Releasesby GlyphApp-Level Retry Configuration
Apps can now register a default per-condition retry budget at deploy time with the new retry_config deployment option, using the same format as the X-Fal-Retry-Config request header. Set it as a class attribute on fal.App or under the app's table in pyproject.toml .
Also shipped Jul 8, 2026fal in July 2026 →
Object metadata column is now in Public Preview
The _object_metadata column is now in Public Preview. The _object_metadata column is a hidden metadata column that exposes object-level properties for objects in cloud storage, including MIME type, ETag, user-defined key-value metadata, system-defined metadata, and object tags. It is available starting from Databricks Runtime 18.1.
Genie products now use pay-as-you-go pricing
Starting July 8, 2026 at 00:00 UTC, Genie products, including Genie Agents , Genie Code , and Genie One , are billed following a pay-as-you-go pricing model that includes 150 Databricks units (DBUs) of free large language model (LLM) usage every month, equivalent to about $10.50 in the US East region.
Google Gemini 2.5 Flash and Pro are scheduled for retirement
Google Gemini 2.5 Flash and Gemini 2.5 Pro will be retired on October 2, 2026. The recommended replacement models are Gemini 3.1 Pro or Gemini 3.5 Flash. See Deprecated and retired models for migration guidance.
Anthropic Claude Sonnet 4 is scheduled for retirement
Anthropic Claude Sonnet 4 will be retired on October 9, 2026. Claude Sonnet 4.6 is the recommended replacement. See Deprecated and retired models for migration guidance.
Restrict access to AI Functions with Unity Catalog permissions (Public Preview)
You can now use Unity Catalog permissions to restrict which task-specific AI Functions your organization can access, independent of foundation model access. Contact your account team to enable this feature. See AI Functions Unity Catalog permissions .
Genie Agents now uses pay-as-you-go pricing
Starting July 8, 2026 at 00:00 UTC, Genie Agents is billed following a pay-as-you-go pricing model that includes 150 DBUs of free large language model (LLM) usage every month, equivalent to about $10.50 in the US East region. Usage beyond the free amount is billed in DBUs, reflecting the underlying LLM models and agents that power each Genie Agents session.
More from falEvery fal release →
New Serverless Usage Page
The new Serverless Usage page (Serverless → Usage) provides attributable, dimensioned reporting of serverless compute spend in the dashboard. Compute reported in machine-seconds , broken down per app, environment, and machine type. Spend is split by price category: Reserve, Burst, On-Demand, and List.
Redesigned Usage & Billing Page
The Usage & Billing page has been rebuilt to support usage attribution (the Settings "Overview" tab is now "Usage"). Filter by auth method, API key, and login username to attribute consumption to a specific credential or user. Normalized app names and revised charts improve readability and export.
Serverless Usage API
- New GET /v1/serverless/usage endpoint reports your own serverless compute usage , the machine-seconds each of your deployed apps consumed, priced with your machine rates and net of discounts Break usage down per app, environment, and machine type, with time_series and summary views over any date range and timeframe Filter by app name with app (exact, one...
Deploy Messages and Annotations
You can now attach a freeform message and custom annotations to each revision when deploying: Messages and annotations are set at deploy time and stay with the revision. View and search them on the app's Versions page in the dashboard, or fetch them via the revisions API .
GPU Utilization in Runner Telemetry
Runner telemetry now includes a dedicated GPU Utilization chart alongside the existing CPU, memory, and VRAM charts, so you can see how much compute your GPUs are actually doing -- not just how much memory they hold.
New Capacity Page
The new Capacity page (Serverless → Capacity) reports GPU consumption against your account limit, providing visibility into available headroom before requests begin queuing. Account-wide GPU usage over time, plotted against your limit , with baseline and burst reference lines indicating utilization relative to reserved capacity.
Per-Condition Retry Configuration
The new X-Fal-Retry-Config request header replaces all-or-nothing retry behavior with a separate retry budget per failure condition, allowing retry policy to be tuned independently for each failure mode.
Filter and Sort Apps
Managing a large number of serverless apps is now easier with new filtering and sorting controls directly on the apps page . Filter by machine type to instantly isolate apps running on specific hardware (e.g., H100, A100, L40) and monitor targeted resource allocation.