Claude Sonnet 4.5 vs GPT-5 in 2026: 8/15 wins, 1.7x faster

Claude Sonnet 4.5 is the mid-tier Claude, priced at $3/$15 per million tokens. GPT-5 is OpenAI's current mid-tier, at $1.25/$10. They look like reasonable swap candidates for developers who want more than a budget model without paying frontier prices. We ran both through 20 real developer tasks to find out where they actually differ.

Methodology

Twenty prompts, two models, one judge. The tasks covered debugging slow Python, writing SQL with joins and aggregates, refactoring Express.js routes to async/await, reviewing JWT auth middleware for security gaps, explaining HTTPS internals in plain language, solving a compound-motion problem step by step, estimating SaaS runway, and several algorithm and documentation tasks.

Both models received the identical prompt. anthropic/claude-sonnet-4 judged each pair twice with positions swapped, so the order of responses couldn't influence the outcome. A verdict only counted when both directions agreed; disagreements became ties. Full methodology is at /docs/benchmarks.

Prompt breakdown: 7 coding tasks, 4 reasoning/math, 3 technical explanations, 3 analysis/security, 3 writing tasks.

Results overview

Five prompts never finished because GPT-5 hit the 45-second request timeout. The tasks that timed out weren't cherry-picked gotchas: memory-leak debugging, PostgreSQL slow-query analysis, concurrent fetch with a rate limiter, TypeScript deep-merge, and React re-render analysis. Claude completed all 20 within the window.

Among the 15 valid comparisons, Claude won 53%, GPT-5 won 27%, and 3 ended tied (20%).

Where each model won

Claude dominated reasoning and structured output. On the SaaS runway calculation (5% monthly churn, $80K burn, $500K in the bank), the train-speed collision problem, and the SQL query with multi-table joins, Claude produced correct answers faster and with more organized breakdowns. On the Fibonacci debug task, Claude returned three working O(n) implementations with trade-off explanations. GPT-5 gave a clean single solution that contained a subtle base-case bug.

GPT-5 led on security and conciseness. The JWT middleware review is the clearest case: GPT-5 identified algorithm confusion attacks (the "none" alg bypass), missing issuer/audience claim validation, and key rotation gaps that Claude's review didn't catch. On the "write a README" task and the longest-substring algorithm, GPT-5's tighter prose and compact code style scored better.

Three prompts in detail

Fibonacci debug (Claude wins)

Prompt: "Here is a Python function that returns the nth Fibonacci number but is extremely slow for large n. Debug it and rewrite it in O(n) time."

Claude returned three correct implementations (iterative, memoization, functools.lru_cache) with a brief explanation of why the original's O(2^n) recursion was the bottleneck. GPT-5 returned one clean iterative solution with input validation, but the algorithm produced fib(0) = 1 rather than the correct 0, because the loop ran over range(n) starting at zero rather than the correct range(2, n+1).

Judge reasoning (forward direction):

"Assistant A's iterative solution correctly handles the edge cases fib(0)=0 and fib(1)=1. Assistant B's solution has a subtle bug - it returns 1 for fib(0) instead of 0 due to the loop structure, making it mathematically incorrect for this base case. While Assistant B includes error handling that A lacks, this does not compensate for the algorithmic error."

Claude: 9.3s. GPT-5: 11.3s.

JWT middleware security review (GPT-5 wins)

Prompt: "Review this authentication middleware for security issues." (Code: JWT verify with a hardcoded string secret, no Bearer scheme enforcement.)

Claude flagged the hardcoded secret, missing Bearer validation, and provided corrected code. GPT-5 caught the same issues and also flagged algorithm confusion attacks (the "none" algorithm bypass if misconfigured), missing issuer/audience claim validation, and token revocation gaps. These are real production risks that Claude left unmentioned.

Judge reasoning (forward direction):

"Assistant B demonstrates deeper security expertise by identifying more comprehensive issues including algorithm confusion attacks, missing claim validation (issuer/audience), token revocation concerns, missing WWW-Authenticate headers per RFC 6750, and clock tolerance issues. Both responses correctly identify the core issues, but Assistant B covers significantly more security vulnerabilities and demonstrates more advanced understanding of JWT security considerations."

Claude: 14.5s. GPT-5: 29.4s. GPT-5 took twice as long and still won the round.

SQL customers query (Claude wins)

Prompt: "Find all customers who made 3+ purchases in the last 90 days with total spend over $500."

Claude returned a query that included purchase_count and total_spend in the SELECT, made the filtering conditions explicit, and added dialect notes for MySQL and SQL Server. GPT-5 returned correct PostgreSQL and MySQL variants, but the SELECT only returned the identifier columns. A caller who needed the aggregate values would need a second query or a post-hoc rewrite. See our SQL generation benchmark for how these models performed on a fuller set of SQL tasks.

Claude: 7.2s. GPT-5: 12.6s.

Subscription vs API

Break-even estimate (assuming a typical call averages 1,000 input + 500 output tokens):

• Claude Sonnet 4.5: $0.0105 per call. At $20/month, break-even is ~1,900 calls/month, or about 63/day.
• GPT-5: $0.00625 per call. At $20/month, break-even is ~3,200 calls/month, or about 107/day.

GPT-5 is significantly cheaper on raw API tokens. If you're building a product that processes thousands of requests per day and quality is acceptable, the token savings add up. But the subscriptions (Claude Pro, ChatGPT Plus) give access to claude.ai and ChatGPT respectively, not programmatic API access. If you're building an application, the API cost comparison is what matters.

Verdict

Claude Sonnet 4.5 wins: 8 of 15 valid comparisons, zero timeouts, and 1.7x faster average response. The edge is clearest on reasoning tasks (math, step-by-step explanations, multi-column SQL) and on correctness under pressure (the Fibonacci base-case bug).

GPT-5 is the right choice for security reviews and for any task where compact, opinionated code beats well-formatted coverage. It is also meaningfully cheaper on API tokens ($1.25/$10 vs $3/$15), which matters at scale.

A similar pattern showed up at the frontier tier: our Claude Opus 4.7 vs GPT-5.5 coding benchmark found Claude ahead on multi-constraint code generation and latency, GPT-5.5 stronger on security-focused SQL and Python debugging. The mid-tier results are consistent.

For most solo developers, Claude Sonnet 4.5 is the better API default for general-purpose tasks. If security audits or tight API cost are the priority, GPT-5 deserves the test. Try both through LLMTest on your own prompts before committing.

How this was tested

• Models: anthropic/claude-sonnet-4-5 vs openai/gpt-5, routed through the LLMTest proxy at llmtest.io/v1
• Prompts: 20 real developer tasks across debugging, SQL, security review, reasoning, and documentation
• Judge: anthropic/claude-sonnet-4 with position-swap dual judging (each prompt judged twice with positions reversed; verdicts count only when both directions agree)
• Valid comparisons: 15 of 20 (GPT-5 exceeded the 45-second request timeout on 5 prompts; Claude completed all 20)
• Total runner cost: $0.60
• Full methodology: /docs/benchmarks