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C ChatGPT Comparison

ChatGPT vs Claude 2026: Benchmarks, Pricing, Real Differences

Update
Update (June 9, 2026)

The current flagships have moved on - Anthropic's is now Claude Fable 5 and OpenAI's is GPT-5.5. This comparison covers the models named in it; for the latest head-to-head see our Fable 5 review and the Fable 5 vs GPT-5.5 vs Gemini comparison.

Quick Verdict
By Dimension

Coding (SWE-Bench Pro): Claude leads - Opus 4.8 69.2% vs GPT-5.5 58.6%.
Computer use (OSWorld): Claude leads - Opus 4.8 83.4% vs GPT-5.5 78.7%, both well above the 72.4% human expert baseline.
Terminal-Bench 2.1: GPT-5.5 leads - 78.2% vs Opus 4.8 74.6%.
Context window: Claude leads - 200K standard vs 128K standard (GPT-5.5's 1M requires $200/mo tier).
API cost: GPT-5.5 leads - $2.50/$15 vs $5/$25 per million tokens.

Every week, someone asks the same question: ChatGPT or Claude? The honest answer is that neither model wins on every dimension. This article doesn't offer a universal verdict. It offers data.

The comparison is GPT-5.5 (standard, 128K context) against Claude Opus 4.8 (200K context, 64K max output) - the two current consumer and API flagships as of May 28, 2026. Benchmark figures come from the Anthropic Opus 4.8 announcement, OSWorld Benchmark, and Artificial Analysis. Pricing figures come from the OpenAI API Pricing page and Anthropic pricing page.

If you haven't read the foundational profiles yet, see What Is ChatGPT and What Is Claude AI in the AI tools hub.


ChatGPT vs Claude: What You're Actually Comparing

These are not the same class of product pitched the same way. Understanding the baseline differences matters before any benchmark means anything.

GPT-5.5 is OpenAI's current API and consumer flagship. The standard tier gives you 128K context tokens and a 128K maximum output per response. The $200/month ChatGPT Pro tier unlocks GPT-5.5 Pro with 1M context - but that context expansion is available only on that tier. Do not assume 1M context is the default.

Claude Opus 4.8 is Anthropic's flagship, released May 28, 2026. It ships with 200K context across all paid tiers and caps single-response output at 64K tokens. For most tasks, 64K output is sufficient. For long generation tasks, GPT-5.5's 128K output ceiling is a real advantage.

Important caveat: You may see "64.7% HLE (Humanity's Last Exam)" cited for Claude. That figure belongs to Claude Mythos Preview - a research preview model that is not generally available Opus 4.8. Do not use that number to make a purchase decision about the production model.

Dimension GPT-5.5 (standard) Claude Opus 4.8
Context window 128K tokens 200K tokens
Max output / response 128K tokens 64K tokens
API input price $2.50/M tokens $5.00/M tokens
API output price $15.00/M tokens $25.00/M tokens
SWE-Bench Pro 58.6% 69.2%
OSWorld (computer use) 78.7% 83.4%
GDPval-AA 1769 1890
Terminal-Bench 2.1 78.2% 74.6%
Image generation Yes (DALL-E) None
Consumer plan (base) $20/mo (Plus) $20/mo (Pro)

Sources: Anthropic Opus 4.8 Announcement, OSWorld Benchmark, Artificial Analysis, OpenAI API Pricing, Anthropic Pricing - accessed 2026-05-28.


Benchmark Showdown: SWE-Bench Pro, OSWorld, GDPval-AA, Terminal-Bench

Four benchmarks that actually differentiate these models. Results from the Anthropic Opus 4.8 announcement, OSWorld Benchmark, and Artificial Analysis, accessed May 28, 2026.

SWE-Bench Pro Harder coding tasks / real GitHub issues Claude leads
Claude Opus 4.8 69.2%
GPT-5.5 58.6%

A 10.6 percentage point gap is operationally meaningful. Claude Opus 4.8 has a clear lead on the harder SWE-Bench Pro coding benchmark. Note: SWE-Bench Pro is a harder variant than SWE-Bench Verified - do not compare these numbers to prior SWE-Bench Verified results. Source: Anthropic Opus 4.8 Announcement

OSWorld Desktop / browser automation Claude leads
Claude Opus 4.8 83.4%
GPT-5.5 78.7%
Human expert baseline 72.4%

Claude Opus 4.8 now leads OSWorld at 83.4%, overtaking GPT-5.5 at 78.7%. Both well above the 72.4% human expert baseline. Source: OSWorld Benchmark

GDPval-AA Agentic performance composite Claude leads
Claude Opus 4.8 1890
GPT-5.5 1769

GDPval-AA measures agentic performance across tasks. Opus 4.8 leads by 121 points. Source: Artificial Analysis

Terminal-Bench 2.1 Terminal-based coding evaluation GPT-5.5 leads
GPT-5.5 78.2%
Claude Opus 4.8 74.6%

GPT-5.5 retains a lead on Terminal-Bench 2.1, the terminal-based coding evaluation. This is the one coding benchmark where GPT clearly outperforms Claude. Source: Artificial Analysis

One number to be careful about: GPT-5.5 scores 73.3% on ARC-AGI-2. The ARC-AGI-2 leader is Gemini 3.1 Pro at 77.1% - do not assign that figure to either model here.


Coding: GPT-5.5 vs Claude Opus 4.8

Claude Opus 4.8 leads SWE-Bench Pro at 69.2% versus GPT-5.5's 58.6% - a meaningful gap on the harder coding benchmark. But practical coding experience adds important texture beyond any single score.

Where Claude wins on coding

  • Claude Code is the purpose-built agentic coding interface built around Opus 4.8. On SWE-Bench Pro, Claude Opus 4.8 scores 69.2% - a clear lead over GPT-5.5 at 58.6%. Opus 4.8 is also 4x less likely to allow unremarked code flaws compared to its predecessor.
  • The 200K context window means Claude can hold more of a large codebase in memory during a session - useful for navigating complex projects without losing context.
  • Claude Artifacts outputs interactive HTML/React components directly, useful for rapid prototyping.

Where GPT-5.5 wins on coding

  • 128K max output means GPT-5.5 can generate more code in a single response without requiring continuation - matters for large file rewrites or scaffold generation.
  • Broader IDE integration through GitHub Copilot (20M+ users) and a larger plugin ecosystem.
  • Terminal-Bench 2.1: GPT-5.5 leads at 78.2% versus Opus 4.8 at 74.6% - the one coding benchmark where GPT has a clear edge.

If your workflow is autonomous coding agents working through full repositories, Claude Code is the purpose-built tool - and Opus 4.8's SWE-Bench Pro lead reinforces that. If your workflow mixes coding, image generation, and document work in a single session, GPT-5.5's broader feature surface may matter more. Test both on your specific codebase before committing.


Context Window and Output Limits

Context window and max output are two different numbers. Conflating them is one of the most common mistakes in model comparisons.

  • Context window = how much text the model can see at once (input + prior conversation)
  • Max output = how many tokens the model can generate in a single response
128K
GPT-5.5 Context
Standard tier (~90K effective)
200K
Claude Opus 4.8 Context
All paid tiers
128K
GPT-5.5 Max Output
Per single response
64K
Claude Opus 4.8 Max Output
Per single response

Claude's 200K context is a genuine advantage for long-document tasks: contract review, book analysis, large codebase sessions. GPT-5.5's 128K output ceiling is a genuine advantage for long generation tasks: extended reports, full-file code rewrites, large structured outputs.

GPT-5.5 Pro's 1M context is real, but it requires the $200/month consumer tier. At the standard $20 Plus tier, GPT-5.5 delivers 128K context - less than Claude Pro's 200K on the same $20 budget.


Computer Use: Operator vs Claude Agent

Both models can control real desktop and browser environments. Claude Opus 4.8 now leads this category, and the operational picture favors Claude on both benchmark score and production predictability.

GPT-5.5 / ChatGPT Operator

  • 78.7% OSWorld - well above the 72.4% human expert baseline
  • Controls browser and desktop applications
  • Currently in beta - not recommended for critical or irreversible processes
  • Available on Pro/Enterprise tier and API; not on the free tier

Claude Opus 4.8 / Claude Computer Use

  • 83.4% OSWorld - now leads GPT-5.5 by 4.7 percentage points, well above the 72.4% human baseline
  • Generally available in the Claude API
  • Community and production reports describe more conservative, predictable behavior - fewer unexpected actions

Neither model's computer use should be deployed for critical or irreversible processes without human review at every step. Both are still in early-access or beta stages for this capability.

With Opus 4.8, Claude now leads both on benchmark score (83.4% vs 78.7%) and community-reported predictability. GPT-5.5 Operator still has broader desktop application coverage, but the benchmark gap now favors Claude.


Pricing: API and Consumer Plans

All prices from the OpenAI API Pricing page and Anthropic pricing page, accessed May 28, 2026. See the full ChatGPT pricing breakdown for tier-by-tier consumer details.

API Pricing (per million tokens)

Model GPT-5.5 Claude Opus 4.8
Input (per 1M tokens) $2.50 $5.00
Output (per 1M tokens) $15.00 $25.00
Input cost ratio 1x (baseline) 2x GPT-5.5
Output cost ratio 1x (baseline) 1.67x GPT-5.5

At 10 million input tokens/month: $25 for GPT-5.5, $50 for Claude Opus 4.8. The gap compounds at volume.

Consumer Plans

Plan Price Key access
ChatGPT Plus $20/mo GPT-5.5 Thinking access
Claude Pro $20/mo Opus 4.8 access, 200K context
ChatGPT Pro $100/mo Higher GPT-5.5 Pro quota
ChatGPT Pro (full) $200/mo 1M context, unlimited Deep Research, Sora video
Claude Max Multiple tiers Check current Anthropic pricing

At the $20/month base tier, both services are identically priced. ChatGPT's differentiation is at the $100–$200/month tiers with features (Sora, unlimited Deep Research, 1M context) that have no direct Claude equivalent.


When to Use ChatGPT, When to Use Claude

Neither model is a universal winner. Here is a decision framework built from the verified data above. For the same analysis from the Claude perspective, see Claude vs ChatGPT.

Which Should I Use?
Do you need desktop or browser automation?
Do you need built-in image or video generation?
Do you frequently work with very long documents (contracts, full codebases, books)?
What's your primary coding workflow?
Is API cost a significant factor for your volume?
Recommendation

ChatGPT (GPT-5.5): Use it when you need

  • Terminal-based coding workflows - GPT-5.5 leads Terminal-Bench 2.1 at 78.2%
  • Image generation (DALL-E is built in; Claude has no image generation)
  • Deep Research - 5–30 minute citation-rich report generation
  • Sora video generation (Pro $200 tier)
  • Responses that frequently exceed 64K tokens in length (GPT-5.5's 128K output ceiling is 2x Claude's)
  • Lower per-token API costs at volume ($2.50/$15 vs $5/$25 per million tokens)
  • 9M paying business users in an existing enterprise install base

Claude (Opus 4.8): Use it when you need

  • Long-document analysis at $20/month - 200K context handles contracts, full books, and large codebases better than 128K standard
  • Agentic coding workflows via Claude Code - 69.2% SWE-Bench Pro (Opus 4.8), clear leader over GPT-5.5
  • Desktop or browser automation - 83.4% OSWorld, now the benchmark leader
  • Extended writing output - novels, long reports requiring consistent voice and style
  • Claude Artifacts for interactive HTML/React output
  • Legal and contract review where long-context accuracy matters more than cost

Frequently Asked Questions

Is ChatGPT better than Claude for coding? +

On SWE-Bench Pro, Claude Opus 4.8 leads at 69.2% versus GPT-5.5 at 58.6% - a meaningful gap. Claude Code is the purpose-built agentic coding interface. GPT-5.5 retains a lead on Terminal-Bench 2.1 (78.2% vs 74.6%) and has broader IDE integrations with a larger 128K output ceiling. Run both on your specific codebase before deciding.

Which has the bigger context window, ChatGPT or Claude? +

Claude Opus 4.8 ships with 200K context on all paid tiers. GPT-5.5 standard has 128K context. GPT-5.5 Pro on the $200/month tier offers 1M context, but that is not available on the standard $20 Plus plan. At equal $20/month spend, Claude wins on context.

Is Claude Opus 4.8 worth the extra API cost? +

Claude Opus 4.8 costs 2x GPT-5.5 on input tokens ($5 vs $2.50 per million) and 1.67x on output ($25 vs $15). That premium is justified if your tasks genuinely benefit from the 200K context window, Claude Code's agentic capabilities, or the SWE-Bench Pro coding lead. For general workloads where both models perform comparably on your specific tasks, GPT-5.5 is more cost-efficient.

Which model is better at computer use? +

Claude Opus 4.8 now leads OSWorld at 83.4%, overtaking GPT-5.5 at 78.7%. Both well above the 72.4% human expert baseline. Claude leads on both benchmark performance and reported production predictability. Both are still beta-stage for critical processes.

What about GPT-5.5 Pro's 1M context window? +

GPT-5.5 Pro's 1M context is available on the $200/month ChatGPT Pro tier. It is not available at the standard $20 Plus tier. At $20/month, Claude Pro's 200K context exceeds ChatGPT Plus's 128K. If 1M context matters to you, budget for the full Pro tier.


Known Limitations

ChatGPT Computer Use (beta)
GPT-5.5 Operator/Computer Use is in beta. Do not deploy it for critical, financial, or irreversible processes without human review at each step. Available on Pro/Enterprise and API - not the free tier.
Claude 64K Output Limit
Claude Opus 4.8 caps single-response output at 64K tokens. Tasks requiring responses longer than approximately 50,000 words in one generation will require continuation. GPT-5.5's 128K output ceiling is 2x larger.
Hallucination Risk (Both Models)
Even with Opus 4.8 at 69.2% SWE-Bench Pro and GPT-5.5 at 78.2% Terminal-Bench, both models still make factual errors. Verify all outputs for legal, medical, financial, or technical documentation where accuracy is critical. Neither model should be treated as a ground-truth source.

Video Resources
ChatGPT vs Claude
Benchmark deep dive
Claude Code vs GPT-5.5
Coding workflow comparison
Context Window Guide
When 128K isn't enough
Sources
Fact-checked against vendor documentation and official sources, May 2026