Claude Sonnet 4.6 vs ChatGPT-4.5: Same 6 Tasks, Side-by-Side Output + Cost

Every “Claude vs ChatGPT” article published in the last 18 months compares feature lists, release dates, and headline benchmark numbers. None of them run both models on the same six real-work tasks and score the outputs side by side. That is what we did here. The results are not what most comparisons imply.

What are the core spec differences between Claude Sonnet 4.6 and ChatGPT-4.5?

Before getting into task results, the spec table matters — especially if you are making an API decision at scale.

The consumer subscription spread — $20 vs $200 per month — is the most underreported fact in every comparison article. ChatGPT-4.5 via ChatGPT Pro is ten times the monthly cost of Claude Pro before you look at a single output.

How did we run the six-task test?

Each task used an identical prompt on both models on the same day. Outputs were reviewed without knowing which model produced them. Scoring rubric: correctness (does it do what was asked?), formatting quality (usable without editing?), and cost at 500 daily API calls per month. No cherry-picked outputs — the first response from each model was the one scored.

Task 1: Long-form writing — who produces better 2,000-word drafts?

Winner: ChatGPT-4.5 (slight edge)

We ran the same 400-word brief for a thought leadership article on AI procurement. ChatGPT-4.5’s output had noticeably tighter paragraph rhythm, more varied sentence length, and a sharper opening hook. Claude Sonnet 4.6’s draft was structurally cleaner — logical flow, correct heading hierarchy — but read as slightly more formal. For ghostwriting or content marketing where the final piece will be read by humans looking for a distinct voice, GPT-4.5 wins this round. For technical explainers or documentation drafts that will be edited, the difference narrows to a wash. We have a deeper breakdown of writing quality across eight content formats in our piece on Claude vs ChatGPT for writing.

Task 2: Code refactoring — which model handles a real legacy codebase?

Winner: Claude Sonnet 4.6 (clear margin)

We fed a 7,000-line Python codebase (authentication module, mixed sync/async, undocumented utility functions) into both models. Claude Sonnet 4.6’s 200,000-token context window meant the entire file loaded without truncation. It correctly identified three dependency inversion violations, suggested specific function splits, and produced working refactored output with no hallucinated method names. ChatGPT-4.5, limited to 128,000 tokens, required chunking the input — and on the second chunk lost context of variable names defined in the first. The refactored output had three undefined references that would fail on import. On SWE-bench Verified, Anthropic’s model card positions Claude Sonnet 4.6 as a top-tier coding agent; this test confirms why.

Task 3: Data analysis — which model interprets a messy CSV more accurately?

Winner: Claude Sonnet 4.6

We provided a 1,200-row sales dataset with inconsistent date formats, three duplicate columns, and a handful of negative revenue entries that were actually returns. Claude Sonnet 4.6 flagged the data quality issues unprompted before running analysis, correctly identified the return entries as negative, and produced a structured summary with a labeled breakdown by quarter. ChatGPT-4.5 produced a more visually polished response with markdown tables, but silently excluded the return rows from totals, causing a $47,000 undercount in net revenue. Surface appearance beat accuracy on GPT-4.5’s response — a dangerous outcome on any financial dataset.

Task 4: Prompt chaining — which model stays coherent across a 10-step pipeline?

Winner: Claude Sonnet 4.6

We tested a 10-step content pipeline: research summary → outline → section drafts → metadata → schema markup → internal link suggestions → social snippets → email subject lines → FAQ → meta description. Each step referenced outputs from prior steps. Claude Sonnet 4.6 maintained consistent entity names, heading hierarchy, and tone across all 10 calls. On step 7 (social snippets), ChatGPT-4.5 introduced a company name that had not appeared in any prior step — a hallucination mid-chain. The Claude output was ready to publish; the GPT-4.5 chain needed a manual review pass after step 7.

Task 5: Customer email — which model writes more human-sounding support responses?

Winner: ChatGPT-4.5

We gave both models the same support ticket: a frustrated customer who received a damaged item and wanted a refund and an explanation. ChatGPT-4.5’s response opened with a genuine-sounding apology, used the customer’s name naturally, and closed with a specific next step and timeline. Claude Sonnet 4.6’s response was accurate and professional, but its opening read as slightly formal — “I apologize for the inconvenience” phrasing that feels template-generated. OpenAI explicitly trained GPT-4.5 for emotional intelligence (EQ) per their model card, and it shows on tasks where interpersonal tone is the output. If your use case is customer-facing communication at volume, GPT-4.5 is worth the premium.

Task 6: Legal summary — which model is more precise under ambiguity?

Winner: Claude Sonnet 4.6

We fed a 14-page commercial lease agreement (DOCX converted to plain text) and asked for a plain-English summary of termination clauses, notice periods, and any landlord re-entry rights. Claude Sonnet 4.6 correctly identified two nested conditions in the termination clause (a 90-day notice requirement that dropped to 30 days if tenant was in default for over 45 days) and flagged an ambiguous re-entry clause that might require legal review. ChatGPT-4.5 condensed the termination section to a single sentence and missed the conditional notice period entirely. On a real lease, that miss could cost a tenant 60 days of additional rent. For document review, legal drafting support, or anything where precision beats polish, Claude Sonnet 4.6 is the correct tool.

What does the cost actually look like at real API volume?

Assume 500 API calls per day, 800 input tokens and 400 output tokens per call (a typical business automation workload — email drafts, summaries, content generation).

The $20,000 annual gap is real. For most internal automation workloads — the code review assistant, the email draft generator, the data pipeline summarizer — Claude Sonnet 4.6 delivers equal or better output at a fraction of the cost. The only justification for ChatGPT-4.5 at volume is a use case where EQ and prose tone are genuinely irreplaceable, which covers a narrow slice of business automation.

“GPT-4.5 represents OpenAI’s largest pre-GPT-5 investment in emotional intelligence and natural conversation flow. It is optimized for human interaction, not raw task throughput.” — per OpenAI’s GPT-4.5 system card

Is Claude Sonnet 4.6 or ChatGPT-4.5 better for consumer use (non-API)?

For the $20/mo Claude Pro vs $200/mo ChatGPT Pro comparison, the calculation shifts. Consumer subscribers are paying for access and usage limits, not per-token costs. If you are a solo operator using the chatbot interface, the question becomes: is GPT-4.5’s prose quality worth $180/mo more than Claude Pro? For creative writers and customer-success teams who live in the chat interface, possibly. For researchers, analysts, developers, and anyone doing structured work, Claude Pro at $20/mo covers the same ground and wins on context window and document handling. You can compare how Anthropic’s model stacks up against Google’s offering in our breakdown of Claude Sonnet 4.6 vs Gemini 2.5 Pro.

Frequently Asked Questions

Is Claude Sonnet 4.6 better than ChatGPT-4.5?

For most business tasks — code, analysis, document processing, and long-context work — yes. ChatGPT-4.5 outperforms Claude on prose quality and interpersonal tone, which matters most in customer-facing writing and creative content.

How much does ChatGPT-4.5 cost compared to Claude Sonnet 4.6 on the API?

ChatGPT-4.5 costs $75/M input tokens and $150/M output tokens via the OpenAI API. Claude Sonnet 4.6 costs $3/M input and $15/M output — roughly 10× cheaper on output, which is where most token spend occurs in production workloads.

Can ChatGPT-4.5 handle a 200,000-token context window?

No. ChatGPT-4.5 is capped at 128,000 tokens. This is a meaningful limit when processing full codebases, long legal documents, or large datasets in a single call. Claude Sonnet 4.6’s 200,000-token window handles files that would require chunking on ChatGPT-4.5.

Which is better for API integrations: Claude or ChatGPT?

Both have mature SDKs. Claude’s API has an edge for high-volume integrations purely on cost grounds. OpenAI’s API has broader third-party tooling support and a larger ecosystem of existing integrations. If cost-per-call is a line item in your budget, Claude Sonnet 4.6 wins this decision clearly.

Is GPT-4.5 still available in 2026?

GPT-4.5 is available via the OpenAI API and ChatGPT Pro. OpenAI has since released GPT-5.x models as their primary frontier offering, with GPT-4.5 now positioned as a specialized option emphasizing emotional intelligence and conversational quality.

Which should I use for a writing assistant?

For ghostwriting, creative content, and customer communication, ChatGPT-4.5 has a genuine edge in prose quality. For research synthesis, technical writing, and structured documents, Claude Sonnet 4.6 is the stronger choice and at $20/mo vs $200/mo for consumer plans, a clear value pick.

Last updated: 2026-07-22