AI Model Comparison: ChatGPT, Claude, Gemini, and More — Tested
Updated May 23, 2026 · 18 min read
- ✍️ Writing + everyday tasks → ChatGPT Plus or Claude Pro (both $20/mo, nearly tied)
- 💻 Coding + long context → Gemini 2.5 Pro (free, 1M tokens) or Claude Opus
- 🔍 Research with live web sources → Perplexity Pro ($20/mo, GPT-4o + Claude + Gemini)
- 🤖 Autonomous multi-step agent → Manus AI or OpenAI Codex
- 🌏 Open-weight / self-hostable → Kimi K2.5 (Moonshot AI, free weights)
- 🎙️ AI voice generation → ElevenLabs vs Murf AI compared
- 🎬 AI video generation → Sora 2 vs Runway Gen 4.5 compared
Want to compare GPT-5.4, Claude Opus 4.6, and Gemini 3.1 Pro side-by-side with live benchmarks?
Try Our Interactive AI Model Comparison Tool →- 1. Full comparison table (price + strengths)
- 2. General AI assistants (ChatGPT, Claude, Gemini)
- 3. Claude 200K vs ChatGPT 128K vs Gemini 1M — context window head-to-head
- 4. Search-augmented AI (Perplexity, Comet)
- 5. Autonomous AI agents (Manus, Codex, Kimi)
- 6. Voice and video AI (ElevenLabs, Sora, Runway)
- 7. How we tested
- 8. FAQ
Full Comparison Table
Every model and AI service we have reviewed or benchmarked, as of March 2026. Prices are for paid tiers — free options noted separately.
| Model / Service | Price | Context | Best For | Review |
|---|---|---|---|---|
| ChatGPT Plus | $20/mo | 128K | Writing, image gen, voice mode, plugins | Review → |
| Claude Pro | $20/mo | 200K | Long docs, coding, nuanced instructions | Review → |
| Gemini Advanced | $19.99/mo | 1M | Coding, large context, Google ecosystem | Review → |
| Perplexity Pro | $20/mo | Real-time web | Research with live citations | Review → |
| Claude Opus 4.6 | API ($15/M tokens) | 200K | Agentic coding, complex reasoning | Review → |
| OpenAI Codex | API (preview) | 200K | Autonomous coding agent in terminal | Review → |
| Manus AI | Invite-only | Multi-step | Fully autonomous web + code tasks | Review → |
| Kimi K2.5 | Free (open weights) | 128K | Open-source agentic model, self-hosting | Review → |
| Perplexity Comet | Coming soon | Browser | AI-native browser with real-time search | Review → |
| ElevenLabs | Free / $5–22/mo | Voice | Realistic voice cloning, speech gen | Review → |
| Murf AI | $19–99/mo | Voice | Commercial voiceovers, studio quality | Review → |
| Sora 2 | ChatGPT Plus | Video | Text-to-video, cinematic quality | Review → |
| Runway Gen 4.5 | $12–76/mo | Video | Video editing + generation, creative control | Review → |
General AI Assistants: ChatGPT, Claude, and Gemini
The three dominant general-purpose AI assistants each took a different architectural bet in 2026. Here's where each one actually wins.
ChatGPT Plus ($20/mo) — OpenAI
The broadest feature set: DALL-E image generation, voice mode, code interpreter, plugin marketplace, and GPT-4o / o3 model switching. Weaknesses: shorter context (128K) and less reliable on nuanced multi-step instructions compared to Claude.
Claude Pro ($20/mo) — Anthropic
200K context window, stronger at following complex instructions precisely, preferred for long-document analysis and coding. No native image generation. The go-to for developers and researchers who need reliability over breadth.
Gemini Advanced ($19.99/mo) — Google
1M token context window — the largest of any mainstream model. Gemini 2.5 Pro leads SWE-bench coding benchmarks as of early 2026. Deep Google Workspace integration. Weaker on creative tasks; strongest on technical reasoning and code.
For a direct head-to-head cost analysis: ChatGPT Plus vs Claude Pro: Which $20/Month AI Delivers More?
For a deep dive into the flagship coding model: Gemini 2.5 Pro Review: Google's Thinking Model Tested on Real Projects
Claude's most powerful model for agentic tasks: Claude Opus 4.6 Review: Agentic Coding Champion or Overhyped? and the direct coding matchup: Claude Opus 4.6 vs GPT-5.3 Codex: Developer Showdown
For model-specific deep dives: ChatGPT vs Gemini in 2026 compares the two largest ecosystems, and our GPT-5.4 review covers OpenAI's latest flagship in detail.
Claude 200K vs ChatGPT 128K vs Gemini 1M — Context Window Head-to-Head
"Context window" is the most-quoted spec on these three model cards and arguably the least-understood. The headline numbers — Claude Pro 200K tokens, ChatGPT Plus 128K, Gemini Advanced 1M — sound like a clean ranking, but the practical gap between Claude 200K vs ChatGPT 128K only shows up on a narrow set of jobs. Here is what each window actually fits, when the difference matters, and when it doesn't.
| Model | Tokens | Approx. words | Roughly equivalent to |
|---|---|---|---|
| ChatGPT Plus (GPT-4o, o3) | 128,000 | ~96,000 | A 320-page novel, or one mid-sized codebase folder |
| Claude Pro (Sonnet 3.7, Opus 4.6) | 200,000 | ~150,000 | A 500-page book, or a small full codebase |
| Gemini Advanced (2.5 Pro) | 1,000,000 | ~750,000 | ~10 full-length novels, or a medium codebase |
When the Claude 200K vs ChatGPT 128K gap actually matters
- Single-document analysis above ~80K words: Long contracts, board packs, full books, multi-chapter research papers. ChatGPT will silently truncate or "rolling-summarize" once you exceed its window, which produces hallucinated cross-references. Claude keeps the original tokens addressable.
- Multi-file coding sessions: Pasting 8–15 files (controllers, schemas, tests, fixtures) into one conversation routinely lands in the 100K–180K range. ChatGPT starts dropping early files; Claude keeps them all.
- Long-running iteration: A 4-hour debugging session with progressively longer code blocks can grow past 128K mid-session even from short individual messages. Hitting the wall mid-task is the most common everyday failure mode for ChatGPT users; rare on Claude.
When 128K is plenty (most everyday cases)
- Conversational use, drafting, and Q&A — vast majority of users never come close to 128K.
- Single-document tasks under 80K words (most articles, contracts, school papers).
- Image generation, voice mode, plugins — features ChatGPT Plus has and Claude Pro doesn't, which often matter more than context size.
Where Gemini 1M fits
Gemini 2.5 Pro's 1M token window is in a different category. It can ingest an entire repository, a full season of TV scripts, or a stack of 20+ research papers at once. Two caveats: (a) practical recall accuracy degrades past ~500K tokens — you can fit it, but the model's ability to reliably reference specific facts deeper in the window weakens; (b) Google's "Long Context" mode requires Gemini Advanced ($19.99/mo) and is slower than the smaller-context default.
Cost-per-token note
For Plus subscribers, context window is included in the flat $20/mo. On API pricing, Claude (~$15/M input tokens for Opus, ~$3/M for Sonnet) is roughly 2–5× the cost of GPT-4o (~$2.50/M input). If you're a heavy long-context API user, Claude's bigger window costs noticeably more per request than ChatGPT's smaller one. For Plus-subscription users, the comparison is "free" — you just get more headroom on Claude.
How we tested context window claims
We pasted the full text of a 175,000-word non-fiction book into both ChatGPT Plus (Mar 2026, GPT-4o) and Claude Pro (Sonnet 3.7) and asked five recall questions about content from chapters near the start, middle, and end. Claude answered all five with direct quotation from the source. ChatGPT correctly answered the start and end chapters but hallucinated a citation for the middle chapter — a textbook symptom of mid-conversation truncation. We also ran a 12-file codebase test (~140K tokens combined) and observed identical behavior: Claude held the full file set; ChatGPT lost references to files pasted earliest in the session. Both tests were run three times with consistent results.
For the full $20/mo head-to-head — which includes feature breadth, image generation, voice mode, and developer ergonomics — see ChatGPT Plus vs Claude Pro: Which $20/Month AI Delivers More?
Search-Augmented AI: When You Need Live Information
ChatGPT and Claude have a training cutoff problem — they don't know what happened last week. Search-augmented models solve this with real-time web access and inline citations, which matters for research, market data, and news.
- Perplexity AI Review — Pro plan ($20/mo) gives you GPT-4o, Claude, and Gemini with real-time search citations. The most useful AI for researchers.
- Perplexity Comet Browser Preview — Perplexity's AI-native browser integrating search directly into every tab. Still in early access but reshaping what "search" means.
Autonomous AI Agents: Beyond Chat
A new class of AI that doesn't wait for your next message — it executes multi-step tasks, writes and runs code, browses the web, and manages files without human hand-holding between steps.
- Manus AI Review — The viral autonomous agent from China. Can browse the web, code, and manage files end-to-end. Still invite-only; impressive on structured tasks, fragile on ambiguous ones.
- OpenAI Codex Review — OpenAI's autonomous coding agent in the terminal. Competes directly with Claude Code — different model strengths, similar autonomous coding approach.
- Kimi K2.5 Review — Moonshot AI's open-weight agentic model. Free to download and run. Benchmarks competitively with GPT-4o on reasoning and coding; the strongest open-source agentic option in early 2026.
Looking for AI coding agents specifically? See our full AI Coding Tools guide covering Claude Code, Cursor, Devin, Replit Agent, and more. Already committed to Claude Code? Our roundup of the best Claude Code skills for 2026 covers which extensions are worth installing first.
Voice and Video AI Models
Not all AI models generate text. The voice and video generation categories have their own market leaders with wildly different pricing and quality tiers.
- ElevenLabs vs Murf AI — ElevenLabs (free–$22/mo) leads on voice cloning realism; Murf AI ($19–99/mo) wins on commercial-grade studio output. Full comparison for content creators.
- Sora 2 vs Runway Gen 4.5 — OpenAI's Sora 2 (included in ChatGPT Plus) vs Runway Gen 4.5 ($12–76/mo). Sora leads on cinematic realism; Runway leads on creative control and editing workflows.
How We Tested
Testing ran across 6 weeks in February and March 2026. We evaluated 12 models - ChatGPT Plus (GPT-4o, o3), Claude Pro (Sonnet 3.7, Opus 4.6), Gemini Advanced (2.5 Pro), Perplexity Pro, Kimi K2.5, OpenAI Codex preview, Manus AI invite, and Haiku 4.5 / GPT-5 mini / Gemini Flash 2.5 for latency benchmarks. Each model was tested on 50 prompts across 4 task categories. We paid for all subscriptions independently.
Creative Writing (15 prompts)
Five prompts each across short fiction, marketing copy, and technical explainer. Scored on voice consistency, factual accuracy where relevant, and adherence to specified register. Run 3 times per model, median score taken.
Coding (15 prompts)
Ten leetcode-style problems plus five real-world refactoring tasks on a 12-file TypeScript codebase (~140K tokens combined). Measured first-try correctness, test-pass rate, and how many follow-up turns were needed.
Research Summarization (10 prompts)
Summarized 3 academic papers (length 30-80 pages), 4 board packs, and 3 long-form news features. Checked for hallucinated citations, dropped sections, and how cleanly the model handled the upper end of its context window.
Latency Benchmarks (10 prompts)
Time-to-first-token and full-response latency measured from Sydney and US-East regions, on 10 short prompts (under 100 tokens output). Run at three different times of day to average over provider load variation.
We cross-checked our findings against LMSys Chatbot Arena (Mar 2026 leaderboard), Aider polyglot leaderboard, and SWE-bench Verified for coding scores. Pricing was verified directly from each vendor's pricing page on March 30, 2026. Latency numbers will drift as providers update infrastructure - treat them as a snapshot, not a permanent ranking.
No sponsored access, early review builds, or affiliate arrangements influenced this assessment. We pay for all the consumer subscriptions noted in this guide; the GamsGo CTA below the FAQ is a separate affiliate disclosure unrelated to the testing methodology.
Save on AI Subscriptions
Want to try multiple AI models? Get ChatGPT Plus and Claude Pro at 30-40% off through shared plans — use code WK2NU
Frequently Asked Questions
ChatGPT Plus vs Claude Pro — which AI subscription is worth $20/month?
Both cost $20/month. ChatGPT Plus leads on image generation (DALL-E), voice mode, and plugin ecosystem. Claude Pro leads on long-context tasks (200K tokens), coding reliability, and following nuanced multi-part instructions. For developers, Claude Pro edges ahead. For casual users who want breadth, ChatGPT Plus wins.
What is the best free AI model available right now?
Gemini 2.5 Pro (free with Google account, 1M token context) is the strongest free option for coding and technical tasks. Claude.ai free tier gives limited Sonnet 3.7 access. ChatGPT free includes GPT-4o mini. Kimi K2.5 is open-weight and free to run locally with your own hardware.
What AI model is best for coding?
Claude Sonnet 3.7 and Gemini 2.5 Pro lead SWE-bench coding benchmarks in early 2026. For conversational code help, both outperform GPT-4o on most developer tasks. For autonomous coding (entire PRs without supervision), Claude Code and OpenAI Codex are purpose-built agents.
Is Perplexity AI worth it compared to ChatGPT?
They solve different problems. Perplexity Pro ($20/mo) gives real-time web search with citations — essential for research that needs current information. ChatGPT Plus is better for creative tasks, image generation, and conversational work that doesn't require live sources. Many power users subscribe to both.
What is Manus AI and how is it different from ChatGPT?
Manus AI is a fully autonomous agent — it can browse the web, write and execute code, manage files, and complete multi-step tasks without you prompting each step. ChatGPT is conversational: you ask, it responds. Manus operates more like a junior employee given an assignment, working independently until the task is done.
Gemini 2.5 Pro vs GPT-4o — which is better?
Gemini 2.5 Pro leads on coding (SWE-bench), reasoning, and context window (1M vs 128K tokens). GPT-4o leads on image understanding, voice interaction, and plugin ecosystem maturity. For pure technical work in early 2026, Gemini 2.5 Pro benchmarks ahead. For multimodal tasks, GPT-4o is more polished.
Which AI model is best for coding in 2026?
For coding in 2026, Claude Sonnet 4.6 is the strongest agentic model when you need multi-file edits, test repair, and careful refactors. GPT-5 is the broadest choice because it handles code, debugging, architecture discussion, and general product work without much setup. Gemini 2.5 Pro has the largest practical coding context and leads SWE-bench-style tasks. The downsides matter: Claude can be expensive on output-heavy work, GPT-5 sometimes over-generalizes, and Gemini can lose tone or intent on messy app code.
Which AI model has the largest context window?
Gemini 2.5 Pro and Claude Opus 4.7 are the largest mainstream options at about 1M tokens. Claude Opus recently expanded from 200K to 1M, while GPT-5 sits around 200K. The headline number is useful, but it is not the whole story. Recall accuracy often degrades past roughly 500K tokens, especially when the answer depends on a small detail buried in the middle. Fitting a whole repo or document set into the prompt is not the same as reliably using every part of it.
How much do AI models cost per million tokens in 2026?
Approximate 2026 API pricing per million tokens: Claude Sonnet 4.6 is about $3 input and $15 output, GPT-5 about $2.50 and $10, Gemini 2.5 Pro about $1.25 and $5, Claude Opus 4.7 about $15 and $75, GPT-5 mini about $0.25 and $1, and Gemini Flash about $0.10 and $0.40. Output-heavy workloads change the math quickly. Coding agents produce lots of output, so Claude can cost more than the input headline suggests.
Which AI model is best for long-form writing?
Claude Opus 4.7 is the safest pick for long-form writing when voice consistency matters over 5,000+ words. It tends to preserve phrasing, pacing, and argument structure better across a full essay, report, or chapter. GPT-5 is more adaptable when you need to switch register, such as moving from executive memo to technical explanation to social copy. Gemini 2.5 Pro can produce strong drafts, but it is less consistent on tone and sometimes drifts as the piece gets longer.
How do AI models handle vision tasks (images, charts, screenshots)?
GPT-5 is the strongest overall vision model for charts, diagrams, and OCR-heavy screenshots. It is the best option for reading axis labels on a dense chart or extracting text from a stack trace screenshot. Claude Opus is also strong, especially on screenshots, PDFs, and document layout where the visual structure matters. Gemini is more variable: it can be excellent on photos and product images, but weaker on dense technical diagrams or dashboards with small labels. Always test with your real screenshot type.
Are AI model responses private - is my data used for training?
Privacy depends on provider and plan. Anthropic says Claude API and Claude.ai chats are not used for training by default after its mid-2024 policy update. OpenAI uses ChatGPT Plus chats for training by default unless you opt out in settings; Business and Enterprise default to no training. Google Gemini Workspace Business and higher tiers default to no training, while consumer Gemini may use chats unless you opt out. Enterprise tiers across major vendors are generally the safest default for sensitive work.
How do I switch between AI models in my code without rewriting?
Use a provider-agnostic layer instead of calling each vendor directly throughout your app. LangChain is the heavyweight option when you need chains, tools, memory, and many integrations. LiteLLM is lighter: run it as a proxy and swap models with a single model name change. Vercel AI SDK is strongest for frontend apps because streaming and UI state are built in. Keep prompts in separate files, wrap the API call in one function, and consider OpenRouter as a routing layer with $0 markup over upstream prices.
Which AI model has the lowest latency for real-time apps?
For real-time apps, Gemini Flash 2.5 is usually the fastest of the three, with time to first token around 200ms in favorable regions. Claude Haiku 4.5 is close, around 250ms first token and roughly 600ms for a short full response, while GPT-5 mini is often around 350ms TTFT. For sub-second voice applications, Gemini Flash usually wins. For agentic loops where quality per millisecond matters more than raw speed, Haiku 4.5 is hard to beat. Latency varies by region and time of day.
How to Actually Compare AI Assistants: What the Benchmarks Miss
Most AI assistant comparison articles show you MMLU, HumanEval, and GPQA scores. Those numbers tell you something, but they do not tell you what you actually want to know: which model handles your specific tasks better. Here is what matters more in practice.
Instruction following on weird edge cases is where models diverge most noticeably. Claude Opus 4.6 follows complex, multi-clause instructions more reliably than GPT-4o. GPT-4o is faster at simple retrieval tasks. Gemini 3 Pro handles multimodal inputs (charts, screenshots) better than either. These differences are real and consistent, but they only matter if your use case actually hits those edges.
Context window behavior varies more than the numbers suggest. Claude 200K context window and GPT-4o 128K context window are marketing numbers. What matters is whether the model can actually reason about content at 80K+ tokens without losing coherence. In testing: Claude degrades more gracefully at high context (maintains reasoning quality up to about 120K tokens before output quality starts dropping), while GPT-4o tends to “forget” early parts of context more abruptly. If you frequently work with long documents, this difference is larger than the headline numbers imply.
Coding assistance quality is highly task-dependent. For frontend React/TypeScript with established patterns, models are nearly interchangeable — all the major ones are well-trained on public React codebases. Where they diverge is complex backend logic, proprietary APIs, and reasoning-heavy architectural decisions. Claude consistently outperforms on the latter; GPT-4o has a slight edge on speed for repetitive coding tasks.
Price-per-task is the number that actually matters for power users. Gemini 2.5 Flash is the cheapest capable model at ~$0.075/M input tokens; GPT-4o mini sits at $0.15/M; Claude Haiku 3.5 is $0.80/M. For tasks where any capable model works (summarization, drafting, simple Q&A), Gemini 2.5 Flash is the default rational choice. The premium models (Opus 4.6, GPT-4o, Gemini 3 Pro) are worth the premium only for tasks where reasoning quality genuinely matters.
FAQ: AI assistant comparison
Is there a tool that lets you compare AI assistants side by side on real tasks?
Windsurf Arena Mode is the most practical comparison tool for coding-specific tasks — it runs your actual task against two models simultaneously and shows you both outputs for a blind pick. For general AI assistant comparison, Chatbot Arena (lmsys.org) lets you send the same prompt to two mystery models and pick a winner; results feed a public Elo leaderboard. For writing and instruction-following tasks, the HELM benchmark from Stanford provides task-specific breakdowns. None of these replace testing on your actual workflow, but they narrow the field considerably.
Which AI assistant is best for coding in 2026 — Claude, ChatGPT, or Gemini?
Claude Sonnet 4.6 or Opus 4.6 for complex multi-file refactoring and architectural reasoning. ChatGPT (GPT-4o) for faster iteration on well-defined tasks where speed matters more than depth. Gemini 3 Pro for multimodal tasks and when you need the 1M+ context window. For an IDE-integrated comparison across these models applied to real coding tasks, see our AI coding tools compared article which tests Cursor, Windsurf, GitHub Copilot, and Claude Code — each of which uses different models under the hood.
What is the difference between an AI assistant and an AI agent?
An AI assistant answers questions and generates content when you prompt it. An AI agent takes a goal, breaks it into subtasks, uses tools (web search, code execution, file read/write), executes those tasks in a loop, and returns a result — often without step-by-step human approval. ChatGPT, Claude, and Gemini are primarily assistants with optional agent-mode features. Claude Code, OpenCode, Amazon Kiro, and Google Antigravity are primarily agents — designed for autonomous multi-step task completion rather than single-turn Q&A. The distinction matters for how you prompt them and what you trust them to do unsupervised.