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Version: v0.22.x

Release notes

Version 0.22.9 (September 22nd, 2026)​

Fixes​

  • [Data Generation] Fixed Check Config and Start running with no model selected and then showing an unclear error. Both buttons are now disabled until a model is selected, and Reset Settings picks a model from the allowed list.

Security​

  • Updated Model Zoo's inference runtime (vLLM) to fix a vulnerability that let a crafted request use up GPU memory and crash the deployment.
  • Updated libraries across H2O Cascade's services to fix several vulnerabilities, including one that allowed TLS certificate spoofing.

Version 0.22.8 (September 18th, 2026)​

New Features​

  • [Platform] The Keycloak admin role name is now configurable (KEYCLOAK_ADMIN_ROLE, default llmstudio_admin), so you can use an existing role in your identity provider instead of creating a new one.

Fixes​

  • [Assistant] Fixed assistant attachments larger than 10 MB failing to upload, even though the UI allows up to 20 MB.
  • [Assistant] Fixed the assistant rejecting models whose names start with openai/ (for example, openai/gpt-oss-120b) when the endpoint lists them that way.
  • [Data Generation] Fixed data generation still offering models the configured endpoint doesn't serve after an administrator clicked Refresh Models, which caused those runs to fail with "Invalid model".
  • [Platform] Fixed System Status showing Object Storage as unhealthy on external S3 installs where the S3 role can only access H2O Cascade's own buckets.
  • [Platform] The About page and the assistant now use the H2O Cascade name.

Version 0.22.7 (September 14th, 2026)​

Fixes​

  • [Platform] Fixed a single failed request making the UI retry it endlessly and show the same error message over and over.
  • [Platform] Fixed experiment and data generation configurations failing to load with "Configuration file not found" on external AWS S3 storage once the stored download link expired.

Security​

  • Updated web UI dependencies to fix six security advisories.

Version 0.22.6 (September 11th, 2026)​

Fixes​

  • [Model Zoo] Fixed deployments failing to start on NVIDIA Hopper and Blackwell GPUs (for example, H100 and B200).
  • [Model Zoo] Fixed deployments failing with a permission error on OpenShift, which runs containers under a random user ID.
  • [Model Zoo] Fixed Model Zoo crashing at startup on FIPS-enabled hosts.
  • [Model Zoo] Fixed the Llama Guard model in Model Zoo returning an error on every request.
  • [Experiments] Fixed experiments staying "queued" forever when the training job failed, for example, when the training worker stopped unexpectedly or hit a time limit. They are now marked as failed, with the error in the logs.
  • [Datasets] Fixed adding a URL-based demo dataset hanging and then showing a generic error when the download host isn't reachable. It now fails quickly with a message that names the host.
  • [Data Generation] Fixed data generation jobs with an empty User Prompt Template reporting success while every row contained the same generic greeting. Start and Check Config are now disabled until a template is entered.

Security​

  • Updated the Transformers library to fix a path traversal vulnerability.
  • Updated the web UI framework (Next.js) to fix two security advisories.
  • Removed an unused copy of pip from the training and Model Zoo images. Security scanners were reporting setuptools vulnerabilities from it.

Version 0.22.5 (September 2nd, 2026)​

New Features​

  • [Experiments] Added an opt-in option to compute feature importance for TabH2O tabular predictions, shown as a ranked chart in the experiment's results.
  • [Model Zoo] Added a provisional /api/v1 endpoint namespace for agent-facing API clients, with an OpenAPI 3.1 spec and a capability manifest. It currently covers the existing Model Zoo endpoints.

Fixes​

  • [Platform] Fixed the assistant, data generation, and AutoML model dropdowns showing no available models when configured against an OpenAI-compatible gateway instead of OpenAI itself. Every enabled model is now offered to every feature, instead of only the overlap with each feature's built-in list.

Security​

  • Fixed a vulnerability in how the assistant's web-fetch tool parses robots.txt files, which could let a malicious site hang the request with a crafted file.

Version 0.22.4 (August 31st, 2026)​

New Features​

  • [Platform] Added support for the OpenAI gpt-5.6 model family, available in the assistant, data generation, and AutoML.
  • [Training] Image classification training now supports non-square (rectangular) image resolutions and an explicit resize mode (squash, pad, or crop), instead of always inheriting the backbone's default center-crop behavior.

Fixes​

  • [Assistant] Fixed document parsing (PDF, DOCX, PPTX, HTML) failing in airgapped environments by bundling the required OCR and layout model weights instead of downloading them on first use.

Security​

  • Updated Model Zoo's inference runtime (vLLM and PyTorch) to fix a memory-corruption vulnerability.

Version 0.22.3 (August 18th, 2026)​

Fixes​

  • [Training] Fixed training.image_resolution being ignored for timm-based vision backbones in image classification, so models now train at the resolution you configure instead of silently falling back to the backbone's default.
  • [Training] Fixed image classification and object detection models training with reduced numerical precision and skipping weight decay on normalization layers, both of which were quietly limiting final model accuracy.

Security​

  • Requests made with the internal service token but no identified user are now rejected instead of running with full administrator access.

Version 0.22.2 (August 14th, 2026)​

New Features​

  • [Platform] Dataset uploads to Azure Blob Storage now upload directly from the browser, matching the existing direct-upload behavior for S3-compatible storage.
  • [Platform] The task-acknowledgment option added in 0.22.1 (H2O_LLM_STUDIO_CELERY_TASK_ACKS_LATE) now also applies to the AutoML and data generation workers, in addition to the training worker.

Security​

  • Disabled tracing in the assistant's underlying agent framework, which by default sent prompts and responses to a third-party endpoint.

Version 0.22.1 (August 11th, 2026)​

New Features​

  • [Platform] Added an option to change when the training worker acknowledges queued jobs (H2O_LLM_STUDIO_CELERY_TASK_ACKS_LATE), so autoscalers can see training jobs that are still in progress.

Version 0.22.0 (August 7th, 2026) — H2O Cascade​

Rebrand​

H2O Enterprise LLM Studio is now H2O Cascade. The product has grown beyond fine-tuning LLMs to support additional modalities and use cases — including image classification and object detection — with more on the way. This rebrand reflects that broader scope; the platform itself, your existing projects, and your data are unaffected.

Documentation for previous H2O Enterprise LLM Studio releases remains available via the version switcher.

New Features​

  • [Platform] Added native Azure Blob Storage support as an object storage backend.
  • [Experiments] New experiments can now start directly from a previously trained experiment's weights (for example, continuing SFT training into RL) instead of a manual download and re-upload of the model.
  • [Training] RL experiments now report a validation score at step 0, in addition to during training.

Fixes​

  • [Assistant] Fixed the assistant failing when chatting against OpenAI-compatible endpoints, and improved the error shown when a response fails to stream.
  • [Training] Fixed a regression that slowed down object detection training.
  • [Training] Fixed RL experiments getting stuck showing "validating" through the first half of a run.
  • [Training] Fixed training runs being marked as failed — and their logs discarded — due to a transient error while monitoring worker processes.
  • [Experiments] Fixed the training-curve chart getting flattened by a single loss outlier spike.
  • [Experiments] Fixed the "System Prompt Column" selection on the new experiment page being dropped from the submitted experiment configuration.
  • [Data Generation] Fixed data generation jobs hanging in airgapped environments while trying to download tokenizer files.
  • [Model Zoo] Fixed deployments failing to wake up when GPU capacity was briefly unavailable; they now wait and retry instead.
  • [Platform] Fixed broken dataset uploads to external object stores caused by incorrect CSP and presigned URL settings.

Security​

  • Fixed an authorization gap that could allow deploying an experiment from a project the user does not have access to.

Version 0.21.2 (July 29th, 2026)​

New Features​

  • [AutoML] AutoML logs now show live experiment progress — status transitions, periodic runtime/ETA/loss updates, and a summary when each experiment finishes or fails.

Fixes​

  • [AutoML] Fixed AutoML showing reinforcement learning (RL) experiments as regular causal LM experiments, including an irrelevant output column option for them.
  • [AutoML] Fixed AutoML runs getting stuck showing "running" when a failure occurred partway through.
  • [AutoML] Fixed LLM-as-a-Judge being rejected as the optimization metric when starting AutoML through the assistant.
  • [AutoML] RL experiments in AutoML now always use LLM-as-a-Judge as the optimization metric, since no other metric applies. The metric selector is hidden for RL.
  • [Training] RL rollout prompts and completions are no longer written to training logs by default, preventing training data from leaking into logs.
  • [Model Zoo] Fixed an issue that prevented deployment of RL models.
  • [Datasets] Fixed CSV row counts being overstated for datasets containing multi-line fields.
  • [Datasets] Removed an unused output column from the RL demo dataset that incorrectly implied labels are required for RL training.
  • [Assistant] Fixed the assistant failing when using model names from a gateway's model catalog.

Version 0.21.1 (July 27th, 2026)​

New Features​

  • [Platform] Support for running against a customer-managed external Postgres database (for example, AWS Aurora), including optional IAM authentication.

Fixes​

  • [Platform] Improved performance of the experiments, deployments, and data generation list pages, which no longer load full task logs on every automatic refresh.
  • [Data Generation] Fixed an issue where data generation jobs could get stuck showing "running" instead of completing or failing.
  • [Training] Fixed a crash when training on datasets containing missing values.
  • [Experiments] Fixed a server error that broke the experiment page and blocked AutoML from starting the next experiment for experiments trained on JSON datasets.
  • [Platform] Fixed the settings page so a failed OpenAI models fetch no longer blocks the rest of the page from loading.

Version 0.21.0 (July 20th, 2026)​

New Features​

  • [Model Zoo] Model deployments now run through a shared, GPU-aware deployment manager instead of a dedicated worker per deployment, improving scalability and cost efficiency.

Version 0.20.2 (July 9th, 2026)​

New Features​

  • [Model Zoo] New batch inference API — submit batch jobs asynchronously, poll or cancel them, and stream progress or receive a webhook callback on completion. Batch jobs are priority-queued so they can't starve interactive traffic, with native batched support for vLLM, chat, NER, PII masking, the Danube3 classifier, and BART.
  • [Platform] Storage bucket names are now configurable via environment variables.

Fixes​

  • [UI] Fixed a dropdown selection issue affecting components using multi-select.
  • [Training] Fixed a training failure that occurred when input CSV files used CRLF line endings.
  • [Platform] Resolved a dependency conflict that could block installation.

Security​

  • Fixed server-side request forgery (SSRF) findings in frontend server actions and API routes.

Version 0.20.1 (July 2nd, 2026)​

New Features​

  • [Data Generation] You can now choose the output dataset's problem type when generating data.
  • [Platform] Further upgraded the core ML stack: PyTorch 2.11, vLLM 0.22.1, and CUDA 13 / cuDNN 9 base images. This raises the minimum required NVIDIA driver version.
  • [Model Zoo] Added per-model request queueing with backpressure, along with cache and queue status visibility via the health and status endpoints.

Fixes​

  • [Model Zoo] Fixed a crash during FLUX model inference caused by a dtype mismatch.

Version 0.20.0 (May 22nd, 2026)​

This release adds reinforcement learning training, a model cache for faster repeat inference, and upgrades the core ML stack.

New Features​

  • [Experiments] Training with reinforcement learning (RL) and LLM reward.
  • [Experiments] You can now select which columns to include or exclude for tabular problems, with automatic column suggestions.
  • [Platform] LRU model cache with a configurable VRAM budget, speeding up repeat inference.
  • [Platform] Core ML stack upgraded to Transformers v5, vLLM 0.19.1, and PyTorch 2.10, with a CUDA 12.8 toolchain across all services.
  • [Platform] Tabh2o moved to a dedicated on-prem HTTP service, improving air-gapped support.
  • [Platform] Improved Content Security Policy (CSP) headers.

Fixes​

  • [Datasets] Numerical columns are no longer misclassified as categorical during tabular data loading.
  • [Datasets] Fixed an issue that prevented new dataset uploads.
  • [Projects] Fixed an issue where renaming a project didn't work correctly.
  • [UI] Fixed a theme flicker and a hydration mismatch that could occur on page load.
  • [Platform] Worker components can now access the HF_TOKEN secret for gated Hugging Face model downloads.
  • [Platform] Swagger UI assets are now self-hosted, with HTTPS-aware security headers behind TLS-terminating ingresses.
  • [Platform] Fixed Model Zoo pod startup and Docker build failures.
  • [Platform] Fresh-namespace installs no longer show a temporary login error while the UI finishes starting up.
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