When a browser is available open it to the connect URL automatically when running the `ollama signin` command. Browser is not opened in any other unauthorized scenario.
When launching OpenClaw without prior onboarding, run the onboarding
wizard instead of going straight to gateway. This ensures proper
gateway configuration (mode, token, etc.) before first use.
- Add onboarded() to check for wizard.lastRunAt marker in config
- Run onboard with --auth-choice skip --gateway-token ollama for fresh installs
- Existing installs (onboarding completed) run gateway directly
- Fix panic in ollama show for image gen models (safe type assertion)
- Add vision capability for Flux2KleinPipeline models at create time
- Flatten transparent PNG images onto white background for better results
Move the unload check (empty prompt + KeepAlive=0) before the image
generation model dispatch in GenerateHandler. This prevents models like
flux from being loaded into memory just to be immediately unloaded when
running `ollama rm`.
Also fix a bug in DeleteHandler where `args[0]` was used instead of
`arg` in the delete loop, causing only the first model to be unloaded
when deleting multiple models.
* x: make `ollama create --experimental` import from safetensors
This change allows pulling in safetensors models into the new experimental model format, and also
fixes the `ollama show` command to be able to correctly display the model information.
* gofumpt the linter
* gofumpt the linter again
* validate the model name
TeaCache:
- Timestep embedding similarity caching for diffusion models
- Polynomial rescaling with configurable thresholds
- Reduces transformer forward passes by ~30-50%
FP8 quantization:
- Support for FP8 quantized models (8-bit weights with scales)
- QuantizedMatmul on Metal, Dequantize on CUDA
- Client-side quantization via ollama create --quantize fp8
Other bug fixes:
- Fix `/api/show` API for image generation models
- Server properly returns model info (architecture, parameters, quantization)
- Memory allocation optimizations
- CLI improvements for image generation
* cmd/bench: support writing benchmark output to file
This changes Ollama to allow the bench command to write benchmark
results to a user-specified output file instead of stdout when the
--output flag is provided.
---------
Co-authored-by: Patrick Devine <patrick@infrahq.com>
This change:
* fixes rope scaling in the mistral converter
* updates ministral to include llama4 scaling
* includes a new ministral parser for parsing reasoning and tool calling
---------
Co-authored-by: jmorganca <jmorganca@gmail.com>
This change adds a basic benchmarking test framework for Ollama which can
be used to determine the prefill, eval, load duration, and total duration
for running a given model or models.
Co-authored-by: A-Akhil <akhilrahul70@gmail.com>
This PR introduces a new ollama embed command that allows users to generate embeddings directly from the command line.
Added ollama embed MODEL [TEXT...] command for generating text embeddings
Supports both direct text arguments and stdin piping for scripted workflows
Outputs embeddings as JSON arrays (one per line)
this change fixes two bugs with `ollama rm`:
1. before a model is removed, it will first be stopped. this only
happens for the first argument and skipped for all other models
2. models are unloaded indiscriminately. this errors for cloud models
and should be omitted
There are two bugs when using `/load <model>` for a model that doesn't exist, namely:
1. it will not restore the current model settings if the current model is a thinking model; and
2. it will crash is the current model is a non-thinking model
This bug fix saves the current runOptions and then restores them if the model load
doesn't happen. It also fixes the crash happening for non-thinking models.
* auth: fix problems with the ollama keypairs
This change adds several fixes including:
- reading in the pubkey files correctly
- fixing the push unit test to create a keypair file in a temp directory
- not return 500 errors for normal status error
* bf16
* tests
* gpt-oss
* enable gptoss for engine
* rough estimate
* convert to mxfp4
* handle safetensors U8
* clamp glu/linear
* update tokenizer
* MXFP4 support
This implements the Open Compute Microscaling (MX) FP4 format
as a tensor type with backend implementations focusing
on mulmat and mulmatid on CPU, CUDA, and Metal.
* Unit tests for MXFP4 support
This exercises various operations and shapes on both CPU and GPU (if detected
on the system)
* cuda graph
* unit test adjustments
* cuda: optimize memory access
Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4
* mac: fix crash on old macos versions
cblas_sgemm is only supported on v13.3 and up, however bf16 is
only supported on v14+ so we were falling back to ggml-blas and
crashing on bf16 tensors. Checking for the function being null
seems to be the simplest way to condittionally avoid registering the
backend.
* server: Minimum context length for gptoss
This model requires a minimum context length of 8192 to function
effectively. Users can set higher values through all normal mechanisms
but lower values will be silently reset.
* ggml: Multiply by numParallel for gptoss sliding window
When computing the graph size estimate, the context size is already
multiplied by numParallel so estimates reflect that. However, since
sliding window models use a smaller, fixed context size, they need
to manually take numParallel into account.
* gpt-oss integration
includes harmony parser and thinking levels, etc.
* fix sync
* fix tests
* fix lint
---------
Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
Co-authored-by: Jesse Gross <jesse@ollama.com>
Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
