# Anthropic's Claude Opus 5 Doubles Its Coding-Benchmark Score at Unchanged Pricing

Opus 5 scores 43.3% on Frontier-Bench versus Opus 4.8's 21.1% and comes within 0.5% of Claude Fable 5 on CursorBench at half the per-task cost.

- Published: 2026-08-02T05:44:51.872Z
- Canonical: https://polylog.news/ai/2026-08-02/anthropic-s-claude-opus-5-doubles-its-coding-benchmark-score
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [Anthropic](https://www.anthropic.com/news/claude-opus-5), [MarkTechPost](https://www.marktechpost.com/2026/07/24/meet-the-new-claude-opus-5-frontier-class-agentic-coding-and-computer-use-at-unchanged-opus-pricing/)

Anthropic [shipped Claude Opus 5](https://www.anthropic.com/news/claude-opus-5) on July 24, positioning it for long-running agents and professional coding work. On the company's published numbers, Opus 5 [scores 43.3% on Frontier-Bench](https://www.marktechpost.com/2026/07/24/meet-the-new-claude-opus-5-frontier-class-agentic-coding-and-computer-use-at-unchanged-opus-pricing/), more than double Opus 4.8's 21.1%, and at maximum effort on CursorBench 3.2 it comes within 0.5% of Claude Fable 5, the firm's top model, while costing roughly half as much per task.

Anthropic kept pricing flat at $5 and $25 per million input and output tokens, with a faster mode at about twice the price for roughly 2.5 times the speed. The model leads most of Anthropic's own benchmark suite, including GDPval-AA, OSWorld 2.0, and AutomationBench, and the company reports it scoring several times higher than the next model on ARC-AGI-3, a test of novel-problem solving.

These are vendor-reported figures on Anthropic-selected benchmarks, so the meaningful signal is the price-performance ratio rather than any single score. A model that reaches near-top-tier coding results at half the per-task cost of its top model shows how quickly the coding tier is being commoditized inside a single lab, which is what independent harness tests on real repositories will now test.

## What this means

The channel is coding capability per dollar. By holding Opus pricing flat while closing most of the gap to its own top model, Anthropic compresses the price-performance frontier for agentic coding, which pressures rivals to match on cost, not just capability. The exposed parties are labs whose coding-tier models cost more for similar output, and developers building on coding agents gain a cheaper high-capability option, provided independent harnesses confirm the benchmark differences on real codebases.

## What to watch

- Independent SWE-bench-style results on real repositories, which test whether the doubled benchmark score translates into fewer failed agent runs.
- Competing coding-tier releases and repricing from OpenAI, Google, and Chinese labs, which would show competition in the coding tier intensifying.