Opus 5.5 vs GPT-6 Astra: What Each Task Actually Costs on the API

A head-to-head API billing test found that Opus 5.5 and GPT-6 Astra's per-task costs diverged from their sticker prices, with Astra's listed API rate roughly 2.5 times higher than Opus 5.5's but its actual costs swinging both ways. On a website build, Astra cost $11.33 over 32 minutes versus Opus 5.5's $18.32 over 40 minutes, while on a 30-second video sizzle reel edited from roughly 105 gigabytes of raw footage, Opus 5.5 cost $10 over 31 minutes versus Astra's nearly $22 over 39 minutes. Both models ran on high effort settings, and the comparison used API billing as a stand-in for subscription costs, with cost data drawn from just two directly tested tasks.

Opus 5.5 vs GPT-6 Astra: What Each Task Actually Costs on the API Real dollar costs and run times for Opus 5.5 and GPT-6 Astra across identical tasks, from website builds to video edits, using actual API billing. What does it actually cost to run Opus 5.5 versus GPT-6 Astra on the same task? In a head-to-head test across identical prompts, Opus 5.5 consistently ran cheaper and often faster than GPT-6 Astra, even though Astra’s API pricing is listed at roughly 2.5 times the rate of Opus 5.5. On a website build, Opus cost $18.32 over 40 minutes versus Astra’s $11.33 over 32 minutes. On a video sizzle reel, Opus cost $10 over 31 minutes versus Astra’s nearly $22 over 39 minutes. Cost per task didn’t track cleanly with either the sticker price or the run time. TL;DR - Astra’s API rate runs about 2.5x higher than Opus 5.5’s, according to published API billing figures cited in testing, but that multiplier didn’t consistently show up in final task cost. - Actual per-task cost swung both directions : Astra came in cheaper on a website-building task $11.33 vs $18.32 but more expensive on a video-editing task nearly $22 vs $10 . - Run time and cost aren’t tightly linked : Astra finished the website task faster 32 minutes vs 40 but took longer and cost more on the video task 39 minutes vs 31 . - Effort settings matter : both models were tested on “high effort” mode, which raises token usage and cost compared to default settings, so real-world bills on lower effort levels would likely be smaller. - API pricing was used as a stand-in for subscription costs so the comparison wouldn’t depend on which subscription tier a $20/month plan versus a $200/month plan a given user happens to be on. - Cost data came from just two directly tested tasks in this comparison website generation and video editing , so it’s a snapshot, not a full statistical picture across every use case. Remy is new. The platform isn't. Remy is the latest expression of years of platform work. Not a hastily wrapped LLM. How was the pricing comparison actually run? The tests were run by sending the same prompt to both Opus 5.5 and GPT-6 Astra in their respective harnesses, then comparing the two outputs side by side. Both models were run on high effort settings, which is the mode that typically produces the most thorough and most expensive results a model can generate for a given task. Rather than track subscription costs, which vary wildly depending on plan tier, the comparison converted usage into equivalent API billing. That approach normalizes the comparison: whether someone is paying $20 a month or $200 a month for a wrapped product, the underlying API cost per task is the same baseline number, and that’s what got tracked and reported after each experiment. Two tasks had hard cost figures attached in this round of testing: building a branded product website from a prompt, and editing a 30-second sizzle reel from roughly 105 gigabytes of raw event footage. Both tasks were run through automated coding/editing harnesses a “vibe coding” style tool for the website, and a video editing tool for the reel , with both models given identical source material and instructions. Is Astra’s higher API price justified by faster or better output? Not consistently, based on the tasks tested. Astra’s listed API rate is around 2.5 times higher than Opus 5.5’s. If pricing tracked capability in a predictable way, you’d expect Astra to either finish faster, produce a better result, or both, often enough to justify the premium. That’s not what happened across these two tasks. On the website build, Astra was actually cheaper in total cost $11.33 vs $18.32 and faster 32 minutes vs 40 . But the judged output quality favored Opus, whose hero section and dark-mode aesthetic were described as feeling more premium and polished. So Astra was cheaper and quicker but rated lower on the subjective creative bar. On the video editing task, the pattern flipped. Astra took longer 39 minutes vs 31 and cost more almost $22 vs $10 , while also being judged as producing a less energetic, less well-synced edit compared to Opus’s version. In that task, Astra lost on every dimension: cost, speed, and quality. The takeaway from these two data points is that the 2.5x price multiplier on Astra’s API rate doesn’t map onto a 2.5x improvement in speed or output value. In one case it was cheaper and worse; in another it was more expensive and worse. Neither result gives a clean justification for the higher per-token rate based on these particular tasks. Why did run time and cost move in different directions? Run time and cost aren’t the same thing, because the two models likely handle token generation, tool calls, and internal reasoning steps differently, even under the same “high effort” label. A model that runs longer isn’t necessarily burning more expensive tokens the whole time, and a model that finishes fast isn’t automatically cheap if it’s using a pricier per-token rate. Other agents ship a demo. Remy ships an app. Real backend. Real database. Real auth. Real plumbing. Remy has it all. That’s part of why Astra could be both faster and cheaper on the website task despite carrying a higher headline API price. It’s also why the video task saw Astra run longer and cost more at the same time, compounding the higher per-token rate with a longer session. For anyone budgeting API spend, this is a practical reminder that sticker price per million tokens doesn’t directly predict what a real task will cost. The only reliable way to know is to run the actual workload and check the billed usage afterward, which is effectively what this comparison did. Does effort level change the cost picture? Yes, and it’s worth flagging clearly. Both models were run on “high effort,” which is typically the setting that maximizes reasoning depth and output thoroughness at the cost of more tokens and longer run times. Most API providers offer lower effort or reasoning tiers that trade some capability for significantly lower cost. That means the dollar figures in this comparison $10 to $22 per task represent something close to a ceiling for these particular workloads, not a floor. Someone running similar tasks on a default or low-effort setting should expect notably lower costs on both models, though the relative cost gap between Opus 5.5 and Astra would likely persist in some form since it stems from the underlying per-token pricing difference. Frequently Asked Questions Is GPT-6 Astra always more expensive to run than Opus 5.5? Not necessarily in total task cost. Astra’s API rate per token is higher about 2.5 times Opus 5.5’s , but in one tested task website generation Astra’s total bill came out lower because it finished faster. In another video editing , Astra was both slower and pricier. Total cost depends on how many tokens and how much time a task actually takes, not just the per-token rate. Why compare API pricing instead of subscription pricing? Subscription plans vary a lot, from around $20 a month to $200 a month depending on the tier, and don’t isolate the actual compute cost of a task. Converting usage to equivalent API billing gives a consistent, plan-independent number that reflects what the work actually costs regardless of which product wrapper someone is using. Does higher cost mean better output quality? Not in this comparison. Opus 5.5 was judged to produce better creative output in website design and video editing while frequently costing less than Astra. Astra’s higher price didn’t translate into consistently better or faster results across the tasks where cost was tracked. Would using a lower effort setting change these costs significantly? Likely yes. Both models were tested at high effort, which maximizes token usage and cost. Lower effort or lighter reasoning settings, available on most API tiers, would probably reduce the dollar figures substantially for both models, though the relative price gap between them would likely remain in some form. Which model is the better value based on this testing? Based on the two tasks with concrete cost data, Opus 5.5 came out ahead on value: it was rated as producing better output in both cases and was cheaper in one of the two tasks. Astra’s only advantage was lower cost and faster completion on the website task, though its output was still rated as less polished.