* mlxrunner: spell out symbols, numbers and links for Phonon
* docs: describe speech text normalization
* mlxrunner: fix Phonon misreadings inherited from xn-ptts
* mlxrunner: fix remaining Phonon misreadings
* mlxrunner: fold Phonon letters from the vocab, read #, _ and lists
* mlxrunner: add xn-ptts license notice for Phonon
* mlxrunner: move the xn-ptts license notice into normalize.go
* mlxrunner: fix remaining Phonon readings and port elongations
* docs: speech reads times and numeric dates
* mlxrunner: fix Phonon readings found in a listening pass
* docs: speech reads times and dates as written
Replace the prerelease checkpoint path with Gradium's GA format, including default-voice import and speech conditioning. Set the 0.40.9 minimum, update the speech docs, and test import, inference setup, and rejection of the old checkpoint.
* mlxrunner: add Phonon text-to-speech support
Add Phonon text-to-speech through the existing MLX runner, with an
OpenAI-compatible speech endpoint and CLI playback.
Include model loading, text preprocessing, streaming audio, and
regression tests.
* docs: add speech models
* fix min version
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Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
ShowResponse's renderer and parser fields existed but the server never
set them; they now carry the effective values (renderer resolves the
gemma4 legacy alias by model size). A new template_source names what
actually renders chat prompts: the configured renderer/parser (leaving
any packaged template inert), a Go template layer, the GGUF's embedded
jinja, harmony, or none.
The CLI prints renderer/parser/template source rows only when set, so
ollama show output is unchanged for models without rendering config.
* docs: add model grouping to cloud usage
Document group_by=model in the cloud usage guide and OpenAPI schema.
Explain group selection and remainder, and show responses with multiple
models across time buckets.
* Update docs/api/cloud-usage.mdx
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
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Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
Forward GET /api/usage and GET /api/balance through the local server
using the signed-in account.
Add API documentation and tests for proxying, signing, and
disabled cloud access.
Implements the EmbeddingGemma2Model architecture on the MLX runner: 24-layer
bidirectional text encoder with PLE, shared gemma4 vision/audio towers,
mean-pool + L2 output. /api/embed accepts per-item media via input dicts.
* mlxrunner: restore System One scoring
Carry the MLX implementation and its tests from the original System One
commit. The API/compiler and llama-server implementation already exist on
the release branch, so retain those versions. Adapt the optional model test
to the renamed decision package and its explicit rendering/context setup.
(cherry picked from commit 26e546ddb3)
* Enable MLX System One and add regression coverage
* mlxrunner: add Laya support for System One
Import Laya checkpoints and implement bidirectional decision scoring.
* mlxrunner: release cached buffers after System One scoring
* decision: match Tev1 and Nimble publisher prompt formats
Select Tev1 prompts using renderer metadata and fix JSON formatting, with regression coverage for GGUF and MLX.
* mlx: support Clef and Clef Flash decision models
Add model import, quantization safeguards, and text/image scoring with the Clef joint decision head.
* support vision capabilities for decision models
* Make Clef scoring cancellable between prefill chunks
Preserve joint-head inputs and test cancellation, cleanup, and recovery.
* mlx: separate decision preparation and readout from forward
Let serial and batched scoring share model-owned preparation and readout
without duplicating architecture-specific logic in the runner.
* mlx: add Strands Decider support
* implement caching
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Co-authored-by: ParthSareen <parth.sareen@ollama.com>
Add CAPABILITY declarations to Modelfiles and an additive capabilities
field to create requests. Preserve declarations across GGUF and safetensors
creation, inheritance, and Modelfile export.
Require decision capability before scheduling System One requests instead
of matching Qwen architecture/renderer metadata. Retain main's GGUF-only
scoring restriction until the separate MLX runtime work lands.
Extracted from the capability foundation in 36d46a0c3 on system_one_mlx;
MLX scoring and manifest-list changes are intentionally separate.
Add manifest-list storage so runner-specific manifests can coexist under one tag while preserving existing v1 tags as best-effort downgrade anchors. Show/list/copy/remove/pull/push now understand runner and digest selection and transfer referenced child manifests and layers.
Add lazy local compatibility migration for legacy Ollama GGUFs into llama.cpp-compatible children, covering the patched model families and preserving parser/renderer, templates, projectors, media metadata, split GGUFs, and MTP/draft tensors where applicable.
Extend create/import/conversion paths for the same compatibility rules, harden manifest-list combine validation, and add focused manifest, migration, transfer, and integration coverage for first-load conversion plus chat/tools/vision/audio/embedding behavior.
Switch from rejecting API requests to logging a warning. Model creation still rejects the deprecated param.
Follow up from #18448 to remove the hard API failure.
* create: add server-side MLX imports and drop GGUF conversion
Support safetensors imports through the MLX create pipeline both locally and on the server, including remote upload/staging, draft layer handling, cancellation propagation, transfer limits, and shared manifest/blob writing.
Limit GGUF create to wrapping existing GGUF inputs into Ollama manifests. Remove the in-tree safetensors-to-GGUF converter, server quantization path, and converter-only dependencies so GGUF conversion and quantization stay in llama.cpp tooling.
Keep the MLX path focused on supported safetensors model creation with validation before MLX work, and expose that flow without the --experimental CLI gate.
* address comments
* add client side gguf create fast path
* address comments
* rebase adjustments
anra8571
Daniel HiltgenandGitHub
Jeffrey MorganandGitHub
Jonathan Berg
Anna RahnandGitHub
Anna Rahn
Anna Rahn
Parth SareenandGitHub
Patrick DevineandGitHub
Eva HandGitHub