GPT-6 Astra vs Claude Opus 5.5: $10 vs $4 per million input tokens

GPT-6 Astra vs Claude Opus 5.5 is a choice between OpenAI's top model and Anthropic's recommended default, and the price gap is large. Astra costs $10 per million input tokens and $50 per million output tokens, while Opus 5.5 costs $4 and $20. On Artificial Analysis's Intelligence Index, Opus 5.5 scored 58 and Astra 57, as read on November 2, 2026.

That makes Opus 5.5 60% cheaper per token and one point ahead on that one independent index. Astra's edge is on the page, not in the scores: it is OpenAI's top tier, and the question is whether your work needs it. This comparison is based on the products' docs and published results. We did not run either model ourselves.

GPT-6 Astra vs Claude Opus 5.5 at a glance

Prices are per million tokens, as of November 2, 2026, from OpenAI's GPT-6 Astra model page and pricing page, and Anthropic's models overview and pricing page. Independent numbers come from Artificial Analysis, read on November 2, 2026, for Astra and Opus 5.5.

What each company says the model is for

OpenAI's changelog calls Astra its most capable model, "built for the hardest end-to-end work." It lists reasoning, coding, computer use, research and document creation. OpenAI released it on September 3. Its newer GPT-6.1 Sol, released September 29, targets complex coding at a lower cost than Astra. Our Sol vs Terra comparison covers that tier.

Anthropic's models overview tells readers to start with Opus 5.5 for most workloads. It describes the model as built for long-running agentic coding and knowledge work. It points to Claude Fable 5.1, priced at $10 and $50 like Astra, for the hardest reasoning and long-horizon agent work. Our Opus 5.5 vs Fable 5.1 comparison covers that step up.

So the closest match to Astra in Anthropic's lineup by price is Fable 5.1, not Opus 5.5. Opus 5.5 is the model people compare because it is the default.

Price: Opus 5.5 is 60% cheaper per token

Opus 5.5 costs 60% less than Astra on both input and output. Cached input shows a bigger gap: $0.20 against $1, because Anthropic charges 5% of the input price for a cache hit on Opus 5.5.

Long prompts widen it further. OpenAI bills any request over 272,000 input tokens at twice the input and cache rates and 1.5 times the output rate for the whole request, so Astra goes to $20 and $75. Anthropic says the full 1M window on Opus 5.5 is billed at the standard rate.

A request with 50,000 input tokens and 15,000 output tokens costs $1.25 on Astra and $0.50 on Opus 5.5 at list prices. That is our arithmetic from the published rates.

Both vendors halve the price for batch jobs. Both also sell a faster mode at a premium: OpenAI's Fast mode is twice the standard rate, and Anthropic lists Opus 5.5 fast mode at $8 and $40.

What independent tests show

On the Artificial Analysis Intelligence Index, Opus 5.5 scored 58, second of 59 models listed on its page, and Astra scored 57, fifth of 59. One point is a small gap, and we would not call it a win. Artificial Analysis's own page names the Opus entry "max with fallback," so the number reflects a high reasoning setting.

The cost to run the index points the other way. Artificial Analysis lists $6.24 per index task for Astra and $10.04 for Opus 5.5. Opus costs less per token but used more tokens to finish the same tasks, which is why the per-task bill is higher. Its blended price per million tokens is $2.94 for Opus 5.5 and $7.70 for Astra, but the per-task figure is the closer guide to a real bill on reasoning-heavy work.

Speed favors Opus 5.5 at 95.5 tokens per second, against 70.6 for Astra, as measured by Artificial Analysis. Anthropic's own docs label Opus 5.5's latency "moderate."

Neither lab's own benchmark claims are used here, because the two companies run different tests. Check Terminal-Bench or SWE-bench for coding results measured the same way on both, and test on your own tasks.

Which one to pick

Pick Opus 5.5 first if you want the lower list price, the flat price over a long context and the faster output. Pick Astra if your tests show it solving tasks Opus 5.5 does not, or if your stack already runs on OpenAI's Responses API, which Astra needs for tool calling. Astra also does not accept a none reasoning effort, custom temperature or top_p, which matters if you are migrating older code.

Neither model is a safe default for every job. The independent index puts them within a point, so the deciding numbers are your own: cost per finished task and the share of tasks done right.

What we don't know

We found no head-to-head test of the two models run by an independent group on coding agents or computer use that we could read. Artificial Analysis's index is one blended score. Rankings and prices move often, so check the vendor pages before you commit.