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ChatGPT vs Claude vs Gemini Comparison

Which AI model should you use, and when?

At-a-Glance Comparison

FeatureChatGPT (5.6 Sol)Claude (Fable 5/Opus 5)Gemini (3.6 Flash/3.1 Pro)
DeveloperOpenAIAnthropicGoogle DeepMind
Free TierGPT-5.6 Terra (limited)Sonnet (limited)Flash (generous)
Paid Price$20/month (Plus)$20/month (Pro)$20/month (Google AI Pro)
Context Window1M tokens1M tokens1M tokens
File UploadYes — docs, images, codeYes — docs, images, codeYes — docs, images, video, audio
Image GenerationYes (ChatGPT Images 2.0)No (text only)Yes (Nano Banana Pro)
Web SearchYes (built-in)Yes (built-in)Yes (Google Search)
Code ExecutionYes (Code Interpreter)Yes (Artifacts / Analysis)Yes (code execution)
API AvailableYesYesYes

Note (13 June 2026): Anthropic has disabled Fable 5 (and Mythos 5) for all users to comply with a US government export-control directive restricting foreign-national access. Opus 4.8 is currently the top accessible Claude model; the table reflects Fable 5's specs for reference. Update (2 July 2026): The US government lifted the export controls on 30 June, and Anthropic restored Fable 5 for users globally from 1 July 2026 (Claude.ai, the Claude Platform, Claude Code and Cowork); Mythos 5 is also being re-enabled. Fable 5 is once again the top-tier Claude model. Update (26 June 2026): OpenAI previewed the GPT-5.6 family (Sol / Terra / Luna) as a government-restricted limited preview to a small set of partners; GPT-5.5 remains OpenAI’s top generally available model, so the table reflects 5.5. Wider GPT-5.6 access is expected in the coming weeks. Update (8 July 2026): The US government lifted the preview restrictions on 8 July 2026, and OpenAI has confirmed GPT-5.6 (Sol / Terra / Luna) is launching publicly this week — from Thursday 9 July 2026 — reaching general availability across the API and ChatGPT over the following weeks. We’ll refresh the table to the Sol / Terra / Luna tiers once they are generally available. Update (10 July 2026): GPT-5.6 (Sol / Terra / Luna) reached general availability on 9 July 2026 across ChatGPT, the API and Codex. Pricing per 1M tokens: Sol (flagship) $5 / $30, Terra (balanced) $2.50 / $15, Luna (fast) $1 / $6. GPT-5.6 Sol is now OpenAI’s top model, and free and Go users default to GPT-5.6 Terra; the header above is updated accordingly. Update (19 July 2026): Anthropic’s promotional free access to Fable 5 for Pro, Max, Team and premium Enterprise seats ended at 11:59pm PT on 19 July 2026, after three extensions. Fable 5 remains available but from 20 July 2026 draws on usage credits at its standard $10 / $50 per million tokens rather than the included weekly allowance; Opus 4.8 and Sonnet 5 remain included on paid subscriptions, and Sonnet 5 is the default model on Free and Pro. Anthropic says it intends to return Fable 5 to subscriptions once it has more compute. Note also that Opus 4.8, Sonnet 5 and Fable 5 all now carry a 1M-token context window at standard pricing — the table is updated accordingly. Correction (21 July 2026): Anthropic confirmed that from 20 July 2026 Fable 5 is not removed from subscriptions outright. It is now a standard inclusion on Max, Team Premium and legacy premium Enterprise seats at up to 50% of weekly usage limits. Only Pro and Team Standard move to usage credits at $10 / $50 per million tokens, and those users receive a one-off $100 credit first. Opus 4.8 and Sonnet 5 remain included across paid plans, with Sonnet 5 the default on Free and Pro. Update (24 July 2026): Anthropic released Claude Opus 5, a near-frontier model that reaches roughly Fable 5–level intelligence at half the price and sets new state-of-the-art results on coding and knowledge-work benchmarks. Standard pricing is $5 / $25 per million tokens (the same as Opus 4.8, and half of Fable 5’s input price), with an optional Fast mode at $10 / $50 running about 2.5× faster. Opus 5 adds a per-request reasoning-effort setting (low / medium / high) so you can dial cost against depth. It succeeds Opus 4.8 as the included mid-tier Claude model on paid plans; the header above now reflects Opus 5. Update (28 July 2026): Google made Gemini 3.6 Flash generally available on 21 July 2026 — a 1M-token workhorse that is faster and cheaper than 3.5 Flash (around $1.50 / $7.50 per million tokens), now the default Flash model; the header above is updated accordingly. Gemini 3.5 Pro remains delayed, so 3.1 Pro is still the top Pro tier. For reference, xAI’s Grok 4.5 (public from 9 July 2026, roughly $2 / $6 per million tokens) also sits in the “Opus-class, faster and cheaper” band alongside these models. Update (30 July 2026): OpenAI cut GPT-5.6 API prices as enterprises push for clearer returns on AI spend. Luna drops about 80% to $0.20 / $1.20 per million tokens (from $1 / $6) and Terra falls roughly 20% to about $2 / $12; Sol’s pricing is unchanged at $5 / $30. OpenAI credited efficiency gains from GPT-5.6 rewriting and optimising its own inference stack.

When to Use Each Model

Choose ChatGPT When...

  • You need an all-in-one tool — text, images, code, web search, and data analysis in a single conversation
  • You want image generation integrated into your workflow (ChatGPT Images 2.0 generates images natively)
  • You're building with the API and need the most mature plugin and function-calling ecosystem
  • You need voice interaction (Advanced Voice mode)
  • Your team is already embedded in the OpenAI ecosystem (Microsoft 365 Copilot)

Choose Claude When...

  • You're working with long documents — Claude's 1M-token context window handles entire reports, contracts, and codebases
  • You need nuanced, careful writing that follows detailed instructions precisely
  • You value safety and thoughtful refusals over eager compliance
  • You're doing complex analysis that requires careful reasoning and step-by-step thinking
  • You want clean, well-structured outputs with consistent formatting
  • You need computer use or agentic coding capabilities

Choose Gemini When...

  • You're working with very large files — Gemini's 1M token window is unmatched
  • You need to analyse video or audio content natively
  • You're deep in the Google ecosystem (Docs, Sheets, Gmail, Drive)
  • You want the most generous free tier for experimentation
  • You need real-time information with tight Google Search integration

Task-by-Task Recommendations

TaskBest ModelWhy
Long document analysis (50+ pages)Claude / GeminiLargest context windows; Claude excels at precise extraction
Creative writing & copywritingClaudeMost nuanced prose; best at following style and tone instructions
Code generation & debuggingChatGPT / ClaudeBoth excellent; ChatGPT has Code Interpreter; Claude has Artifacts
Data analysis & visualisationChatGPTCode Interpreter executes Python and generates charts in-conversation
Image generationChatGPTNative ChatGPT Images 2.0 generation; iterative editing in conversation
Email drafting & commsClaudeBest at matching professional tone and following specific formatting requests
Research with citationsGeminiTight Google Search integration provides source links inline
Video/audio analysisGeminiOnly model with native multimodal video and audio understanding
Legal/compliance reviewClaudeStrongest at careful, nuanced analysis with appropriate caveats
Brainstorming & ideationAny — try all threeEach model has different creative tendencies; compare outputs for the richest ideas
The real answer: The best model depends on your task, not brand loyalty. Power users keep accounts with at least two services and route tasks to the model best suited for each job. Think of them as specialists, not competitors.

Quick Decision Framework

  1. What's the task? Match it to the table above.
  2. How much context? Short task → any model. Long document → Claude or Gemini.
  3. Need images or multimedia? ChatGPT for image generation. Gemini for video/audio analysis.
  4. What ecosystem are you in? Microsoft → ChatGPT/Copilot. Google → Gemini. Platform-agnostic → Claude.
  5. Still unsure? Run the same prompt through two models and compare outputs. The quality difference on your specific task is what matters.

Deep-dive into Claude vs ChatGPT

Read our detailed analysis comparing these models across real-world tasks with side-by-side output examples.

Read the Full Comparison