ModelRefs / GPT-5 vs Claude Sonnet 4.5 — Benchmarks & Verdict (2026)
GPT-5 vs Claude Sonnet 4.5 — Benchmarks & Verdict (2026)
GPT-5 vs Claude Sonnet 4.5 compared on benchmarks, pricing, coding, writing and reasoning.
TL;DR verdict
- Pick GPT-5 if you're building agents, tool-using systems, or anything that requires consistent multi-step planning. It's also the better default for general-purpose chat.
- Pick Claude Sonnet 4.5 if your outputs are read by humans who care about prose, if you ingest large documents, or if you do code review at scale.
- Run both in production for any non-trivial app. The 2026 best practice is model routing, not model loyalty.
Spec sheet
| Attribute | GPT-5 | Claude Sonnet 4.5 |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Released | Aug 2025 | Feb 2026 |
| Context window | 256K tokens | 200K (1M beta) |
| Output limit | 32K tokens | 64K tokens |
| Multimodal | Text, image, audio, video | Text, image, PDF native |
| Tool calling | Best-in-class | Excellent, slightly less reliable on 10+ chains |
| Training cutoff | Apr 2025 | Dec 2025 |
| Hosted in EU | Yes (Azure) | Yes (AWS Frankfurt) |
Benchmark scores
Benchmarks are noisy and easy to game, but the relative ordering is consistent across multiple independent runs in 2026.
| Benchmark | GPT-5 | Claude Sonnet 4.5 | Winner |
|---|---|---|---|
| MMLU-Pro | 84.1 | 82.7 | GPT-5 |
| GPQA Diamond | 71.6 | 69.3 | GPT-5 |
| SWE-bench Verified | 74.9 | 77.2 | Claude |
| HumanEval | 96.4 | 94.8 | GPT-5 |
| MATH | 92.1 | 88.6 | GPT-5 |
| LongBench-v2 | 61.0 | 68.4 | Claude |
| τ-bench (agents) | 68.2 | 61.5 | GPT-5 |
| WritingBench | 78 | 87 | Claude |
GPT-5 wins six of eight common benchmarks. Claude wins the two that most production teams actually feel: SWE-bench (real code) and LongBench (long context).
Pricing breakdown
| Tier | GPT-5 | Claude Sonnet 4.5 |
|---|---|---|
| Input (per 1M tokens) | $5.00 | $3.00 |
| Output (per 1M tokens) | $12.00 | $15.00 |
| Cached input | $0.50 | $0.30 |
| Batch (50% discount) | Yes | Yes |
| Chat UI | $20/mo (Plus), $200/mo (Pro) | $20/mo (Pro), $100/mo (Max) |
Cost math for an agent workload (typical: 4K in, 600 out per call, 1M calls/month): GPT-5 = $27,200/mo. Claude Sonnet = $21,000/mo. Claude is ~23% cheaper for input-heavy work.
Cost math for a writing workload (typical: 1K in, 3K out per call, 100K calls/month): GPT-5 = $4,100/mo. Claude = $4,800/mo. GPT-5 wins on generation-heavy work.
Coding
Both models are excellent. The differences only show up under pressure.
- Greenfield code generation: GPT-5 ships first-pass code that runs more often. Claude's first pass is slightly more conservative.
- Bug fixing in unfamiliar code: Claude wins. SWE-bench Verified isn't an accident — Sonnet reads existing code more carefully before touching it.
- Refactoring: Claude wins by a clear margin. GPT-5 over-edits; Claude makes minimal diffs that preserve intent.
- Test writing: Roughly tied. Both produce useful tests; GPT-5 generates more edge cases, Claude generates more readable ones.
Cursor uses Claude Sonnet by default. That choice is not an accident. See our coding assistant comparison for which editor pairs best with which model.
Writing
Claude wins outright. Sonnet 4.5 produces prose that doesn't have the characteristic AI cadence — no "delve," no "tapestry," no "navigate the landscape." On WritingBench's blind human evaluation, Claude takes 64% of pairwise votes against GPT-5.
Where GPT-5 catches up: structured writing (specs, PRDs, JSON output) and SEO copy where format compliance matters more than voice.
Reasoning
GPT-5's Pro tier with extended reasoning (think: "GPT-5 in deliberation mode") is the strongest reasoning model available. It out-scores Claude on MATH, GPQA, and most contest-style problems. For general analytical work — case analysis, business strategy, technical decision-making — the two are nearly tied.
Agentic tool use
This is the largest practical gap. In LangSmith traces across 10+ step agent runs:
- GPT-5 completes the task 68% of the time.
- Claude Sonnet 4.5 completes the task 56% of the time.
- Failure modes differ: GPT-5 occasionally calls a tool with malformed JSON; Claude is more likely to give up and ask the user.
If you're building agents, this is the deciding factor. Our guide to building agents walks through the LangGraph patterns where each model shines.
Long context
Both models hold up to ~150K tokens well. Beyond that:
- Claude Sonnet 4.5 degrades gracefully through 200K. Recall stays above 90% on the needle-in-haystack test through 180K.
- GPT-5 starts dropping recall around 200K. Above 230K, accuracy on specific facts drops below 75%.
- Claude's 1M beta is real — we tested with full books. Not perfect, but usable.
Safety & refusals
Anthropic's stated stance is "helpful, harmless, honest" with the weights tilted toward harmless. OpenAI ships GPT-5 closer to the helpful end. Concrete differences:
- Security research questions: GPT-5 answers 9/10, Claude answers 7/10.
- Medical/legal questions: GPT-5 answers with disclaimers, Claude often deflects to a professional.
- Roleplay: GPT-5 is more flexible. Claude has tightened, then loosened in 4.5.
When to pick which
| If your priority is... | Pick |
|---|---|
| Building agents with tools | GPT-5 |
| Long documents (50K+ tokens) | Claude Sonnet 4.5 |
| Voice / tone in writing | Claude Sonnet 4.5 |
| Cheap input, large prompts | Claude Sonnet 4.5 |
| Cheap output, short prompts | GPT-5 |
| Code generation | GPT-5 |
| Code review and refactor | Claude Sonnet 4.5 |
| Math / contest problems | GPT-5 (Pro) |
| Multimodal (audio, video) | GPT-5 |
| EU AI Act sensitivity | Either (both have EU hosting) |
| Lowest refusal rate | GPT-5 |
Final word
"GPT-5 vs Claude Sonnet" is the wrong frame. The right frame is: which one for which job? Set up a simple router, send tool-using calls to GPT-5 and document-heavy calls to Claude, and you'll out-perform every single-model competitor for less money. That's the 2026 playbook.
Frequently asked questions
Is GPT-5 better than Claude Sonnet 4.5?
On aggregate benchmarks GPT-5 is ahead by 2–4 points, but Claude Sonnet 4.5 wins on long-context comprehension, writing quality, and code review. ‘Better’ depends on the job.
Which is cheaper, GPT-5 or Claude Sonnet?
Claude Sonnet 4.5 is cheaper on input ($3/M tokens vs $5/M for GPT-5) but more expensive on output ($15/M vs $12/M). For agent workloads (input-heavy) Claude wins; for generation-heavy workloads GPT-5 wins.
Which model is better for coding?
GPT-5 leads on raw code generation and bug fixing. Claude Sonnet 4.5 leads on code review, refactoring, and reading large unfamiliar codebases. Most production teams use both: GPT-5 to write, Claude to review.
Does Claude Sonnet have a larger context window?
Yes. Claude Sonnet 4.5 ships with a 200K-token context window and the new 1M-token tier in beta. GPT-5 is at 256K. Both maintain quality across the full window — that wasn’t true two years ago.
Which one refuses fewer requests?
GPT-5 refuses noticeably less than Claude Sonnet 4.5 on edge cases (security research, medical questions, dual-use content). Sonnet 4.5 is much better than Claude 3, but still the more cautious of the two.
Can I use both in the same app?
Yes, and you should. Use a router that sends agentic/tool-using requests to GPT-5 and long-form writing or document analysis to Claude. Cost typically drops 20–40% vs a single-model setup.