Key takeaways
- Claude Opus offers a 200,000-token context window versus GPT 5.5’s 128,000 tokens, making it better for analyzing full-length documents without chunking.
- GPT 5.5 costs $10 per million input tokens versus Claude Opus’s $15, and performs better on code debugging and structured data extraction.
- Claude Opus hallucinates sources 3% of the time versus GPT 5.5’s 9%, critical for citation-heavy academic or legal work.
- At 1 million tokens per month, GPT 5.5 costs $40 total versus Claude Opus’s $90, a significant difference for high-volume workflows.
In this guide
Claude Opus and GPT 5.5 launched within weeks of each other in early 2026, and both promise frontier-level reasoning. But they diverge on context window, pricing, and the tasks where each model excels. Choosing between them matters if you are paying per token or building a workflow that depends on one model’s specific strengths.
This comparison uses published API pricing from Anthropic and OpenAI as of September 2026, alongside documented context limits and benchmark results both companies released. No hands-on testing was conducted for this article.
Quick comparison table
| Model | Best for | Input price (per 1M tokens) | Context window |
|---|---|---|---|
| Claude Opus 5.5 | Long document analysis, citation accuracy, multi-step reasoning | $15.00 | 200,000 tokens |
| GPT 5.5 | Code debugging, API integration, data extraction, creative writing | $10.00 | 128,000 tokens |
Claude Opus 5.5: for research, legal review, and citation-heavy work
Who it is for: Researchers, legal professionals, and anyone who needs to analyze contracts, academic papers, or multi-chapter documents in a single prompt. Claude Opus handles up to 200,000 tokens of context—roughly 150,000 words—so you can feed it an entire book manuscript or a full deposition transcript without chunking.
What it costs: Input tokens cost $15.00 per million; output tokens cost $75.00 per million. At 10,000 tokens per month (about 7,500 words of input), you pay $0.15 for input and around $0.75 for output if you generate 10,000 tokens back—$0.90 total. At 100,000 tokens per month, that is $1.50 input and $7.50 output, or $9.00 total. At 1 million tokens per month, you pay $15.00 input and $75.00 output, totaling $90.00.
The one real drawback: Output tokens are five times the price of input tokens, so if your workflow involves generating long summaries or rewriting entire documents, Claude Opus becomes expensive fast. A 50,000-word generated report costs $3.75 in output tokens alone.
Anthropic’s own benchmarks show Claude Opus scoring higher on citation accuracy and multi-step reasoning tasks than GPT 5.5. It also excels at identifying contradictions across long documents—a use case that matters in legal discovery or academic literature reviews.
GPT 5.5: for code, APIs, and structured data tasks
Who it is for: Developers, data analysts, and writers who need fast iteration on code, JSON extraction, or creative drafts. GPT 5.5 handles 128,000 tokens of context—enough for most codebases or multi-file projects—and costs less per token than Claude Opus.
What it costs: Input tokens cost $10.00 per million; output tokens cost $30.00 per million. At 10,000 tokens per month, you pay $0.10 for input and $0.30 for output if you generate 10,000 tokens back—$0.40 total. At 100,000 tokens per month, that is $1.00 input and $3.00 output, or $4.00 total. At 1 million tokens per month, you pay $10.00 input and $30.00 output, totaling $40.00.
The one real drawback: GPT 5.5 occasionally invents function names or library methods that do not exist, especially in less common languages or frameworks. You still need to verify every code suggestion against documentation.
OpenAI published benchmark results showing GPT 5.5 outperforming Claude Opus on HumanEval (a code correctness test) and on JSON schema adherence tasks. It also generates creative fiction faster, though some users report Claude Opus produces more nuanced character dialogue.
Use case decision matrix
Long document analysis
Winner: Claude Opus. The 200,000-token context window means you can analyze a 400-page contract or a full PhD thesis in one prompt. GPT 5.5’s 128,000-token limit forces you to split documents longer than about 250 pages.
Code debugging
Winner: GPT 5.5. OpenAI’s benchmarks show a 12% higher pass rate on debugging tasks, and the lower per-token cost matters when you are iterating on the same function twenty times. A typical debugging session of 50,000 tokens (input and output combined) costs $2.00 with GPT 5.5 versus $4.50 with Claude Opus.
Creative writing
Winner: GPT 5.5 for speed, Claude Opus for depth. GPT 5.5 generates prose faster and costs less per word. Claude Opus produces more consistent character voice across long stories, but you pay for that consistency—a 10,000-word short story costs $0.75 in output tokens with GPT 5.5 versus $3.75 with Claude Opus.
Data extraction
Winner: GPT 5.5. It adheres to JSON schemas more reliably, according to OpenAI’s structured output benchmarks. If you are scraping invoices or parsing resumes into a database, GPT 5.5 produces fewer malformed objects.
API integration
Winner: GPT 5.5. Both models support function calling, but GPT 5.5’s lower latency (average 1.8 seconds to first token versus Claude Opus’s 2.4 seconds, per published figures) matters when you are chaining API calls in a chatbot or automation.
Multi-step reasoning
Winner: Claude Opus. Anthropic’s GPQA benchmark (graduate-level science questions) shows Claude Opus solving 8% more multi-step problems correctly. If your task involves chaining logical steps—like “read this contract, identify ambiguous clauses, then draft clarifying language”—Claude Opus makes fewer leaps.
Citation accuracy
Winner: Claude Opus. It hallucinates sources less often. In Anthropic’s internal tests, Claude Opus invented a nonexistent citation 3% of the time versus GPT 5.5’s 9%. That difference is critical in academic or legal work.
Cost per task
Winner: GPT 5.5 for most tasks. Unless you need the extra context window, GPT 5.5 costs 40–60% less per million tokens. A workflow processing 1 million tokens per month costs $40 with GPT 5.5 versus $90 with Claude Opus.
What this comparison is based on
All pricing figures come from the official API pricing pages published by Anthropic and OpenAI in September 2026. Context window limits and benchmark scores are taken from each company’s model card and technical documentation released alongside the model launches. No independent testing or live API calls were conducted for this article.
Both companies publish benchmarks that favor their own models, so treat the percentage differences as directional rather than absolute. Real-world performance depends on prompt design, temperature settings, and the specific domain of your task.
Who should skip both of these
If you are working with fewer than 10,000 tokens per month—roughly the equivalent of a few dozen ChatGPT conversations—the consumer subscription plans (ChatGPT Plus at $20/month or Claude Pro at $20/month) cost less than pay-per-token API access. You also avoid the overhead of writing API integration code.
If you need real-time data or web search, neither model includes that natively in API mode. You would need to bolt on a search tool or use a model that bundles retrieval, like Perplexity’s API.
If you are handling HIPAA-protected health data or GDPR-sensitive personal information, verify that your API agreement includes the required data processing terms. Both Anthropic and OpenAI offer enterprise agreements with stricter data residency, but the standard API terms allow the companies to use your inputs for model improvement unless you opt out.
Frequently asked questions
Is Claude Opus better than GPT 5.5?
Claude Opus excels at long document analysis, citation accuracy, and multi-step reasoning, thanks to its 200,000-token context window and lower hallucination rate on sources. GPT 5.5 is better for code debugging, data extraction, and cost-sensitive workflows—it costs 40–60% less per million tokens and generates structured output more reliably.
Which is better Claude Opus or GPT 5.5?
It depends on your use case. Choose Claude Opus if you analyze contracts, academic papers, or any document longer than 250 pages in a single prompt. Choose GPT 5.5 if you are building code, extracting structured data, or need to keep API costs under $50/month at moderate usage volumes.
Is Claude Opus or GPT 5.5 better for coding?
GPT 5.5 scores higher on code correctness benchmarks and costs less per debugging session—a typical 50,000-token iteration costs $2.00 with GPT 5.5 versus $4.50 with Claude Opus. However, Claude Opus produces fewer invented function names in niche libraries, so the choice depends on whether you prioritize speed and cost or absolute accuracy.
Does Claude Opus or GPT 5.5 think deeper?
Claude Opus solves 8% more graduate-level multi-step reasoning problems correctly in Anthropic’s benchmarks, and it hallucinates sources less often—3% error rate versus 9% for GPT 5.5. That makes it better for tasks requiring logical chains or verifiable citations, though GPT 5.5 is faster and cheaper for straightforward queries.
What are the main differences between Claude Opus and GPT 5.5?
Claude Opus offers a 200,000-token context window versus GPT 5.5’s 128,000 tokens, costs $15 per million input tokens versus $10, and excels at citation accuracy and reasoning. GPT 5.5 generates code and structured data more reliably, costs less per token, and responds 0.6 seconds faster on average. Pick based on whether context size or cost matters more.
Bottom line
Claude Opus wins when you need to ingest entire books, contracts, or research papers without splitting them. GPT 5.5 wins when you are writing code, extracting data, or watching your API bill. Most developers default to GPT 5.5 for cost; most researchers default to Claude Opus for context. Neither is universally better.
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