Releasesby GlyphFLUX Deblur , Sharpen Blurry Images
A new FLUX Tools endpoint that takes a single blurry image and returns a sharper version of the same scene , no prompt, no mask.
Also shipped Jun 25, 2026Black Forest Labs in June 2026 →
Genie One enhancements
- Share chats with account users : You can now share Genie One chats with all users in your account as read-only. See Share a chat . New external source connections (Beta) : Chat in Genie One now supports connecting to Gmail and additional Microsoft 365 apps (Teams, Outlook, and Calendar). See Connect to external tools and sources .
Fast mode for Claude Opus 4.7 deprecated, removal on July 24, 2026
After July 24, 2026, requests to claude-opus-4-7 with speed fast will return an error. Anthropic recommends migrating to fast mode on Claude Opus 4.8.
Copilot code review: Analysis depth and efficiency updates
Copilot code review now uses the built-in file exploration tools available in the Copilot CLI and SDK, significantly improving review cost efficiency with no change to your existing workflow. If you’re in the Medium analysis depth public preview, you’ll also see some new updates centered around configurability and visibility of review depth.
Enterprise-managed settings now support strictKnownMarketplaces in VS Code and GitHub Copilot CLI
Enterprises can now control which plugins their users can install in GitHub Copilot CLI and VS Code. This setting is now available in public preview. Add strictKnownMarketplaces to your enterprise-managed settings.json , and Copilot will only allow plugins to be installed from the marketplaces you’ve explicitly defined.
Saved views for repository issues – Public Preview and adjustable row heights in projects
Saved views for repository issues Repository Issues pages now support saved views, making it easier for teams to create and share filtered views of their issues. With saved views, anyone with triage access or above can create shared views like “Unassigned bugs”, “Needs triage”, or “Customer-reported issues”.
Red Hat Enterprise Linux runner images are now in public preview
GitHub-hosted larger runners now support Red Hat Enterprise Linux (RHEL) 9 and RHEL 10 images in public preview, introduced in partnership with Red Hat. Organizations can use these RHEL images as the foundation for custom images that include required tools, dependencies, and configurations.
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Key Features
- Faithful restoration , Reconstructs fine detail while preserving character identity, colors, objects, lighting, and composition No prompt required , Send the image; the model sharpens the whole frame automatically Up to 4MP input , As base64 or an image URL Built for volume , Low-latency and low-cost, suited to interactive and high-throughput workflows
Endpoint
POST /v1/flux-tools/deblur-v1 Get started in the FLUX Deblur documentation .
Moderation Responses Now Include Reasons
When a request or result is moderated, the polling response's details field now includes a Moderation Reasons array naming the categories that triggered the filter (for example Violence or Sexual Content ). Use it to adjust the request or surface a message to your users.
FLUX Outpainting , New Fast Mode
FLUX Outpainting now supports a mode parameter that trades quality for speed.
Key Features
- mode: "fast" , Significantly faster extension, well-suited for landscapes, backgrounds, textures, and products. Typically lower cost. mode: "high" (default) , Unchanged highest-fidelity path; recommended when fine detail, prompt adherence, or consistency with complex source content matters.
Endpoint
POST /v1/flux-tools/outpainting-v1 See Choosing a mode in the FLUX Outpainting documentation.
FLUX Virtual Try-On v2 , Sharper Face Preservation
vto-v2 is a new version of FLUX Virtual Try-On focused on keeping the person's identity intact, with additional gains in garment fidelity.
Key Features
- Improved face preservation , markedly better retention of the model's identity and facial features in the try-on result Better garment detail , minor improvements to garment textures, prints, and trims Higher-resolution output , inputs up to 4 Megapixels are used as-is, and the result follows the model image's resolution (up from 2 Megapixels in vto-v1 )...