GPT-6 Astra vs Claude Opus 5: Which AI Is More Powerful?

OpenAI's GPT-6 Astra and Anthropic's Claude Opus 5 are, as of September 2026, each company's answer to the same question: how do you make a frontier-capable model that's actually practical to run at scale. GPT-6 Astra leads on raw benchmark scores and context window size. Claude Opus 5 leads on price-to-capability ratio and was built specifically to be Anthropic's everyday default rather than a showcase model.

This comparison is based on each company's own published benchmarks, documentation, and pricing pages — not independent side-by-side testing we ran ourselves. Where a claim comes from a vendor's own benchmark, we say so; we haven't run these models against each other on identical tasks, and we're not going to present invented test transcripts as if we had.

Quick Answer

Which is more powerful, GPT-6 Astra or Claude Opus 5? On OpenAI's own published benchmarks, GPT-6 Astra scores exceptionally high on hard reasoning tests — 97.6% on FrontierMath Tier 4 and 99.9% on ARC-AGI-3 — and offers a much larger context window (1.05 million tokens versus Opus 5's 200,000). Claude Opus 5 is priced roughly half of GPT-6 Astra ($5/$25 per million input/output tokens versus $10/$50) and is positioned by Anthropic as an efficient everyday model rather than a pure capability showcase. Neither company has published results from testing the two directly against each other, so "which is more powerful" depends partly on which vendor's benchmark you trust and what you're optimizing for: raw reasoning ceiling and context length (Astra) or cost-efficient everyday capability (Opus 5).

Key Takeaways

• GPT-6 Astra (released September 4, 2026) has a 1.05 million token context window — more than 5x Claude Opus 5's 200,000
• Claude Opus 5 (released July 24, 2026) costs about half as much per token as GPT-6 Astra
• Both models offer adjustable reasoning effort: GPT-6 Astra has 5 effort settings, Opus 5 has an "effort dial"
• GPT-6 Astra's knowledge cutoff is April 30, 2026; verify Opus 5's current cutoff directly with Anthropic before relying on either for very recent events
• This comparison is documentation-based, not from our own head-to-head testing — treat "winner" framing below as benchmark-sourced, not lab-verified

The Two Contenders

GPT-6 Astra — OpenAI

GPT-6 Astra is OpenAI's flagship model, released September 4, 2026, replacing the GPT-5.6 family (Luna, Sol, Terra) as OpenAI's top-tier option. OpenAI describes it as designed to use computers, browse the web, work across large collections of files, write and execute code, and continue complex tasks with less human guidance than earlier models needed.

Technical specifics OpenAI has published: a context window of roughly 1.05 million tokens with a maximum output of 128,000 tokens, five selectable reasoning-effort settings, support for tool calling and structured JSON outputs, and a knowledge cutoff of April 30, 2026. On OpenAI's own long-context evaluation (MRCR v2), Astra scored 96.3% against 73.8% for the previous GPT-5.6 Sol model — a meaningful jump specifically on tasks that require tracking information across very long inputs.

Claude Opus 5 — Anthropic

Claude Opus 5, released July 24, 2026, is positioned by Anthropic as its efficient everyday model — the default for Claude Max subscribers, aimed at enterprises, knowledge workers, and developers who want most of the capability of Anthropic's frontier Fable line without the price. On Anthropic's own CursorBench 3.2 evaluation at maximum effort, Opus 5 scores within roughly 0.5% of Claude Fable 5.1's peak result while costing about half as much per task, and it also leads on Frontier-Bench and GDPval-AA, two benchmarks Anthropic uses for software engineering and knowledge-work tasks respectively.

Opus 5 has a 200,000 token context window — smaller than GPT-6 Astra's, but still large enough to handle most professional documents, codebases, and long conversations without truncation. Its "effort dial" lets you trade some capability for lower token usage and cost on simpler requests, a similar idea to GPT-6 Astra's reasoning-effort settings.

Feature and Spec Comparison

Published Benchmark Comparison

These are each company's own reported scores on their own chosen evaluations — not a controlled, identical-task comparison between the two models, since OpenAI and Anthropic don't publish results on each other's benchmark suites.

GPT-6 Astra, per OpenAI: 97.6% on FrontierMath Tier 4 (a very hard mathematical reasoning benchmark), 99.9% on ARC-AGI-3 under OpenAI's provider adapter harness, 100% on ExploitBench, and 96.3% on OpenAI's MRCR v2 long-context test.

Claude Opus 5, per Anthropic: within about 0.5% of Fable 5.1's peak score on CursorBench 3.2 (a coding-focused benchmark) at maximum effort, with leading results on Frontier-Bench and GDPval-AA.

The honest takeaway: GPT-6 Astra's published numbers on hard reasoning and long-context tasks are extremely strong, and its context window is a genuine structural advantage for tasks involving very large documents or codebases. Claude Opus 5's benchmark story is less about topping every chart and more about matching near-frontier performance at roughly half the price — a different kind of claim that's harder to compare apples-to-apples against Astra's raw scores.

How We Compared These Models

This comparison is built from each company's own product pages, technical documentation, and published benchmark results, cross-checked against independent reporting on release dates and pricing. We have not run GPT-6 Astra and Claude Opus 5 against identical tasks ourselves, and we're not presenting fabricated test transcripts as if we had — a previous version of this article included invented head-to-head "test results" that we've removed for exactly that reason. Where a specific detail (like Opus 5's exact knowledge cutoff) wasn't independently confirmable from Anthropic's public materials at the time of writing, we've said so rather than guessing.

Which Model for Specific Use Cases

Very long documents or large codebases: GPT-6 Astra's 1.05 million token context window is the clearer fit when you need a model to hold an entire large codebase, a lengthy legal contract, or a full research corpus in context at once without chunking.

Cost-sensitive, high-volume use: Claude Opus 5's roughly half-price token cost, combined with near-frontier benchmark performance, makes it the more practical choice for applications making a large number of API calls where every token counts.

Coding assistants and agentic tools: Both are strong here — GPT-6 Astra's ExploitBench and reasoning scores and Opus 5's CursorBench 3.2 result both point to serious coding capability. For a dedicated comparison of coding-focused tools built on these models, see our Claude Code vs Cursor vs Codex comparison.

Students and researchers: For most academic work, either model's free-adjacent or entry-paid tier is more relevant than the flagship comparison here — see our best AI tools for students guide for the practical, budget-conscious picture.

General everyday assistant use: Most people don't need either flagship model for daily tasks. Our ChatGPT vs Claude vs Gemini comparison and best free AI assistants guide cover the free and mid-tier options that cover most everyday use without paying flagship API rates.

Pricing and How to Access

GPT-6 Astra: Available through the OpenAI API at $10 per million input tokens and $50 per million output tokens (2x input and 1.5x output above 272,000 input tokens in a single request; cached input is $1 per million tokens). Also accessible through ChatGPT's paid tiers — check OpenAI's current plan pages for which tier includes Astra access, since this has shifted across model releases before.

Claude Opus 5: Available through the Anthropic API at $5 per million input tokens and $25 per million output tokens, and set as the default model for Claude Max subscribers. Also available through Claude Pro, Team, and Enterprise plans, and through Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry.

Frequently Asked Questions

Is GPT-6 Astra better than Claude Opus 5?

On OpenAI's own published benchmarks, GPT-6 Astra scores very highly on hard reasoning and long-context tasks, and its context window is more than five times larger than Opus 5's. Claude Opus 5 costs about half as much per token and is designed as an efficient everyday model rather than a pure capability showcase. Neither company has published a direct head-to-head result, so "better" depends on whether you're optimizing for raw capability and context length or cost efficiency.

What happened to GPT-5.5 and the older Claude Opus?

Both have been superseded. OpenAI moved from GPT-5.5 through the GPT-5.6 family (Luna, Sol, Terra) to GPT-6 Astra, released September 4, 2026. Anthropic moved from Opus 4.8 to Opus 5, released July 24, 2026. An article or comparison referencing "GPT-5.5" or an unversioned "Claude Opus" today is comparing at least one generation behind the current models.

How much do GPT-6 Astra and Claude Opus 5 cost?

GPT-6 Astra is $10 per million input tokens and $50 per million output tokens via the API (with a surcharge above 272,000 input tokens in one request). Claude Opus 5 is $5 per million input tokens and $25 per million output tokens — about half of Astra's rate.

Which model has the bigger context window?

GPT-6 Astra, by a wide margin — roughly 1.05 million tokens versus Claude Opus 5's 200,000 tokens. This matters most for tasks involving very large documents, codebases, or datasets that need to stay in context at once.

Can I use both models?

Yes, and many developers and professionals do, choosing per task rather than committing to one vendor. Both are accessible through their respective APIs and through major cloud platforms (Amazon Bedrock, Google Cloud Vertex AI, Microsoft Foundry), which makes running both in the same application straightforward.

Which Model Should You Use?

If your work regularly involves very large inputs — full codebases, lengthy contracts, large research corpora — GPT-6 Astra's context window is a structural advantage that Opus 5 can't match regardless of benchmark scores. If you're optimizing for cost at volume, or want strong performance without paying frontier-model prices, Claude Opus 5's roughly half-price token cost and near-frontier benchmark results make it the more practical everyday choice.

Given how quickly both companies have shipped new versions in 2026 — Anthropic alone updated twice in the time this article covers — treat any specific benchmark number or price here as a snapshot, and check both companies' current pricing pages before making a purchasing decision based on cost.