insights. Unsubscribe any time.
Source
Read the official source: Ollama v0.40.9 release notes (GitHub) ↗Summaries are written by OnPrem World from the official source. We link to the original and never republish it.
On this site
More news
- Recursive releases Flint, an Apache 2.0 coding model with 40B parameters and about 2.5B active, already in Ollama for Mac
- AMD and Intel agree on oneDNN as PyTorch's shared x86 CPU acceleration library
- vLLM v0.32 brings 4-bit KV cache to more GPUs and stops allowing every CORS origin by default
- DeepSeek-V4.1-Flash-1017: a same-size update with better agent scores and shorter answers
- Open WebUI 0.12.3 adds end-to-end encrypted chats and one search box for the whole workspace