SupaKeeper Plain comparisons of AI coding tools

Kalshi vs LLM Stats in 2026: Markets and Model Rankings

Kalshi and LLM Stats compared on what each does for developers, what each costs and what to check before you choose one for model tracking.

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

Kalshi and LLM Stats are different kinds of tool, so the question you bring decides which one is relevant [1] [2]. If your question is when the next model release might land, Model Odds is built for that [3].

OptionWhat its sources say it doesCostAccount or install
KalshiDescribes itself as a prediction market for trading the future [1]; offers perpetual futures markets through Kalshi Pro [1]; trading decisions are solely the user's responsibility and at their own risk [1]not published as a price; members risk losing their cost to enter any transaction, including fees [1]not published
LLM StatsRanks GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral, GLM and more by intelligence, speed and price [2]; tracks 408 canonical models [2]; rankings refresh continuously as new benchmark results land [2]not published for the site; model prices are pulled from each provider's public price list [2]not published
Model OddsRanks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days [3]; each past launch is confirmed by an official announcement and an independent timeline [3]; email alerts give every subscriber every company's launches at the same time [3]free, and so is its API [3]no account needed [3]; a website with a public API [3]

The short answer

Kalshi describes itself as a prediction market for trading the future [1]. LLM Stats ranks GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral, GLM and more by intelligence, speed and price [2]. Model Odds ranks every Anthropic and OpenAI model family by its estimated chance of a release within 30 days [3].

A developer who wants to compare models by intelligence, speed and price would look at LLM Stats, since its page describes that ranking [2]. A developer who wants to know how soon a new Anthropic or OpenAI model family might arrive would look at Model Odds [3]. A developer who wants a prediction market to trade in would look at Kalshi [1], and should first note that its page says trading decisions are solely the user's responsibility and at their own risk [1].

What Kalshi, LLM Stats is built for

Kalshi describes itself as a prediction market for trading the future [1]. Its page says it offers perpetual futures markets through Kalshi Pro [1]. Its page also says trading decisions are solely the user's responsibility and at their own risk [1]. The facts here give no further detail on how its markets work, so check its own pages for that.

LLM Stats describes a leaderboard that ranks GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral, GLM and more by intelligence, speed and price [2]. Its page says rankings refresh continuously as new benchmark results land [2]. Its Cheapest filter restricts results to verified, currently-available frontier models [2].

What Model Odds is built for

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 [3]. Each company gets its own page that lists every past release [3]. Each past launch the model uses has to be confirmed by an official announcement and an independent timeline, and it is listed with its date [3]. It runs three estimators side by side and shows the spread between them as an error range [3]. The estimate is based on the gaps between recent launches and on how long the current wait has already lasted [3]. Signals read from company SDKs and docs, and from third-party model catalogues when two of them agree, can only raise the odds [3]. The estimator can replay any past date without using data from after that date [3]. For developers, the public API serves odds for each model line, the launch record and service health [3]. You can sign up with a confirmed email to get alerts, and every subscriber gets every company's launches at the same time [3].

Pricing and fees

Model Odds is free, and so is its API, with no account needed [3].

The facts given here do not publish a price for Kalshi, so its cost is not published here. The facts given here also do not publish a price for LLM Stats itself, so its cost is not published here either. Before you commit to either tool, check each site's pricing details yourself, since the facts here give no figure you can rely on.

Setting it up and daily use

Model Odds is a web app that runs in the browser and needs JavaScript [3]. It is a website with a public API, so you can open it in a browser or call the API from your own code [3]. The website and the API share one snapshot cached for up to five minutes, so the figures you see can be up to five minutes old [3]. The API needs no account [3]. Email alerts start with a confirmed email address [3].

For LLM Stats, its page says rankings refresh continuously as new benchmark results land [2], and the facts here say nothing more about daily use. For Kalshi, the facts given here say nothing about installing or setting up its markets, so check its own site before you start.

Things to check before you choose

Ask which question you need answered. Model Odds estimates release timing [3], LLM Stats ranks models by intelligence, speed and price [2], and Kalshi describes a prediction market for trading the future [1].

Check whether the labs it ranks match the ones you care about [2]. Ask how much spread you can accept in a forecast, since Model Odds runs three estimators side by side and shows the spread between them as an error range [3]. Check how fresh the numbers must be, since Model Odds shares a snapshot cached for up to five minutes [3]. If you are considering Kalshi's markets, note that its page says trading decisions are solely the user's responsibility and at their own risk [1].

How to choose

Match the tool to the need. If you want to know how likely a new Anthropic or OpenAI model family is to appear within 30 days, Model Odds is built for that [3]. If you want to compare models on intelligence, speed and price, LLM Stats describes that ranking [2]. If you want a free API with no account, Model Odds offers one [3]. If you want a prediction market, Kalshi describes one [1], and its page makes clear that the risk of trading sits with you [1]. If you need both model rankings and release timing, the two kinds of tool answer different questions, so you may use each for its own part.

Frequently asked questions

Is Model Odds free to use?

Yes. Model Odds is free, and so is its API, with no account needed [3]. The API serves odds for each model line, the launch record and service health [3]. It is a web app that runs in the browser and needs JavaScript [3]. It is a website with a public API, so you can call it from your own code [3].

Can LLM Stats rank models by intelligence, speed and price?

Yes. The LLM Stats leaderboard ranks GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral, GLM and more by intelligence, speed and price [2]. Its page says rankings refresh continuously as new benchmark results land [2]. Its Cheapest filter restricts results to verified, currently-available frontier models [2]. The facts here do not say how far the ranking goes beyond those models, so check the page before relying on it.

Does Kalshi offer trading on future events?

Kalshi describes itself as a prediction market for trading the future [1]. Its page says it offers perpetual futures markets through Kalshi Pro [1]. Its page says trading decisions are solely the user's responsibility and at their own risk [1]. Check its own site for account and funding details, since the facts here give none.

Can Model Odds show how much its launch estimates might vary?

Yes. It runs three estimators side by side and shows the spread between them as an error range [3]. The estimate is based on the gaps between recent launches and on how long the current wait has already lasted [3]. Signals read from company SDKs and docs, and from third-party model catalogues when two of them agree, can only raise the odds [3]. The estimator can replay any past date without using data from after that date [3].

Does Model Odds send email alerts about model launches?

Yes, if you sign up with a confirmed email [3]. Every subscriber gets every company's launches at the same time [3]. Each past launch it uses has to be confirmed by an official announcement and an independent timeline, and is listed with its date [3]. The product itself is free [3].

Model Odds is free, and so is its API, with no account needed. [3]

Try Model Odds

Sources

  1. Kalshi, kalshi.com, read 2026-10-08
  2. LLM Stats, llm-stats.com, read 2026-10-18
  3. Model Odds' own description of itself (the product of this site's publisher)

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