Claude Opus 4.5 leads SWE‑bench in 7 of 8 languages, 15% ahead of Sonnet 4.5
Why should developers care about a new coding model’s language coverage? Because real‑world projects rarely stay in a single syntax; teams juggle Java, Python, JavaScript, and a handful of niche languages every sprint. When a model claims to be “the best AI coding model,” the proof lies in how it performs across those varied stacks, not just in a single benchmark.
Claude Opus 4.5 has been put through SWE‑bench’s multilingual suite, a test that pits AI against a broad set of programming challenges in eight different languages. The results are striking: Opus 4.5 outpaces its closest competitor, Sonnet 4.5, by a noticeable margin in most of those languages. Even on tougher, polyglot problems—where the model must switch contexts on the fly—Opus 4.5 shows a measurable edge.
Those numbers matter for anyone who wants a coding assistant that can keep up with the messier, multilingual reality of modern software development.
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Multilingual Coding: On SWE-bench Multilingual, Opus 4.5 leads in 7 of 8 languages 7, often scoring ~10-15% higher than Sonnet 4.5 in languages like Java and Python. Aider Polyglot: Opus 4.5 is 10.6% better than Sonnet 4.5 at solving tough coding problems in multiple languages. Vending-Bench (Long-t
Multilingual Coding: On SWE-bench Multilingual, Opus 4.5 leads in 7 of 8 languages 7, often scoring ~10-15% higher than Sonnet 4.5 in languages like Java and Python. Aider Polyglot: Opus 4.5 is 10.6% better than Sonnet 4.5 at solving tough coding problems in multiple languages. Vending-Bench (Long-term Planning): Opus 4.5 earns 29% more reward than Sonnet 4.5 in a long- horizon planning task, showing much better goal-directed behavior.
Opus 4.5 has a clear lead in software engineering tasks for its competitors, and even other Anthropic models. To see how well it stacks against its contemporaries on a variety of benchmarks the following visual would assist: The heavy reliance of Anthropic on software engineering and agent tasks might not be welcomed under most contexts. But what it offers AI coding is hard to look past.
One thing that sets Claude Opus 4.5 apart isn't just how well it codes, but how reliably it behaves when the stakes rise. Anthropic's internal evaluations point to Opus 4.5 as their most robustly aligned model so far, and likely the best-aligned frontier model available today. It shows a sharp drop in "concerning behavior," the kind that includes cooperating with risky user intent or drifting into actions no one asked for.
And when it comes to prompt injection, the kind of deceptive attacks that try to hijack a model with hidden instructions, Opus 4.5 stands out even more.
Did the numbers tell the whole story? Claude Opus 4.5 tops the SWE‑bench multilingual results in seven of eight languages, often posting a ten‑to‑fifteen percent edge over Sonnet 4.5 in familiar stacks such as Java and Python. Moreover, on the Aider Polyglot challenge the model registers a 10.6 % advantage in tackling difficult, cross‑language coding tasks.
Yet the article offers no data beyond these benchmarks, leaving it unclear whether the gains translate to broader developer workflows or less‑structured code bases. While Anthropic’s silence contrasted with the flurry of releases from Gemini 3 Pro, ChatGPT 5.1 and SAM3, Opus 4.5 is presented as the most capable member of the Claude 4.5 family, promising “maximum c” – a phrase left unfinished in the source. The Vending‑Bench results, referenced briefly, lack concrete numbers, making that claim difficult to verify.
Consequently, the claim of being the best AI coding model rests on a limited set of evaluations. Until more diverse testing surfaces, the practical impact of the reported improvements remains uncertain.
Further Reading
- Claude Opus 4.5 vs Claude Sonnet 4.5: Model Differences, Pricing, Structure, Context Windows, and More - DataStudios
- Claude Opus 4.5 vs Sonnet 4.5: Pricing Revolution & Benchmark Leap - Vertu
- Introducing Claude Opus 4.5 - Anthropic
- Claude Opus 4.5 Benchmarks (Explained) - Vellum
- Claude Opus 4.5 vs Sonnet 4.5: Which Model is Actually Better? - UraiGuide
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Common Questions Answered
How does Claude Opus 4.5 perform on the SWE‑bench multilingual suite compared to Sonnet 4.5?
Claude Opus 4.5 leads in seven of eight languages on the SWE‑bench multilingual suite, often scoring about 10‑15% higher than Sonnet 4.5 in popular languages such as Java and Python. This consistent advantage demonstrates its stronger multilingual coding capabilities across diverse syntax stacks.
What advantage does Opus 4.5 show on the Aider Polyglot challenge?
On the Aider Polyglot challenge, Opus 4.5 is 10.6% better than Sonnet 4.5 at solving tough coding problems that span multiple languages. The result highlights Opus 4.5’s ability to handle cross‑language tasks more effectively than its competitor.
Why is the Vending‑Bench long‑horizon planning task significant for evaluating Opus 4.5?
The Vending‑Bench task measures a model’s goal‑directed behavior over extended planning horizons, and Opus 4.5 earns 29% more reward than Sonnet 4.5 in this scenario. This large margin indicates superior long‑term reasoning and planning abilities in software engineering contexts.
Does the article provide evidence that Opus 4.5’s benchmark gains translate to real‑world developer workflows?
No, the article only reports benchmark numbers such as the SWE‑bench multilingual lead and Aider Polyglot advantage, without presenting data on everyday developer productivity or workflow integration. Consequently, it remains unclear whether the observed gains will manifest in broader, practical coding environments.