How to Pick the Right AI Model

A practical decision guide. Three steps, no fluff. Match the model to your task, budget, and codebase size.

01

What are you building?

Match the model to the workload

Coding task

Prioritize intelligence

Opus, GPT-5.4, Gemini Pro

See intelligence rankings→

Quick chat / iteration

Prioritize speed

Gemini Flash, Haiku, GPT-4o Mini

See speed rankings→

High volume / batch

Prioritize cost

Llama, Qwen, Mistral

Calculate costs→

Real-time app

Prioritize latency

GLM-5, Kimi, Gemini Flash

See latency rankings→
02

What's your budget?

Every price point has a strong option

Free

No cost, solid performance

Gemini CLI, Llama via Ollama, Qwen via Ollama

$20/mo

Pro-tier access

Claude Code (Pro), Cursor Pro, ChatGPT Plus

$200/mo

Unlimited frontier models

Claude Code Max (unlimited Opus)

API / pay-per-token

Scale to any volume

All providers - price varies by model

Compare token costs→
03

Context window matters

How much code can the model see at once

Small project

Under 10 files

Any model works - context is not the bottleneck

Medium codebase

10-100 files, typical apps

128K+ tokens (most modern models)

Large monorepo

Hundreds of files, deep context

200K+ (Claude) or 1M (Gemini)

Next Steps

Browse the Leaderboard

See all 208+ models ranked by intelligence, speed, cost, and latency

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Get a Recommendation

Describe your task and get a personalized model match with dispatch configs

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Calculate Costs

Estimate your monthly spend based on token volume and model choice

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