How to track when new models are slated to release for AI researchers in 2026

Learn how AI researchers can track when new models are slated to release, with steps, tools, and mistakes to avoid.

By SupaKeeper · 2026-10-15

SupaKeeper is published by LunarWerx, which makes some of the tools compared here.

To track when new models are slated to release, gather the model families and labs you follow, choose a tool or workflow that surfaces release timing, and check that the source stays current and cites its evidence.

Option	What it can do	What to check
Model Odds	Ranks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days, with three estimators and a verified launch record. ^[1] ^[1] ^[1] Free, including its API, with no account needed. ^[1]	Check whether its coverage of model families and its alert and API options match the research workflow.
Lab announcements and release notes	Use the announcements and documentation already published by the labs being followed.	Check whether the current approach gives the timing visibility needed across all relevant model families.
Model catalogue or newsletter	A separate source may provide a way to track release details across labs.	Check which model families and labs it covers, how it confirms launches, and how often it updates before choosing it.

What you need before you start

Before tracking release timing, have a clear list of the model families and labs that matter for research. Know which companies and model lines are relevant, and keep notes on past release dates that can serve as a reference point.

Keep the model names or family names that help distinguish each release. A useful tracking setup should make it easier to tell which models are expected soon without checking many separate sources.

Decide whether the main need is seeing estimated timing, browsing a history of past launches, getting alerts, or checking an API for programmatic access. Different tools may focus on different parts of release tracking.

Check whether a tool covers the model families you follow and whether it works in the environment you use. This helps avoid choosing a workflow that does not match the way releases are monitored.

Step by step

Gather the model families and labs that need to be tracked. Include the companies and model lines that matter for research planning.

Choose a way to collect release timing information into one place. The option can be a dedicated tool, an API, or a workflow that organizes release details for you.

Open the release view and check that each entry is clear enough to identify. Useful details can include the model family, the lab, and any estimated timing connected to the release.

Search or filter the list when looking at a specific model family. This reduces the time spent checking sources one by one.

Review how the view handles updates. A release tracker should match how often new information arrives or changes during normal monitoring.

Keep a simple routine for noting which model families are most relevant. Consistent tracking habits make future checks easier.

Recheck the tool choice when research priorities change. Confirm that the chosen source covers the needs that matter now, such as alerts, API access, or historical launch records.

Tools that can do it

Model Odds is made by the team that publishes this site.

Model Odds is a website with a public API. ^[1] It is a web app that runs in the browser and needs JavaScript. ^[1]

Model Odds ranks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days. ^[1] Anthropic and OpenAI each get their own page that lists every past release. ^[1]

Model Odds runs three estimators side by side and publishes the spread between them as the error bar. ^[1] The estimate is a renewal process fitted on the gaps between recent launches, and it takes into account how long the current wait has already lasted. ^[1]

Each past launch the model uses has to be confirmed by an official post and an independent timeline, and it is listed with its date. ^[1]

An API serves per-line odds, the launch record, and service health. ^[1]

Model Odds is free, and so is its API, with no account needed. ^[1]

Other approaches include following lab announcements and release notes directly, or using a model catalogue or newsletter after checking what it covers and how it handles timing. Compare each option against the exact job of tracking when new models are slated to release.

Common mistakes to avoid

Avoid choosing a release tracker without checking which model families it covers. Check which labs appear in the source before relying on it for monitoring.

Avoid relying on a single source without verifying how it confirms launches. A tracker is harder to trust when past entries are not backed by official posts or independent timelines.

Avoid ignoring how often the data updates. A release tracker should be checked against how frequently new information arrives.

Avoid assuming that every tool provides the same access methods. Check whether the option is focused on a web view or also covers needs such as alerts or API access that matter for a research workflow.

Frequently asked questions

How can AI researchers track when new models are slated to release?

AI researchers can track release timing by choosing a tool or workflow that matches the labs and model families being followed. The important checks are which models appear, how timing is estimated, and whether the source stays current and cites its evidence for past launches.

What should be checked before choosing a model release tracker?

Check which model families and labs the tracker covers, how it estimates timing, and whether past launches are confirmed by official sources. Also check whether the tool provides only a web view or includes other options such as alerts or API access that matter for research work.

Does Model Odds show release timing for AI models?

Model Odds ranks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days. ^[1] It runs three estimators side by side and publishes the spread between them as the error bar. ^[1] This can be compared with other sources by checking how each option handles timing and evidence.

Can a model release tracker help with research planning?

A release tracker can help with research planning by making expected timing easier to see across model families. The useful approach depends on how releases are estimated, how past launches are confirmed, and how often the data updates. Check whether the chosen tool provides the coverage needed for the labs being followed.

What mistakes should be avoided when tracking model releases?

Avoid selecting a tool without checking which model families it covers, and avoid relying on a source that does not confirm past launches with official posts or independent timelines. A good workflow starts with knowing which labs need to be tracked and what level of evidence is required for each entry.