By ByteBot
Anthropic’s Claude Opus 4.5 just became available across every major IDE on December 3, 2025. It’s the first AI coding model to break 80% on SWE-bench Verified with an industry-leading 80.9% score, putting it 3-5 percentage points ahead of GPT-5.1 Codex Max and Google Gemini 3 Pro. If you’re using GitHub Copilot, VS Code, JetBrains, Xcode, or Eclipse, you can access this model right now. This is what reclaiming the coding crown looks like.
The Benchmark Story: 80.9% Changes the Game
SWE-bench Verified isn’t some synthetic coding test. It’s 500 human-validated GitHub issues from real open-source projects that actual engineers confirmed are solvable. Each task requires understanding a codebase, implementing a fix, and passing unit tests. At 80.9%, Claude Opus 4.5 is the first model to break the 80% barrier. GPT-5.1 Codex Max sits at 77.9%. Gemini 3 Pro trails further behind.
That 3-5 percentage point gap matters at this level. We’re not talking about 40% versus 45%. When models are already solving most real-world coding tasks, every percentage point represents harder problems getting solved. The competitive moat here isn’t enormous, but it’s real.
Claude also dominates OSWorld at 66.3%, a benchmark testing whether AI can actually operate desktop computers, manipulate spreadsheets, and navigate UIs. No other model comes close on that test.
But Does It Matter in Real Work?
Here’s the tension. Simon Willison, a prominent developer, spent a weekend with Opus 4.5 in early access. He used it to ship an alpha release of sqlite-utils: 20 commits, 39 files changed, 2,022 additions, 1,173 deletions. The model “was responsible for most of the work” on several large-scale refactorings.
His assessment? “Clearly an excellent new model.” But when his preview expired and he switched back to Sonnet 4.5, he “kept on working at the same pace.” His conclusion: frontier LLMs are harder to differentiate in production coding than benchmarks suggest.
This doesn’t mean the benchmarks are meaningless. It means that at the frontier, the differences are subtle. An 80.9% model will occasionally solve a problem that a 77.9% model can’t. But for most everyday coding tasks, both work well enough that the practical difference fades.
Where You Can Use It Today
The December 3 rollout is the real story. Claude Opus 4.5 is now available through GitHub Copilot across Visual Studio Code, Visual Studio, JetBrains IDEs, Xcode, Eclipse, and GitHub Mobile. This isn’t vaporware. If you have a Copilot Enterprise, Business, Pro, or Pro+ subscription, you can select Opus 4.5 from the model picker in agent, ask, and edit modes right now.
For organizations, admins need to opt in by enabling the Claude Opus 4.5 policy in Copilot settings. But once that’s done, your entire team has access to what is currently the best-performing AI coding model on standardized benchmarks.
GitHub Copilot has over 20 million users and is deployed at 90% of Fortune 100 companies. This rollout makes Opus 4.5 accessible to millions of developers immediately. That scale matters.
Token Efficiency and Pricing Improvements
Opus 4.5 also uses 48-65% fewer tokens than its predecessors while maintaining or exceeding performance. GitHub’s early testing reports that it “surpasses internal coding benchmarks while cutting token usage in half.” At the medium effort setting, it matches Sonnet 4.5 performance using 76% fewer output tokens.
This translates to faster response times and lower costs. Anthropic dropped the price 67%: $5 input and $25 output per million tokens, down from $15/$75 for the previous Opus. That’s still more expensive than GPT-5.1 ($1.25/$10) or Gemini 3 Pro ($2/$12), but the performance gap may justify the premium for some use cases.
Built for Agentic Workflows
Anthropic positions Opus 4.5 as “especially well-suited for code migration and code refactoring.” It’s designed for heavy-duty autonomous tasks where the model needs to handle ambiguity and reason about tradeoffs across multi-step workflows.
The tool search feature lets Opus 4.5 work with hundreds or thousands of tools dynamically, discovering and loading them on demand instead of jamming everything into the context window upfront. Thinking blocks automatically preserve reasoning continuity across multi-turn sessions. The 200K context window and 64K thinking budget (configurable to 128K) support long, complex coding sessions.
Internal testers at Anthropic report that tasks “near-impossible for Sonnet 4.5 just weeks ago are now within reach.” When pointed at complex, multi-system bugs, it “just gets it.”
The Market Reality
Eighty-two percent of developers now use AI coding tools daily or weekly. Forty-one percent of all code written globally is AI-generated or AI-assisted. Coding AI is a $4 billion market in 2025, up from $550 million, and it’s the largest single category of AI spending across the entire application layer.
But there’s a trust problem. While 91% of engineering organizations have adopted AI coding tools, 46% of developers actively distrust the accuracy of AI-generated code. Only 33% trust it. Positive sentiment has declined from over 70% in 2023-2024 to 60% in 2025.
A randomized controlled trial by METR found that experienced developers using AI tools took 19% longer to complete tasks than without AI, even though the developers believed they were 20% faster. The objective measurements contradicted their perceptions.
This suggests that model quality matters. If developers are going to rely on AI for nearly half their code, the difference between 77.9% and 80.9% on real-world problem-solving might be more significant than Simon Willison’s anecdote implies. Incremental improvements compound when you’re using these tools all day.
Should You Switch?
If you already have GitHub Copilot access at the right tier, trying Claude Opus 4.5 costs you nothing but a few clicks. It’s the current benchmark leader. Whether that translates to noticeably better code in your workflow is something you’ll need to test yourself.
The frontier is crowded. GPT-5.1 Codex Max, Gemini 3 Pro, and Claude Opus 4.5 are all excellent. The practical differences may not be dramatic for most tasks. But if you’re hitting edge cases where your current model struggles, the model that scores 80.9% instead of 77.9% might be the one that gets you unstuck.
Opus 4.5 is live. It’s fast. It’s in your IDE. And right now, it’s the best-performing AI coding model on the most widely recognized benchmark. That’s worth your attention.
