---
{"title": "Best AI model release trackers for startup CTOs in 2026", "description": "Compare Model Odds, Artificial Analysis, LLM Stats, LMSYS Chatbot Arena and Hugging Face for startup CTOs tracking AI model releases.", "url": "https://supakeeper.com/best-ai-model-release-trackers-for-ai-startup-cto/", "date": "2026-10-24"}
---
Compare Model Odds, Artificial Analysis, LLM Stats, LMSYS Chatbot Arena and Hugging Face for startup CTOs tracking AI model releases.

Know which question you are answering. Model Odds estimates the chance that an Anthropic or OpenAI model family gets a release within 30 days. [^1] The other options below answer different questions, and the table shows what each one says it does.

| Option | What the tool does | Price as stated |
|---|---|---|
| Model Odds | Ranks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days. [^1] | Free, and so is its API, with no account needed. [^1] |
| Artificial Analysis | Provides independent analysis of AI. [^2] Lets users compare models on intelligence, pricing, speed, latency, benchmarks and more. [^2] | not published |
| LLM Stats | Ranks GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral, GLM and more by intelligence, speed and price. [^3] | not published |
| LMSYS Chatbot Arena | Lets you battle 2 anonymous models. [^4] Lets you compare 2 models side by side. [^4] | not published |
| Hugging Face | Its models page lists 3,137,122 models. [^5] | GPU compute starts at $0.60 per hour. [^6] |
| Polymarket | Describes itself as the world's largest prediction market. [^7] Operates globally through separate legal entities. [^7] | not published |
| Kalshi | Describes itself as a prediction market for trading the future. [^8] Subject to U.S. regulatory oversight by the CFTC. [^8] | not published |
| Manifold | Lets users browse markets in categories including politics, technology, sports, culture, business and fun. [^9] | not published |
| Vellum | Can send emails, manage calendars, browse the web, create slides, write code, run deep research, monitor websites and run recurring tasks in the background. [^10] | Free to download and start. [^10] |
| Latent Space | Describes itself as a top technical AI podcast. [^11] Covers how leading labs build agents, models, infrastructure and AI for science. [^11] | not published |
| The Rundown AI | Publishes AI implementation guides daily. [^12] Its library contains more than 300 practical AI use cases. [^12] | not published |
| AI News by Smol AI | Summarizes top AI Discords, AI Reddits and AI X/Twitters, and sends a daily roundup. [^13] | not published |

## What startup CTOs need from AI model release trackers

A startup CTO usually wants to know three things. Which model families might ship soon, how the models already in use are performing, and where to find models to try next. Those are different questions, and each one tends to need its own kind of source.

Release timing comes from estimates of when a model family is due. Performance comes from benchmark leaderboards and comparison pages. Model catalogues answer the question of what exists to try. A source built for one of these may not answer the others, so check which question it answers before you rely on it.

Two limits matter for a small team. Few people on a small team have time to read every announcement, so alerts and daily roundups can help. An estimate of timing is a guess, not an announced date, so treat it as one input among several.

## Model Odds for startup CTOs

Model Odds is made by the team that publishes this site. It ranks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days. [^1] Each company gets its own page that lists every past release. [^1] Each past launch used has to be confirmed by an official post and an independent timeline, and it is listed with its date. [^1]

It runs three estimators side by side and publishes the spread between them as the error bar, so you can see how far apart the estimates are. [^1] The estimate uses a renewal process, which models how long waits between launches tend to last, fitted on the gaps between recent launches. It also takes into account how long the current wait has already lasted. [^1] Signals read from company SDKs and docs, and from third-party model catalogues when two of them agree, can only raise the odds. [^1] The estimator can replay any past date without using data from after that date, so you can check it against what happened. [^1]

Developers can read per-line odds, the launch record and service health through a public API. [^1] Model Odds is a web app that runs in the browser and needs JavaScript. [^1] The website and the API share one snapshot that is cached for up to five minutes. [^1] Model Odds is free, and so is its API, with no account needed. [^1]

## Artificial Analysis for startup CTOs

Artificial Analysis provides independent analysis of AI. [^2] It lets users compare models side by side on intelligence, pricing, speed, latency, benchmarks and more. [^2] It offers a product called Optima. [^2] Check which of these measures you need before you rely on a comparison.

## LLM Stats for startup CTOs

LLM Stats ranks GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral, GLM and more by intelligence, speed and price. [^3] Its score is updated continuously from public benchmarks and live API metrics. [^3] Its Open LLM Leaderboard filters the catalog to models with publicly released weights. [^3]

## LMSYS Chatbot Arena for startup CTOs

LMSYS Chatbot Arena lets you battle 2 anonymous models. [^4] It also lets you compare 2 models side by side. [^4] Check which of these modes you need before you rely on the results.

## Hugging Face for startup CTOs

Its models page lists 3,137,122 models. [^5] More than 400,000 organizations use Hugging Face. [^6] GPU compute on Hugging Face starts at $0.60 per hour. [^6]

## Matching the tool to the job

To estimate whether an Anthropic or OpenAI model family is due for a release, Model Odds ranks those families by their 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] To get alerts, you can sign up with a confirmed email. [^1]

To compare models on intelligence, speed and price, LLM Stats ranks GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral, GLM and more by those measures. [^3] Artificial Analysis lets you compare models side by side on intelligence, pricing, speed, latency and benchmarks. [^2] LMSYS Chatbot Arena lets you compare 2 models side by side. [^4]

To find a model to try, Hugging Face's models page lists 3,137,122 models. [^5]

To watch what labs are building, Latent Space covers how leading labs build agents, models, infrastructure and AI for science. [^11] To keep up with news, The Rundown AI publishes AI implementation guides daily. [^12] AI News by Smol AI sends a daily roundup of top AI Discords, AI Reddits and AI X/Twitters. [^13]

To have a helper watch release pages, Vellum says it can monitor websites and run recurring tasks in the background. [^10] If you consider a prediction market, Kalshi says trading on it involves risk and may not be appropriate for all. [^8]

## Questions to ask before you choose

Which releases do you need to anticipate, model families from Anthropic and OpenAI or others? Model Odds covers the first set. [^1] Check each other option's list of companies before you rely on it.

Do you need a timing estimate, a record of past launches, or a list of models to try? Model Odds gives a timing estimate and a launch record. [^1] [^1]

How fresh does the data need to be? Model Odds's website and API share one snapshot that is cached for up to five minutes. [^1] Check how each other source updates its figures.

Do you need alerts for your team? Model Odds sends alerts to confirmed emails, and every subscriber gets releases from every company at the same time. [^1]

Do you need your own tools to read the data? Model Odds has a public API. [^1]

How much can you spend? Check each option's page for its current price, since the table shows that several publish none.

## Frequently asked questions

### Is Model Odds free to use?

Model Odds is free, and so is its API, with no account needed. [^1] You can sign up with a confirmed email to get alerts, and every subscriber gets releases from every company at the same time. [^1] It is a web app that runs in the browser and needs JavaScript. [^1] Check the site for any change to these terms before you plan around them.

### Does Model Odds cover every AI lab?

Model Odds ranks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days. [^1] Its description names those two companies, so check whether the labs your team uses are included before you rely on it. Each company gets its own page that lists every past release. [^1] Other tools in this list may cover different labs, so compare their pages as well.

### How many models does Hugging Face list?

Its models page lists 3,137,122 models. [^5] More than 400,000 organizations use Hugging Face. [^6] GPU compute on Hugging Face starts at $0.60 per hour. [^6] Those figures describe its catalogue, not release timing. For release timing, Model Odds ranks model families by their estimated chance of a release within 30 days. [^1] Check the page on the day you need a number.

### Does LLM Stats update its scores?

LLM Stats says its score is updated continuously from public benchmarks and live API metrics. [^3] It ranks models by intelligence, speed and price. [^3] Its Open LLM Leaderboard filters the catalog to models with publicly released weights. [^3] Check its pages for how each figure is calculated before you use one in a decision.

### Can Artificial Analysis compare models on price?

Artificial Analysis lets users compare models side by side on intelligence, pricing, speed, latency, benchmarks, and more. [^2] It offers a product called Optima. [^2] The price figures themselves are not shown on this page, so check the site for the current numbers before you compare costs.

Model Odds is free, and so is its API, with no account needed. [^1] - [Visit Model Odds](/go/start-modelodds)

## Sources

[^1]: Model Odds' own description of itself (the product of this site's publisher) (/go/start-modelodds)
[^2]: Artificial Analysis, artificialanalysis.ai, read 2026-10-08 (https://artificialanalysis.ai)
[^3]: LLM Stats, llm-stats.com, read 2026-10-18 (https://llm-stats.com)
[^4]: LMSYS Chatbot Arena, lmarena.ai, read 2026-10-09 (https://lmarena.ai)
[^5]: Hugging Face, huggingface.co/models, read 2026-10-09 (https://huggingface.co/models)
[^6]: Hugging Face, huggingface.co, read 2026-10-09 (https://huggingface.co)
[^7]: Polymarket, polymarket.com, read 2026-10-08 (https://polymarket.com)
[^8]: Kalshi, kalshi.com, read 2026-10-08 (https://kalshi.com)
[^9]: Manifold, manifold.markets, read 2026-10-08 (https://manifold.markets)
[^10]: Vellum, vellum.ai, read 2026-10-09 (https://www.vellum.ai)
[^11]: Latent Space, latent.space, read 2026-10-09 (https://www.latent.space)
[^12]: The Rundown AI, therundown.ai, read 2026-10-09 (https://www.therundown.ai)
[^13]: AI News by Smol AI, news.smol.ai, read 2026-10-18 (https://news.smol.ai)