ChatGPT vs Claude vs Gemini: Which AI Fits Which Job

Which AI model is best? The honest answer is "it depends", but the way it depends is more interesting than most comparison articles let on.

A note on versions and sources first. The specific figures below (context windows, prices, free-tier limits) describe the GPT-4o, Claude 3.5 Sonnet and Gemini 2.0 generation. All three companies have shipped newer models since, with bigger context windows and different prices, so check each provider's pricing page for current numbers. The task-by-task strengths come from published benchmarks and widely reported user experience, not from our own lab testing, and they've stayed broadly similar from one model generation to the next.

The useful questions aren't about toy prompts like "write me a poem about fall". They're which model handles a real codebase review, which one writes a blog post that doesn't sound like a press release, and which one can deal with Hindi the way we mix it with English in daily conversation. If you're new to AI tools, our getting started with AI guide covers the basics before you start picking sides.

The three contenders (at the generation compared here)

Feature	GPT-4o	Claude 3.5 Sonnet	Gemini 2.0 Pro
Company	OpenAI	Anthropic	Google
Context Window	128K tokens	200K tokens	2M tokens
Max Output	~16K tokens	~8K tokens	~8K tokens
Multimodal	Text, image, audio, video	Text, image	Text, image, audio, video
Free Tier	Yes (limited GPT-4o)	Yes (limited)	Yes (generous)
Paid Price	$20/month (Plus)	$20/month (Pro)	$20/month (Advanced)
API Input Cost	$2.50/M tokens	$3.00/M tokens	$1.25/M tokens
API Output Cost	$10.00/M tokens	$15.00/M tokens	$5.00/M tokens

Gemini 2.0 Pro's 2 million token context window is huge. Feed it an entire codebase and it won't blink. Of the other two, Claude had the bigger window at 200K, and it was widely reported to handle long contexts reliably, while API pricing leans so heavily toward Gemini that it matters a lot if you're building apps on top of these. If you want to know how context windows and tokenization work under the hood, our deep-dive on how large language models work breaks it down.

Coding

All three handle everyday coding well: bug fixing, feature implementation and code review. The differences are in style.

Claude has built a reputation, in coding benchmarks like SWE-bench and among developers, for clean, idiomatic code and explanations that teach you why a fix works, for example why a stale closure behaves the way it does in React's render cycle. In code review it tends to be thorough, flagging security issues like SQL injection alongside performance and structure problems.

ChatGPT is very close behind and sometimes the more creative of the two, leaning towards giving you working fix code over explaining principles. Gemini is competent, and its huge context window helps when you need it to read a lot of code at once, but on complex code it has generally been rated a step behind.

So for coding, Claude is the usual first pick, with ChatGPT a close second.

Writing: they all write differently

Ask all three for the same long technical article and the drafts come back with very different personalities.

ChatGPT's tend to be solid and well organized, technically accurate with good transitions, and a little textbook-like. Correct, but sometimes flat.

Claude is widely regarded as the most natural long-form writer: conversational without getting sloppy, willing to state opinions and acknowledge counterarguments, and good at grounding concepts in examples.

Gemini's drafts often come in shorter than requested and lean heavily on facts, so they can read like documentation.

Professional emails flip the order. For replying to difficult clients, writing project updates or drafting a salary negotiation, GPT-4o hits the right tone most consistently, diplomatic where it needs to be and well structured. Claude's run long. Gemini's are terse.

For creative writing, Claude's prose is generally the most evocative, ChatGPT's is competent, and Gemini's tends to lack a distinct voice.

On writing, then, it's Claude for long-form and creative work and ChatGPT for professional communication, with Gemini the weakest writer of the three (though it improves with each generation).

Analysis and reasoning: Gemini's territory

For data analysis, such as pulling seasonal patterns and anomalies out of a spreadsheet of sales data, Gemini has a strong reputation, helped by Google's data tooling and its ability to take in large files. ChatGPT reliably finds the major trends, and Claude tends to ask clarifying questions about context before making recommendations, which is often the sensible move.

On multi-step logical reasoning, all three handle basic and intermediate problems well. At the hardest levels results vary by benchmark and model version, so check current leaderboards rather than trusting any single comparison.

For summarizing long documents, Gemini's big context window is a real advantage. Claude's summaries are often the most readable, though any model can paraphrase in ways that subtly shift the original meaning, so check anything important against the source.

Gemini wins data and summarization, Claude wins reasoning and strategy, and GPT-4o is solid across the board without leading any one sub-category.

Math

On standard undergraduate math (derivatives, matrices, hypothesis testing), all three are consistently right. Competition problems split them.

On competition math (AMC and AIME-style problems), scores move a lot between model generations, and dedicated reasoning models now do far better than the general chat models this article started with. Check published benchmark results for the current versions.

For everyday math, any of the three will do.

Indian languages: Gemini runs away with it

This one matters a lot for Indian users.

Most of us switch between English and a regional language all day, and Hinglish ("mujhe ek Python script chahiye jo CSV file read kare") is how a lot of Indians actually type. Gemini has generally been the strongest here, which isn't surprising given how much Google has invested in Indian language data.

ChatGPT handles Hindi well, though its output can be overly formal and Sanskritized, the kind nobody uses in conversation. Claude understands Hindi input but has historically been the weakest of the three at replying in it, sometimes answering in English unless asked not to.

For Tamil, Telugu and other regional languages the same broad pattern has held, with Gemini usually ahead. Multilingual work? Start with Gemini, and try your own language before committing.

Privacy

Most comparisons skip this, but it matters if you use these for work.

With OpenAI (GPT-4o), free-tier conversations may be used to train future models, though you can opt out in Settings > Data Controls. The API isn't used for training. Conversations are stored for 30 days for abuse monitoring.

Anthropic (Claude) works much the same way: the free tier may be used for training, there's an opt-out, and the API isn't used. Anthropic's usage policies are clearer.

Google (Gemini) is more complicated because of Google's advertising business. Human raters review free-tier conversations, and those conversations may train models, while the paid Google One AI Premium plan says it won't use your data for training. Workspace has its own policies.

For anything sensitive, like proprietary code, confidential data or legal documents, use API access with data retention disabled, whichever model you pick. Don't put sensitive material into any free consumer tier. Data policies change, so check each provider's current terms.

Free tiers

These were the free-tier details for the generation compared here; limits and included models change often.

Feature	ChatGPT Free	Claude Free	Gemini Free
Model Access	GPT-4o (limited), GPT-3.5	Claude 3.5 Sonnet (limited)	Gemini 2.0 Flash, Pro (limited)
Daily Limits	~15 GPT-4o messages	~20 messages	Generous (varies)
File Upload	Yes (images)	Yes (images, docs)	Yes (images, docs, audio, video)
Code Execution	Yes (Code Interpreter)	No	Yes (Colab integration)
Web Search	Yes	No (usually)	Yes (grounded in Google Search)
Context Window	128K	200K	1M+

Gemini's free tier is the most generous by a decent margin. (The 1M+ in that table is 2.0 Flash's 1 million token window. The 2 million figure up top is 2.0 Pro's.) ChatGPT's includes Code Interpreter, which is useful, and Claude's free tier gives you the full Sonnet model, but with the tightest daily message limit of the three.

API pricing for builders

Costs add up fast here. These were list prices per million tokens for these specific model versions; newer models are priced differently, so use this to understand the relative tiers, not as current pricing.

Model	Input Cost/M	Output Cost/M	Speed
GPT-4o	$2.50	$10.00	Fast
GPT-4o mini	$0.15	$0.60	Very Fast
Claude 3.5 Sonnet	$3.00	$15.00	Fast
Claude 3.5 Haiku	$0.25	$1.25	Very Fast
Gemini 2.0 Flash	$0.10	$0.40	Very Fast
Gemini 2.0 Pro	$1.25	$5.00	Fast

Gemini 2.0 Flash at $0.10 input and $0.40 output is absurdly cheap. For high-volume apps that don't need top-tier quality, it's the obvious pick. Claude Sonnet costs the most but gives the best output for coding and writing. A sensible approach is to send routine stuff to a cheap model (GPT-4o mini, Haiku or Flash) and route complex queries to the expensive ones, a hybrid setup that can cut costs by 70-80% and keep quality where it counts.

At a glance

Task	Usually strongest
Coding and code review	Claude
Long-form and creative writing	Claude
Professional emails	ChatGPT
Data analysis	Gemini
Summarizing very long documents	Gemini
Hindi and Indian languages	Gemini
General conversation	ChatGPT

This reflects the broad pattern across benchmarks and user reports, not a scored test of our own.

Who should use what

If you're an Indian developer, make Claude your main coding companion. For code reviews, bug fixes, architecture advice and the quality of its explanations, it has consistently been rated highly. Keep ChatGPT around for Code Interpreter and web browsing, and switch to Gemini when you're working in an Indian language.

Students should start with Gemini's free tier, since the limits are the most generous, it's good for research, it plugs into the Google services you already use, and it's the strongest for Indian languages. Our AI tools for students in India post goes into specific workflows for academics.

Businesses building AI products can run high-volume, cost-sensitive tasks on a cheap, fast model (Gemini Flash is a common pick) and route complex queries to a top Claude or GPT model, depending on the task.

Casual users? ChatGPT, still. It has the most polished conversational experience and the largest plugin ecosystem.

Where this goes from here

Be wary of anyone who claims to have found the single "best" AI model, because the picture shifts every few months, with OpenAI, Anthropic and Google each shipping new versions. Each family still has a personality.

ChatGPT is the all-rounder: good at everything. Claude is the careful specialist, strongest at coding and writing. Gemini is the one for data and efficiency, best at analysis, Indian languages and anything cost-sensitive.

So use all three. Match each one to the task and you'll get much better results than you would by going all-in on one brand out of loyalty, and since six months from now the strengths may have moved again, keep testing and judge by the output.