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LLM ComparisonGPT-5.5Claude 3 Opus

GPT-5.5 vs Claude 3 Opus

Compare GPT-5.5 and Claude 3 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5.5Claude 3 Opus
ProviderOpenAIAnthropic
Model Typetexttext
Context Window1,000,000 tokens200,000 tokens
Input Cost
$5.00/ 1M tokens
$15.00/ 1M tokens
Output Cost
$30.00/ 1M tokens
$75.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5.5

OpenAI

1. Strongest Agentic Coding Model

  • State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
  • Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.

2. Higher Intelligence at GPT-5.4 Latency

  • Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
  • Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.

3. Powerful for Knowledge Work & Computer Use

  • Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
  • Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.

4. Scientific Research Co-Scientist

  • Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
  • Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.

Claude 3 Opus

Anthropic

1. Intelligence & Reasoning

  • Highest capability in the Claude 3 family
  • Near-human comprehension and fluency
  • Excels at MMLU, GPQA, GSM8K, advanced reasoning tasks

2. Complex Problem Solving

  • Best for research, strategy, multi-step planning
  • Handles ambiguous, open-ended tasks with ease

3. Vision & Multimodal Capabilities

  • Strong chart/graph understanding
  • Processes documents, technical diagrams, and dense visual data

4. Recall & Long-Context Reasoning

  • Near-perfect recall (>99% on NIAH benchmark)
  • Handles very large documents and multi-file workflows

5. Enterprise-Grade Accuracy

  • Significantly reduced hallucinations
  • High correctness rate for factual queries