Track what happened after the launch announcement: browse the source-linked AI feature availability tracker, including plan, region and platform scope. Kingy has not tested account-level access.
Verified AI Launch Intelligence
See what launched, what changed, and what it costs.
Track AI product launches, model updates, pricing changes and tested workflows. Each record separates official sources, company claims, Kingy testing and third-party evidence so you can see what is known and what remains unverified.
Editorial submissions and sponsor-fit reviews are separate. Payment does not influence Kingy scores, verdicts, rankings, evidence labels, or publication decisions.
Launch tracker
Browse the AI Launch Tracker
Search source-backed launch records, then use common filters first and advanced filters only when you need a narrower view.
BaseRT local LLM runtime for Apple Silicon
BaseRT’s second Product Hunt launch appeared on July 19, presenting a one-command local LLM runtime for Apple Silicon after the BaseRT 0.1.6 engine release on July 18.
BaseRT is a focused option for developers who want Apple Silicon inference behind familiar CLI and OpenAI-compatible interfaces. Its practical value depends on model…
Jan v0.8.3 release
Jan released v0.8.3 with fixes across MCP browser-port handling, backend installs, media handling, and chat rendering.
- Launch readiness
- 7.4 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-24.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Jan's v0.8.3 release on GitHub fixes MCP browser-port handling, backend installs, media handling, and chat rendering in its open-source, local-first desktop assistant (github.com/janhq/jan). It…
ComfyUI v0.26.0 release
ComfyUI v0.26.0 added Qwen3-VL text generation, SCAIL-2 multireference support and context-window sampling for LTX2 with IC-LoRa guides, alongside workflow and node updates.
Version 0.26.0 adds specific capabilities, including Qwen3-VL text generation and SCAIL-2 multireference support. Before changing a working graph, check the required ComfyUI version, model…
Ollama v0.30.10 release
Ollama released v0.30.10 with Apple Silicon MLX support for Command A and North family models, plus llama.cpp and build-artifact updates.
- Launch readiness
- 7.7 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-24.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Ollama's v0.30.10 release adds Apple Silicon MLX support for the Command A and North model families, plus llama.cpp and build-artifact updates, per the GitHub…
Open WebUI v0.9.6 release
Open WebUI released v0.9.6 with knowledge-base sync, folder organization, filesystem tooling, permissions, and security-related fixes.
- Launch readiness
- 7.6 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-24.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
Open WebUI's v0.9.6 release adds knowledge-base sync, folder organization, filesystem tooling, permissions work, and security-related fixes, per the GitHub release (github.com/open-webui). Developers, Operators, and…
LM Studio 0.4.0 launch
LM Studio introduced version 0.4.0 with server deployment, parallel requests, continuous batching, a new REST API endpoint, and a refreshed UI.
- Launch readiness
- 7.1 / 10
- Demo evidence
- Not scored yet
- Creator-story fit
- Not scored yet
Score definitions and rubric
These are launch-record readiness heuristics, not product ratings.
Launch readiness
How complete and reviewable the launch record is, not the quality of the product.
Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.
Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.
Demo evidence
Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.
Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.
Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.
Creator-story fit
Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.
Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.
Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.
- Scale
- 0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
- Assigned by
- Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
- Rubric and check date
- Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-24.
- Confidence and missing data
- Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
- Freshness
- Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
- Disputes
- Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.
LM Studio introduced version 0.4.0 with server deployment, parallel requests, continuous batching, a new REST API endpoint, and a refreshed UI (lmstudio.ai). Developers, Researchers,…
Daily radar
Latest verified AI launches
A Radar edition publishes only when the day has enough source-ready signal; the tracker continues to show the newest verified records.
Daily AI Launch Radar: Genie 4’s trusted-tester research preview
November 6 catch-up: Google DeepMind’s October 27 Genie 4 research preview, trusted-tester access, waitlist and limits on pricing and wider availability.
No source-ready records are tagged for today yet, so this section is showing the latest public launch records available in the tracker.
Gemini Omni 1.2 Flash
Summary: Google launched Gemini Omni 1.2 Flash on November 5, 2026, with general availability through the Gemini API and Gemini for business.
Why it matters: Gemini Omni 1.2 Flash gives video teams longer native clips and editing controls. Check the selected output settings and actual billing units before estimating…
- Pricing
- The announcement lists US$0.07 per second for 720p video. The API changelog separately lists US$12 per million video output tokens. These are different billing units; check the applicable settings and current terms.
- Verification
- Source-verified; 2 sources
GPT-6 Cyber
Summary: OpenAI introduced GPT-6 Cyber on November 5, 2026, with initial API and Codex access for select approved Daybreak Red customers. Wider access is planned.
Why it matters: GPT-6 Cyber is relevant to security teams eligible for Daybreak Red. Confirm approval, permitted use and pricing before planning work around its restricted API…
- Pricing
- Standard API rates per million tokens are US$20 input, US$2 cached input and US$100 output. Cache writes are US$25 for 30 minutes or US$50 for 12 hours per million tokens. Context length and processing choices can change rates; confirm approved-access terms and the current pricing table.
- Verification
- Source-verified; 2 sources
ChatGPT Images 2.6
Summary: OpenAI released Images 2.6 on November 4, 2026, in ChatGPT and Codex across all subscription tiers, plus Sunburst and Flare API variants.
Why it matters: Images 2.6 expands image workflows across OpenAI products. Compare Sunburst and Flare on your own edits and check API billing separately from subscription limits.
- Pricing
- API rates per million tokens for both variants: image input US$8, cached image input US$2 and image output US$30; text input US$5 and cached text input US$1.25. Subscription limits and API billing are separate.
- Verification
- Source-verified; 2 sources
Mistral Large 4 (Le Chonk) weights
Summary: Mistral made improved Large 4 weights downloadable on October 29, 2026, following its October 6 public preview. The repository documents text and image input, text output,…
Why it matters: Mistral Large 4 gives teams a documented choice between an API and downloadable weights. Evaluate the commercial-license restriction, infrastructure cost and your own task…
- Pricing
- Mistral's USD model documentation lists $0.70 input, $0.07 cached input and $2.10 output per million tokens. Self-hosting costs are separate.
- Verification
- Source-verified; 4 sources
GitHub Copilot Fusion
Summary: GitHub announced Copilot Fusion general availability on October 28, 2026, on all Copilot plans in VS Code, the Copilot app, Copilot CLI and JetBrains IDEs. Users…
Why it matters: GitHub Copilot Fusion gives existing Copilot users an orchestration option in supported clients. Confirm your plan’s models and effort settings, monitor credit use and…
- Pricing
- Each underlying model is billed at its standard rate with no separate Fusion charge. Official docs specify a 30% paid-plan model-cost discount through November 30, 2026. Multiple-model tasks can consume more credits.
- Verification
- Source-verified; 2 sources
Gemini 4 Carbon
Summary: Google announced Gemini 4 Carbon on October 28, 2026. Access starts with a subset of cyber defenders and is to expand gradually to trusted Fairwind partners.…
Why it matters: Gemini 4 Carbon is currently relevant to teams admitted to Google’s controlled cyber-defense rollout. Broader developer, business and consumer access is a future step.…
- Pricing
- Announced introductory API rates are US$2 per million input tokens and US$10 per million output tokens, with cached input 95% below the input rate. Google lists later rates of US$4 and US$20 after the introductory period, without a confirmed expiry here. These announced rates do not establish a generally callable public API.
- Verification
- Source-verified; 2 sources
Plan ahead
Upcoming Deadlines
Future-dated migration, shutdown, and retirement records are separated from today's launches and latest-record lists. These dates are upcoming operational events, not launches that have already happened.
OpenAI Agent Builder shutdown deadline: November 30, 2026
Summary: OpenAI announced the Agent Builder lifecycle deadline: the visual workflow builder is deprecated and scheduled to shut down on November 30, 2026. OpenAI documents two migration…
Why it matters: Export the workflow, select the Agents SDK or a suitable Workspace Agent, and test tools, state, permissions and guardrails before the November 30 shutdown.…
- Pricing
- Review replacement API costs or Workspace Agent plan requirements before migrating. This record does not estimate your workflow’s implementation or operating cost.
- Verification
- Recheck due; 3 sources
OpenAI reusable prompt objects and v1/prompts are scheduled to shut down November 30, 2026
Summary: OpenAI announced reusable-prompt deprecation on June 3, 2026. The documented November 30 shutdown covers reusable prompt objects and v1/prompts. Move managed prompt content into application-owned code…
Why it matters: Treat saved OpenAI prompt objects as a migration dependency before November 30. Move their content and variables into application code, then validate the generated…
- Pricing
- Pricing unknown
- Verification
- Recheck due; 5 sources
Three GPT Image API models are scheduled to retire December 1, 2026
Summary: OpenAI schedules gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest for API removal on December 1, 2026. Its current deprecation table recommends gpt-image-2.5-sunburst or gpt-image-2.5-flare.
Why it matters: OpenAI schedules gpt-image-1-mini, gpt-image-1.5 and chatgpt-image-latest for API removal on December 1, 2026. Its current deprecation table recommends gpt-image-2.5-sunburst or gpt-image-2.5-flare. Inventory the three…
- Pricing
- Review the current price of the chosen replacement and measure representative jobs. This lifecycle record does not establish workload cost or promise a cost-neutral migration.
- Verification
- Recheck due; 5 sources
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AI assistants sent 1.3279% of kingy.ai's own traffic. Published studies put the web-wide figure anywhere from under 1% to 25%. The index reconciles them, catalogued by method.
Methodology
How Kingy AI Scores Launches
Kingy AI scoring is designed for launch discovery, editorial review, creator planning, and buyer trust checks.
Kingy score
A directional editorial score for launch clarity, source quality, audience fit, pricing visibility, demo usefulness, and practical buyer or creator value.
Demo score
A signal for whether the product can be shown, tested, explained, or compared without relying on vague announcement copy.
YouTube potential
A creator-fit signal for demos, tutorials, before-and-after workflows, explainers, reviews, and audience-specific product education.
Source verification
Records distinguish verified, needs verification, and founder submitted status using official URLs, source links, last-verified dates, and correction paths.
Pricing clarity
Pricing signals favor launches with visible pricing, free-plan status, pricing pages, API access notes, or clear uncertainty when pricing is not public.
Use-case clarity
Launches are easier to evaluate when the audience, workflow, category, demo, and alternative comparison are obvious from public sources.
Founder and sponsor fit
Founder submissions and sponsor interest are routing signals only; editorial review still checks source quality, public claims, demo clarity, and usefulness.
Verification labels
Verified means enough public source evidence is present, needs verification means the record needs more checking, and founder submitted means the entry came through the submission path.
Scores are editorial signals, not scientific benchmarks, paid placements, or guarantees.
Founder submission
Submit Your AI Launch
Founders can send a launch for editorial review when the public source trail is ready to verify.
What to include
- Product name
- Website
- Launch date
- What launched
- Official source links
- Pricing page
- Demo/video
- Company info
- Category
- Public funding info
- Screenshots/media
Privacy note
Do not submit secrets, unreleased financials, private customer data, or regulated personal data.
Submit only public product, company, source, pricing, demo, and media details that Kingy AI can review without logging into private systems.
Sponsor path
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Want the whole tracker as data? Download every launch record as CSV or JSON, CC BY 4.0, with a citable DOI per monthly edition.