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How it works

How it works

We turn independent tests and people's votes into a pick for your task, then tell you which app and plan gets it. Here's each step, using the site's own data.

Models compared

16 from Anthropic, OpenAI, Google, DeepSeek and Moonshot AI.

Tests and vote categories

26, each explained on Tests explained.

Everyday tasks

46 task pages, named after what people search for.

Last updated

26 Sept 2026. Plans checked 26 Sept 2026.

From test to pick

Four steps, shown for coding and building apps, the task people search for most.

  1. 1

    Gather the evidence

    Tests and votes that measure the task, each labelled by how closely it matches.

    3 tests for coding and building apps

  2. 2

    Score each model

    Combine its place on every test into one task score.

    Claude Fable 5.1 comes 1st of 10

  3. 3

    Make the picks

    Best overall, best for $25 a month or less, and best free.

    3 picks

  4. 4

    Match to a plan

    Find the cheapest app and plan that includes each pick.

    Claude Max, $100/month

Where the evidence comes from

Our own tests, plus free, public sources whose licences let us show their data. Every chart names its source underneath, and our own results carry the navy Tested by us tag.

Tested by usOurs

Our own tests of everyday work, with every question and every model's answer published

We use
1 test
Licence
Ours

Epoch AI

Results from independent tests of real work, like fixing code or answering expert questions

We use
11 tests
Licence
CC BY 4.0
As of
26 Sept 2026

LMArena

People comparing two anonymous answers and picking the better one

We use
14 vote categories
Licence
CC BY 4.0
As of
25 Sept 2026

models.dev

Prices, release dates and how much each model can read

We use
16 models
Licence
MIT
As of
26 Sept 2026

Makers' own pages

Which plans include which model, and what makers claim at launch (always labelled)

We use
4 apps, 13 plans
Licence
Cited
As of
26 Sept 2026

How close a test is to your task

Hardly any test measures an everyday task exactly, so every test on a task page carries one of three labels.

Tests this task

The test is this kind of work.

17 task pages rest mainly on this

General ability

It tests overall ability. Used only when nothing closer exists.

0 task pages rest mainly on this

A more specific task, like vibe coding, borrows its broader task's tests when it has none of its own, labelled as related at most.

The task score

On each test, the lowest of our models is placed at 0 and the highest at 100. A model's task score is the average of its places. Here's how the top of coding and building apps is worked out:

ModelWould a real maintainer accept its code?
Tests this task
Building features in real software projects
Tests this task
People's votes on coding questions
Tests this task
Task score
Claude Fable 5.1
1st
90–7583
GPT-6 Astra
2nd
1001003879
GPT-5.6 Sol
3rd
77984372
Kimi K3
4th
63916172
  • It's relative. It shows who leads among the models we track, not how good they are in absolute terms. Last place isn't useless.
  • A test needs at least 3 of our models before it counts, so two results can't decide a ranking.
  • A model needs results on at least half the tests, including at least one test of real work when the task has one. People's votes alone can't put a model on the chart.
  • A dash means the model hasn't taken that test; its score averages the tests it has.

4 more models have some results for coding and building apps but not enough to score yet.

The picks

Every task page opens with picks made by a fixed rule, so they always agree with the charts:

  • Best overall: the highest task score, and the cheapest plan that includes it.
  • Best for $25 a month or less: the highest-scoring model on a plan at that price or below.
  • Best free: the highest-scoring model on a free plan.
  • Within 5 points: it's too close to call, so we name both, higher-ranked first, each with its plan and price.
  • Extra cost doesn't count. A model you pay for on top of a plan isn't treated as included.

Here's the result for coding and building apps:

Best overallToo close to call
  • Claude Fable 5.1Get it with Claude Max, $100 a month (for up to half your weekly allowance)
  • GPT-6 AstraGet it with ChatGPT Plus, $20 a month (only in ChatGPT's Work mode and Codex, not normal chat)

1st and 2nd of 10 models for this task

Best for $25 a month or less

GPT-6 Astra

Get it with ChatGPT Plus, $20 a month (only in ChatGPT's Work mode and Codex, not normal chat)

2nd of 10 models for this task

Best free

Kimi K3

Get it with Kimi Free

4th of 10 models for this task

Based on tests of this task. The picks follow a fixed rule using the charts below and each app's plans.

Already paying for one? See what each plan gives you here
App and planPriceBest model on it for thisPosition
ChatGPT FreefreeGPT-5.6 Luna7th of 10
ChatGPT Go$8 a monthGPT-5.6 Luna7th of 10
ChatGPT Plus$20 a monthGPT-6 Astra
Only in ChatGPT's Work mode and Codex, not normal chat
2nd of 10
ChatGPT Pro$100 a monthGPT-6 Astra
Called GPT-6 Pro in the app
2nd of 10
Claude FreefreeClaude Sonnet 56th of 10
Claude Pro$20 a monthClaude Sonnet 5
Its main model, Claude Opus 5.5, is too new to score yet.
6th of 10
Claude Max$100 a monthClaude Fable 5.1
For up to half your weekly allowance
Its main model, Claude Opus 5.5, is too new to score yet.
1st of 10
Gemini FreefreeGemini 3.6 Flash8th of 10
Google AI Plus$4.99 a monthGemini 3.6 Flash8th of 10
Google AI Pro$19.99 a monthGemini 3.8 Flash5th of 10
Google AI Ultra$99.99 a monthGemini 3.8 Flash5th of 10
Kimi FreefreeKimi K34th of 10
Kimi Moderato$19 a monthKimi K34th of 10

Too close to call

Results come with a likely range, drawn as a thin line on each bar. When the top two lines overlap, we say it's too close to call rather than naming a winner.

People's votes on business and finance questions

An example from the site · Higher is better

Claude Opus 5.5 · Anthropic1st
Claude Fable 5.1 · Anthropic2nd
Gemini 3.8 Flash · Google DeepMind3rd
Kimi K3 · Moonshot AI4th

New models

Independent testers take one to three weeks to catch up with a launch, so each model shows where its evidence stands. A new version always starts from nothing; we never assume it performs like the one before.

Independently tested

8 or more, or a place on Epoch AI's combined score.

13 models right now

Early results

Fewer than 8 independent results.

3 models right now

The maker says

No independent results yet, only what the maker says.

0 models right now

Apps and plans

ChatGPT, Claude and Gemini are apps; each runs one or more models, and free plans often run an older one. We compare the models, then map each to the plans that include it.

AppPlans we coverChecked
ChatGPT
OpenAI
Free (Free), Go ($8/month), Plus ($20/month), Pro ($100/month)26 Sept 2026
Claude
Anthropic
Free (Free), Pro ($20/month), Max ($100/month)26 Sept 2026
Gemini
Google
Free (Free), Google AI Plus ($4.99/month), Google AI Pro ($19.99/month), Google AI Ultra ($99.99/month)26 Sept 2026
Kimi
Moonshot AI
Free (Free), Moderato ($19/month)26 Sept 2026
  • We check plans against the makers' own pages at least every 30 days. Where a maker's page can't be read, we use press coverage and say so.
  • An older model that a plan still uses stays on our charts, because it's what people on that plan actually get.
  • Plans change often, so check the price before you buy.

Cost charts show what developers pay to use a model directly, for 1,000 typical requests of about 1,500 words in, 500 out. If you use an app, the monthly plan is what you pay.

Who writes what

Norm, our guide

Anything Norm says about the data, like who leads or what the top models cost, is filled in from the same numbers as the charts, so it can't disagree with them. His advice is written by a person and only appears once it's been reviewed.

What the makers say

Launch claims appear on model pages, always labelled as the maker's own, and never count towards a score.

What it can't tell you

  • How good AI is at your exact job. Tests are close stand-ins, and the label on each chart tells you how close.
  • Whether one answer is right. Every model makes mistakes; Norm's guide on each task says what to check.
  • How a model does inside a specific app feature, like a document upload or a coding tool. We compare the models, not the apps.
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