Claude Opus 5.5 vs GPT-6 Astra: We Tested the 40% Cheaper Claim

Anthropic launched Claude Opus 5.5 on September 22 with the kind of headline every AI team wants to hear: its new flagship costs 40% less to run than Opus 5. The rate card, however, appears to say something else. Input fell from $5 to $4 per million tokens. Output fell from $25 to $20. That is a 20% cut, not 40%.

The missing half of the claim is the interesting part. Anthropic says Opus 5.5 uses fewer tokens per task, and it cut the cache-read rate by 60%. Put those effects together and a long agent session can approach—or beat—the headline. Send the same one-shot prompt and the saving is exactly 20%.

Against OpenAI's GPT-6 Astra, the sticker-price gap is larger: Opus 5.5 is 60% cheaper at the same short-context token counts. But that still does not prove it is cheaper per completed task. The model that succeeds in one run can beat the model that needs three repairs, even with a higher token rate.

This guide separates the three questions the launch-day posts collapse into one: price per token, tokens per task and tasks that pass. It uses current API rates and four reproducible workloads—not a screenshot of a benchmark chart.

CalculatorAI is not affiliated with Anthropic or OpenAI. Prices were checked September 23, 2026 and can change. Anthropic's benchmark and efficiency figures are vendor-reported; the cost arithmetic below is ours.

The launch hookHow 20% per token becomes 40% per task

Claude Opus 5.5 costs $4 per million fresh input tokens and $20 per million output tokens. Opus 5 costs $5 and $25. At identical token counts, every uncached request is therefore 20% cheaper.

Anthropic's 40% figure is a typical-workload claim, not a tariff calculation. The company says the new model needs fewer tokens and fewer steps to finish work. In the simplest uncached case, a 20% lower rate combined with 25% fewer tokens produces a 40% lower bill:

That is plausible, but it is not automatic. Your prompt, tools, effort level, stopping conditions and evaluation determine whether the model actually uses 25% fewer tokens. A migration that keeps the same token counts gets the tariff saving and nothing more.

The rate cardOne launch, three different discounts

The release has no single discount. Fresh input, output and cache writes fell 20%; a five-minute cache read fell 60%; Fast mode doubles the new standard rates. Batch processing halves standard input and output.

The cache row matters disproportionately for coding and research agents. A system prompt, repository map, tool definitions and conversation prefix can be reused across many steps. Opus 5.5 bills those cache reads at one-twentieth of its fresh-input price; Opus 5 bills them at one-tenth. The new model is not merely cheaper—it changes which prompt segments are worth caching.

Our broader Claude API pricing guide explains the five-minute and one-hour write rates, while the OpenAI API pricing guide covers Astra's 272,000-token context boundary and processing tiers.

Four workloadsWhere the winner changes

The examples below use the same tokens for both models unless noted. This is intentionally conservative: it tests the published rate card without assuming that either vendor's model completes work in fewer steps.

One-shot work: the saving is 20%, full stop

An 80,000-token code audit with an 8,000-token answer costs $0.60 on Opus 5 and $0.48 on Opus 5.5. Nothing in that request benefits from a cache read and we held output constant. The new model is 20% cheaper.

This is the cleanest counterexample to treating “40%” as a universal discount. If your workload is one prompt, one response and no retries, budget from the rate card—not the launch headline.

Cached agents: the discount grows before efficiency gains

Our twelve-step coding session writes a 100,000-token stable prefix once, reads 1.1 million cached tokens over later turns, adds 120,000 fresh tokens and produces 36,000 output tokens. Opus 5.5 costs $1.92 versus about $2.68 on Opus 5: a 28.2% reduction at identical usage.

To reach a total 40% reduction in this particular mix, Opus 5.5 needs about 16.4% fewer billable tokens or equivalent work. That is a lower bar than the 25% required in the uncached example because the cache-read rate already did more of the work.

This is also why our AI Agent Cost Calculator separates fresh context, cached context and generated output. One blended “tokens per task” field hides the largest launch-day change.

Long context: OpenAI's threshold can dominate the comparison

GPT-6 Astra doubles input and cache rates when a prompt exceeds 272,000 input tokens and charges 1.5 times the output rate for the full request. Claude Opus 5.5 publishes one standard rate across its one-million-token context window.

For 400,000 input tokens and 20,000 output tokens, that produces $2.00 on Opus 5.5 and $9.50 on Astra. Opus is 78.9% cheaper at equal tokens. This is not evidence that it will produce the better answer; it is evidence that chopping or caching a long Astra prompt is a financial requirement, not a micro-optimization.

Batch: both discounts are real, neither proves quality

Five million input tokens and 500,000 output tokens cost $30 on standard Opus 5.5 or $15 through Anthropic's Batch API. At the corresponding published OpenAI rates, Astra costs $75 standard or $37.50 Batch.

Batch is the obvious choice for offline classification, extraction and nightly evaluation. It is irrelevant for an interactive coding agent that must return the next tool call now. “Cheapest” always needs a latency condition.

The benchmark trapCost per token is not cost per accepted result

Anthropic reports that Opus 5.5 leads several agentic coding and knowledge-work evaluations. Its launch page says the model beat Astra's reported FrontierCode score at default effort for about one-fifth of the cost per task, and roughly matched Astra on Terminal-Bench for about 40% of the cost. Those are notable results—but they are still vendor-reported comparisons with different harnesses and effort settings.

The useful metric inside your product is simpler:

Run a blind evaluation on your own repository, documents or support queue. Score correctness before style. Count the repair turns. A model that saves $0.60 but adds eight minutes of review did not save money.

The same principle appears in our ChatGPT vs Claude vs Gemini cost-per-task comparison: model tier usually moves the bill more than the logo, but quality gates decide whether a lower rate becomes a lower operating cost.

Migration warningOpus 5.5 is not a drop-in model-ID swap

The price is the easy part. Anthropic documents several behavior changes that can break an existing Opus 5 integration.

Opus 5.5 supports up to one million context tokens and 128,000 output tokens; adaptive thinking cannot be switched off. Fast mode is a first-party Claude API research preview at $8 input and $40 output per million—twice standard—not a free speed boost. The model is also available through AWS, Google Cloud and Microsoft Foundry, but Fast mode is not.

Decision ruleWho should switch today?

For an existing Opus 5 workload, Opus 5.5 is the obvious challenger: the base rate is lower and the cache rate is dramatically lower. “Obvious challenger” is not “automatic production replacement.” The migration changes and always-on thinking deserve an evaluation run.

For an Astra workload, route by task. Start with repeated long-context agents and offline batch jobs, where the price gap is structurally large. Keep Astra where your own evaluation shows a higher acceptance rate or fewer expensive failures. A multi-model router should escalate by measured difficulty, not by brand loyalty.

Where these numbers come from

Anthropic's September 22 announcement supplies the 40% typical-workload claim, the reported token-efficiency improvements and its benchmark comparisons. Claude Platform documentation supplies the $4/$20 standard rates, $5 five-minute and $8 one-hour cache writes, $0.20 cache reads, 50% Batch discount, $8/$40 Fast mode, context limits and migration changes.

OpenAI's API pricing page and GPT-6 Astra model page supply the $10/$50 standard rates, $1 cached input, $12.50 cache write and the higher price band beyond 272,000 input tokens.

Every worked number is reproduced in drafts/claude-opus-5-5-vs-gpt-6-astra-numbers.mjs. We did not run the proprietary models against a hidden benchmark and do not present Anthropic's evaluations as independent findings.

FAQFrequently asked questions

Is Claude Opus 5.5 really 40% cheaper than Opus 5? Anthropic reports about 40% lower cost on typical workloads. At identical uncached token counts, the published rate is 20% lower. The total can reach 40% if the model uses fewer tokens or if a cache-heavy workflow benefits from the 60% lower cache-read price.

Is Claude Opus 5.5 cheaper than GPT-6 Astra? At equal short-context token counts, yes: $4/$20 versus $10/$50 makes Opus 5.5 60% cheaper. In our cached agent it is 64.1% cheaper, and in the 400,000-token example it is 78.9% cheaper because Astra enters its long-context price band. Cost per accepted result can still differ.

Does Opus 5.5 beat GPT-6 Astra? Anthropic reports wins or near-parity on several coding and knowledge-work benchmarks at lower task cost. Treat those as vendor results. The relevant answer for a product comes from a blind evaluation using its own tasks, tools and pass criteria.

Should I use Opus 5.5 Fast mode? Only when latency has measurable value. Fast mode doubles standard token rates to $8/$40 and is available only on the first-party Claude API. Benchmark the time saved against the premium.

Can I disable thinking to cut output cost? No. Claude Opus 5.5 uses adaptive thinking and Anthropic says thinking cannot be disabled. Control depth with effort and task budgets, then measure output and thinking usage.

Next stepTest the headline on your own workload

Take 50 tasks from production, freeze the inputs and acceptance rubric, and run Opus 5, Opus 5.5 and GPT-6 Astra at documented effort settings. Record fresh input, cache writes, cache reads, output, retries and accepted results.

Put those totals into the AI Agent Cost Calculator. If Opus 5.5 cuts accepted-task cost by 40%, the headline is true for you. If it saves 20%, that is still a real price cut. The mistake is budgeting from either number before measuring the task.