Claude Opus 5.5 vs GPT-6 Astra: 40% of the list price, but dearer per task at max effort

Claude Opus 5.5 lists at $4 per million input tokens and $20 per million output, 40% of GPT-6 Astra's $10 and $50. Which one costs less per task depends on the effort setting. On Artificial Analysis's Intelligence Index v4.3.2, Opus 5.5 costs more per task than Astra at max effort ($5.98 against $3.26) and less at medium ($1.34 against $1.54), and it scores higher at both.

The benchmark tables need the same care. Anthropic's launch table sets Opus 5.5 at xhigh against Astra at high on Terminal-Bench 4.0, each lab's highest reported score, and every Astra figure in it comes from OpenAI or a third party, never from a run by Anthropic. On Artificial Analysis's own harness the two score the same, 59.6%.

We ran neither model, and every figure below names its publisher and setting. Anthropic's documents, OpenAI's model page for Astra and six outside evaluators were read on 23 September 2026; OpenAI's full rate card and safety overview are from our reading of 3 and 5 September; the 23 user comments were posted on 22 and 23 September. Each model's full story is in its own review, and this page covers where the two differ.

Which is better, Claude Opus 5.5 or GPT-6 Astra?

For coding agents and knowledge work run at medium or high effort, Claude Opus 5.5 is the better value on the published evidence. At those settings Artificial Analysis scores it above GPT-6 Astra (51.24 against 49.57 at medium, 53.58 against 50.92 at high) for a similar cost per index task ($1.34 against $1.54, and $1.82 against $1.73). GPT-6 Astra is the better pick when a job needs max effort and cost per task decides it, and for business automation of the kind Zapier's AutomationBench measures.

Three facts drive the split. Opus 5.5 costs 40% of Astra's list price and a fifth of its cache-read price, and Astra reprices a whole request once input passes 272,000 tokens. But at max effort Artificial Analysis measured Opus 5.5 writing about 119,000 output tokens per index task against about 27,000 for Astra, so at that setting the lower rate buys fewer tasks.

The split rests mostly on one publisher's composite of ten evaluations, which can hide the single evaluation your workload depends on. Where a benchmark below matches your work, that row should outweigh our summary.

Is Claude Opus 5.5 cheaper than GPT-6 Astra?

Per token, yes. Claude Opus 5.5 costs 40% of GPT-6 Astra's price on input and output ($4 and $20 against $10 and $50 per million tokens), 40% on cache writes ($5 against $12.50) and one fifth on cache reads ($0.20 against $1.00), our division of both vendors' rates as read on 23 September 2026. The full cards, with every mode and multiplier, are in the Opus 5.5 rate card in our review and the Astra rate card in our review.

The 40% survives the pricing modes. Both vendors halve their rates for batch work and double them for fast mode, so Opus 5.5 stays at 40% of Astra in each: $2 and $10 against $5 and $25 in batch, $8 and $40 against $20 and $100 in fast mode, the Astra figures and the batch figures being our arithmetic from each vendor's stated multiplier. Regional processing: Anthropic charges 1.1x for US-only inference, and OpenAI's pricing page, read 5 September, charged a 10% uplift on data-residency endpoints for eligible models, a list we have not checked Astra against.

The cache-read ratio is the one that moves real bills. Anthropic says cache reads "make up the majority of agentic and coding work costs", and both vendors set cache writes at 1.25 times their own input rate, so the write gap stays at 40% while the read gap widens to a fifth. An agent that resends a long cached context every turn pays Astra five times what it pays Opus 5.5 for that context. The rate is still only half the bill; the other half is how many tokens each model spends on a task, covered below.

What happens to GPT-6 Astra pricing above 272K tokens?

Above 272,000 input tokens, GPT-6 Astra bills the entire request, the first 272,000 tokens included, at double its input and cache rates and one and a half times its output rate. Head to head, that cuts Claude Opus 5.5's share of the bill from about 35% to about 20% on a mostly cached prompt, because the Anthropic pricing page we read prints no long-context surcharge line. The exact wording of OpenAI's rule is quoted in our GPT-6 Astra review.

Three worked examples show where the line falls. Each carries 20,000 new input tokens with the rest of the prompt read from cache, and 10,000 output tokens.

Prompt size	Claude Opus 5.5	GPT-6 Astra	Opus 5.5 as a share of Astra
271,000 tokens	$0.330	$0.951	35%
273,000 tokens	$0.331	$1.656	20%
300,000 tokens	$0.336	$1.71	20%

Our arithmetic from each vendor's published rates, read 23 September 2026. It assumes the cache was written by an earlier call and is still live, and leaves out cache writes and tool fees. Opus 5.5 is priced at list with no long-context surcharge, which is what the page we read shows.

Adding 2,000 tokens to the prompt raises Astra's bill by 74% and Opus 5.5's by less than a tenth of a cent, and the dollar gap between the two more than doubles, from $0.621 to $1.325, all our arithmetic. Below the line Opus 5.5 costs about a third of Astra on this kind of request; above it, about a fifth. On our reading of OpenAI's fast-mode multiplier, which applies to "the applicable rates", fast mode stacks on top and prices Astra's output over the line at $150 per million.

One caveat bounds all of this. The Claude pricing page we read links to a detailed pricing page we did not open, and Opus 5.5 also has a 1M-token window. If a long-context rule for Opus 5.5 sits on that page, the 20% rises. For prompts that carry whole repositories or document sets, count input tokens before a call goes to Astra.

Which costs less per task, Claude Opus 5.5 or GPT-6 Astra?

It depends on the effort setting. On Artificial Analysis's Intelligence Index v4.3.2, Claude Opus 5.5 costs more per index task than GPT-6 Astra at max ($5.98 against $3.26) and at xhigh ($3.46 against $2.31), about the same at high ($1.82 against $1.73), and less at medium ($1.34 against $1.54) and low ($0.55 against $0.82). Opus 5.5 scores higher at every setting except low.

Effort setting	Opus 5.5 index score	Opus 5.5 cost per index task	Astra index score	Astra cost per index task
max	57.62	$5.98	52.67	$3.26
xhigh	55.99	$3.46	52.39	$2.31
high	53.58	$1.82	50.92	$1.73
medium	51.24	$1.34	49.57	$1.54
low	42.31	$0.55	45.78	$0.82

Artificial Analysis Intelligence Index v4.3.2, read 23 September 2026. Unrounded scores and the Astra rows come from the data behind the charts on the publisher's Opus 5.5 page, a v4.3.2 page, which displays Opus 5.5 as 58, 56, 54, 51 and 42. Opus 5.5 entries run with Anthropic's default fallback enabled.

Token count explains the order. The publisher's launch article: "Opus 5.5 (max) uses ~119k output tokens per Intelligence Index task, against ~73k for Opus 5 (max), ~78k for Fable 5.1 (max) and ~27k for GPT-6 Astra (max)". At max, Opus 5.5 writes about 4.4 times Astra's output at 40% of Astra's output rate, our arithmetic, and the tokens win. The cost figures also fold in each model's typical cache-hit rate, which the publisher says it measures live.

Which row applies depends on how you run the model. Anthropic gives Opus 5.5's default effort as medium, the row where it is both cheaper and higher-scoring. OpenAI's model page names the same five settings for Astra, "reasoning.effort supports low, medium, high, xhigh, and max.", and states no default.

Two cautions. Our Astra review of 6 September printed Astra at 55 at max on index v4.2, a different version that cannot be set against 52.67. And cost per task varies by benchmark: on Zapier's AutomationBench at max, Opus 5.5 costs $1.28 per task and Astra $1.73.

Is Claude Opus 5.5 really a fifth of GPT-6 Astra's cost?

That is Anthropic's claim for particular benchmarks at particular settings, and no outside cost figure confirms it; on Artificial Analysis's full index the nearest pair is 41%. On that index, Claude Opus 5.5 at medium scores 51.24 against GPT-6 Astra at max on 52.67, at 41% of Astra's cost per task, our division. Anthropic's GDPval-AA line, "At default effort (medium), Opus 5.5 beats GPT-6 Astra at max effort for about a fifth of the cost per task.", holds on score in the publisher's data, 1576 against 1542 Elo.

What Anthropic says	Settings it names	What the outside data shows
Beats Astra on GDPval-AA for about a fifth of the cost per task	Opus 5.5 medium, Astra max	Score holds, 1576 against 1542 Elo. No GDPval-only cost is published
Matches Astra on Terminal-Bench 4.0 at about 40% of the cost	None	Level at 59.6% only with Opus 5.5 at xhigh or max; at medium it scores 52.5%
Beats Astra's best FrontierCode score at roughly 20% of the cost per task	Opus 5.5 medium	Cognition's result files carry token counts and no cost, per Anthropic's card, so the ratio is Anthropic's calculation

Anthropic's announcement and system card (p. 176); Artificial Analysis's page data for both models. All read 23 September 2026.

The Terminal-Bench line, "It matches GPT-6 Astra at about 40% of the cost.", names no setting. The match needs Opus 5.5 at xhigh or max, where Artificial Analysis's composite cost per task favours Astra, and no Terminal-Bench-only cost is published to settle the 40%.

Claude Opus 5.5 vs GPT-6 Astra benchmarks

On Artificial Analysis's own Terminal-Bench 4.0 run, Claude Opus 5.5 and GPT-6 Astra are level at 59.6%, while Anthropic's launch table shows 66.4% against 57.9%. The launch table pairs Anthropic's run of Opus 5.5 at xhigh with OpenAI's own report of Astra at high; Artificial Analysis ran both on one harness, mini-swe-agent, with three repeats over 66 tasks. Across the other benchmarks where one publisher has both, Opus 5.5 leads on ARC-AGI-2 at high, Artificial Analysis's index, GDPval-AA and Humanity's Last Exam, and Astra leads on Zapier's AutomationBench and on ARC-AGI-2 at max.

The publisher's words are that Opus 5.5 "scores 59.6%, level with the leader GPT-6 Astra (xhigh)", Opus 5.5 reaching it at both max and xhigh. Anthropic's footnote gives its own row's settings: "Terminal-Bench 4.0 results are reported for Claude Opus 5.5 at xhigh effort and GPT-6 Astra at high effort, as reported by OpenAI". The card says Astra sits at high because "in their reporting max effort fared slightly lower than high, so we picked their highest number" (p. 178), and Opus 5.5 at max scored 64.8%, within noise of xhigh. So the 8.5-point gap, our subtraction, compares each lab's best reported number from separate runs, Anthropic's in Claude Code and OpenAI's in a setup the card does not describe, and Anthropic does not present it as a matched run. Its run also had safeguards on, with a fallback model answering 2.5% of requests and touching 10% of trials.

Benchmark	Setting	Who ran it	Claude Opus 5.5	GPT-6 Astra
Terminal-Bench 4.0	Opus 5.5 max and xhigh, Astra xhigh	Artificial Analysis	59.6%	59.6%
Terminal-Bench 4.0	Opus 5.5 xhigh, Astra high	Anthropic; OpenAI's report for Astra	66.4%	57.9%
Intelligence Index v4.3.2	max, both	Artificial Analysis	57.62	52.67
GDPval-AA v2.1	max, both	Artificial Analysis	1846 Elo	1542 Elo
Humanity's Last Exam	max, both	Artificial Analysis	61.4%	54.7%
AutomationBench v1.0.6	max, both	Zapier	40.0%	41.4%
Terminal-Bench-Science 0.1	max, both	Anthropic; OpenAI's report for Astra	58.7%	64.6%
FrontierCode v1.1 (Main)	each at its best; Opus 5.5 at medium	Cognition	54.6%	53.3%
FrontierSWE v2	max, both	Proximal, via Anthropic's card	62.3%	65.5%
ARC-AGI-1, Semi-Private	high, both	ARC Prize	98.5%	98.5%
ARC-AGI-2, Semi-Private	high / max	ARC Prize	93.3% / 91.7%	92.1% / 95.0%

Independent rows read at source on 23 September 2026, some values from the data behind the publishers' pages; vendor rows from Anthropic's announcement and system card (pp. 174 to 179). OpenAI's two figures are not checked against OpenAI's own documents.

None of the Astra cells in Anthropic's table is a run by Anthropic. The card's caption says competitor figures come from each developer's published system cards or benchmark leaderboards, and for FrontierCode it says "Cognition ran the evaluation for every model shown and reported the results", with Claude models in Claude Code and GPT models in Codex CLI. The same table prints Humanity's Last Exam with tools at 67.7% against 57.2%, with no effort stated for Opus 5.5 and no specific source for the Astra cell; the Artificial Analysis row above is the like-for-like one.

Is Claude Opus 5.5 on ARC-AGI-3 or LMArena?

Not yet. As of 23 September 2026 ARC Prize lists no ARC-AGI-3 result for Claude Opus 5.5 at any setting, so GPT-6 Astra's ARC-AGI-3 scores have nothing to be compared against. LMArena lists Opus 5.5 on none of its boards, so Astra's first place on the WebDev board is a lead over other models and not over Opus 5.5. Epoch AI's Capability Index and Artificial Analysis's Coding Agent Index likewise carry Astra and not Opus 5.5. Astra's own results on those boards are in our Astra review, linked above. An empty row one day after launch is no evidence against the model.

Where does GPT-6 Astra beat Claude Opus 5.5?

GPT-6 Astra is ahead on five published measures: Zapier's AutomationBench at max (41.4% against 40.0%), Terminal-Bench-Science in Anthropic's own table (64.6% against 58.7%, Astra's figure as reported by OpenAI), Proximal's FrontierSWE v2 at max (65.5% against 62.3%), ARC-AGI-2 at max (95.0% against 91.7%) and Artificial Analysis's index at low effort (45.78 against 42.31). It also writes far fewer output tokens per task at max effort.

Business automation across apps is the clearest case against the cheaper model. Zapier scores each task's final state against fixed criteria, and its 1.4-point gap comes with no published error margin. Anthropic says Zapier ran Opus 5.5 "without fallback models, so safeguard interventions were considered failures", which it says lowered the score; Zapier's page does not say. Opus 5.5 at max does lead Zapier's Sales domain at 42.74% and ties Astra in Operations at 62.0%.

On Terminal-Bench-Science Astra's lead is 5.9 points, our subtraction, against a standard error the card gives as ±4.8 points for Opus 5.5. At low effort Astra scores 45.78 against 42.31 on Artificial Analysis's index for 27 cents more per task. And at max, where Opus 5.5 writes about 4.4 times as many output tokens, Astra's cost per index task is 55% of Opus 5.5's, our division, for a score about five points lower.

Which is better for coding, Claude Opus 5.5 or GPT-6 Astra?

Neither leads every coding measure. Claude Opus 5.5 leads Cognition's FrontierCode (54.6% at medium against Astra's best of 53.3%) and ties GPT-6 Astra at 59.6% on Artificial Analysis's Terminal-Bench 4.0 run; Astra leads Terminal-Bench-Science and Proximal's FrontierSWE v2. At 40% of the list price, a tie or a narrow gap favours Opus 5.5 on cost, except at xhigh and max effort, where Artificial Analysis's per-task figures favour Astra.

The results divide by kind of work. FrontierCode grades whether an agent's change would be merged without edits and penalises out-of-scope changes, per the card, and Opus 5.5 scores best there at medium, its default. FrontierSWE v2 and Terminal-Bench-Science are longer agentic tasks, and Astra leads both. The first-day user reports lean further to Opus 5.5, as the user reports below show, and none of them replaces running both models on your own repository.

Claude Opus 5.5 vs GPT-6 Astra context window

GPT-6 Astra has a 1,050,000-token context window and Claude Opus 5.5 a 1M-token window; Astra caps output at 128,000 tokens and Anthropic lists Opus 5.5 at 128K. The practical difference is price: Astra bills at its long-context rates once input passes 272,000 tokens, and the Anthropic pricing page we read prints no such threshold.

Both take text and image input, return text and expose the same five effort settings. Anthropic gives Opus 5.5's default effort as medium and its reliable knowledge cutoff as June 2026, with thinking that cannot be switched off in the API; OpenAI gives Astra's cutoff as 30 April 2026 and no default effort. On long-document reasoning, Artificial Analysis's AA-LCR has Opus 5.5 at 84.7% at max in its page data and no Astra figure in our record, and the launch article says Opus 5.5 "remains behind on CritPt, AA-LCR, and GDP.pdf" without naming the leader.

What do users say about Claude Opus 5.5 vs GPT-6 Astra?

Most first-day reports that set the two side by side favour Claude Opus 5.5 on coding and on subscription quota, and they disagree about token use. We link 23 comments from 22 accounts on Reddit and Hacker News, posted on 22 and 23 September 2026. None describes GPT-6 Astra winning a concrete coding task, and one reports Astra using a third of Opus 5.5's output tokens. These are self-selected comments from one launch day, mostly about subscription plans, and they show where the argument sits without settling it.

Three describe moving back to Claude after a spell on Astra, and two more lean that way. Frumbleabumb, 22 September 2026: "But opus 5.5 is great. Token usage is low, and I get the typical high context reasoning you expect out of Claude I just can't get with Astra." ArcaneMoose, the same day, had let a two-year Claude subscription lapse for Astra a day before the launch. impulser_, 22 September 2026: "Usage is actually Claude now because of Opus 5.5". schipperai, 22 September 2026, found Astra "wasn't as good of an upgrade from Sol when it comes to coding and orchestration" and called Opus 5.5 "Fable-level performance that's cheaper and faster, and communicates plainly and briefly." qkamikaze, 22 September 2026: "I feel like Opus 5.5 is almost comparable to Astra, for a fraction of Astra's prices."

Most of the reports with a concrete coding task favour Opus 5.5. Soft-Bus-5880, 22 September 2026: "I spent hours wrestling with Astra without getting anywhere, and Opus just nailed the entire thing in a single prompt". Reasonable-Sign8458, 22 September 2026, who pays for both, re-ran code Astra had written: "Ran it with Opus 5.5 today and it fixed 98 bugs." A later comment on 23 September put the run at "3 hours and 38 minutes". roflc0ptic, 23 September 2026, back-testing against pull-request comments: "About $24 for 10 PRs. I was surprised how much worse Astra did on correctness; I stopped testing with it." senko, 22 September 2026: "Opus 5.5 is neck-and-neck with Fable 5.1 and Astra 6 in my vibe-coding tests". dondiegorivera, 22 September 2026, who uses Astra daily, wrote that "the new Opus feels like a phase shift." One found both wanting: TheVoyant, 22 September 2026, had Astra fail and revert three tasks at 64% of a $100 plan's usage, while Opus 5.5, at 43% and hitting its five-hour limit almost at once, "has done the task wrong three times."

Users split on cost per task, and two of them read the same Artificial Analysis table. Wsz2020, 22 September 2026, reproduced rows including "Claude Opus 5.5 (high) | 53.6 | $1.82" and "GPT-6 Astra (high) | 50.9 | $1.73", which match the figures above. PrinceRufusFastcar, 22 September 2026: "Certainly Opus 5.5 at 'max effort' is very expensive, but Opus 5.5 at 'high' is both a lot cheaper than Astra and scoring higher." The score half matches the data; the cost half holds against Astra at xhigh or max, and not against Astra at high, where the publisher has $1.82 against $1.73. Roland31415, 23 September 2026, wrote "30% cheaper than Astra. 75% cheaper than Opus 5.", a figure we could not match to any same-setting pair in that table; the nearest, low effort, is 33% cheaper and scores lower. ShadyShroomz, 22 September 2026, found Opus "lower cost per task in my personal benchmark, and better performance", while granting Astra a slight edge at the top tier.

On quota and tokens the reports split. this_user, 22 September 2026: "Astra is barely usable even on the $100 plan." and "Opus is at least actually usable even on the small plan." kuatecno, 23 September 2026: "Astra was wasting tokens and not following my goals.", though "I might be back with astra in a couple days". Against both, user43928, 22 September 2026, wrote that Astra "uses a third of the output tokens of Opus 5.5, Fable 5.1, or Opus 5. 17k for Astra xhigh vs 61-66k." Artificial Analysis's counts point the same way, about 27,000 against about 119,000 at max. A subscription quota and an API token count are different measures, and these comments mix the two.

Some drew the line by workload. ptj66, 22 September 2026: "If you code Opus 5.5 will be outstanding." and "If you are doing knowledge work, research or just regular office stuff Astra and the new Sol Models might still be the better deal for you." LocoMod, 23 September 2026, opened with "Astra is an incredible model." before praising Opus 5.5's speed. Majinvegito123, 23 September 2026, called Opus 5.5 an "incremental improvement for huge cost savings" and not the "Astra killer" some had hoped for.

Claude Opus 5.5 vs GPT-6 Astra safety

Neither lab compares the two models on safety in what we read, and no outside evaluator we read has done so, so there is no ranking to give. What each lab reports about its own model differs in kind: Anthropic ships Opus 5.5 with classifiers that block some cyber, biology and frontier-AI requests and can hand them to older models, and OpenAI classes Astra as its first model at the Critical level of cybersecurity capability.

For Claude Opus 5.5, blocked cyber requests fall back to Claude Opus 4.8, and blocked biology and frontier-LLM requests to Claude Opus 5. That is automatic in Anthropic's apps; on the API, per the system card, "the developer must opt in to automatic fallbacks" (p. 48). Some Opus 5.5 benchmark scores above therefore include answers another model finished. The card also reports a regression on instructions planted in text a user pastes into their own prompt, about 2% of attempts at default effort and about 7.4% at max (p. 126). TuxSH, 22 September 2026, found Opus 5.5 often made useless by its cyber guardrails and wrote that they are worse than Astra's. The detail is in our Opus 5.5 review.

For GPT-6 Astra, OpenAI's safety overview states: "Astra is our first model to reach the Critical level of cybersecurity capability under our Preparedness Framework." The same document says "GPT-6 Astra's monitorability has decreased relative to GPT-5.6 Sol." We read that overview on 3 September and have read two sections of Astra's system card. Who OpenAI decided may use that capability is the subject of our analysis of the Critical cyber classification, and our Astra review has the rest. Our own writing workflow runs on Anthropic models, and the disclosure at the foot of this page says what that means for the comparison above.

What has changed since GPT-6 Astra launched?

GPT-6 Astra's prices have not moved; its outside scores have. OpenAI's model page on 23 September 2026 prints the same $10 and $50, $1.00 cached input, $12.50 cache writes and 272,000-token rule we read on 5 September.

• 3 September 2026: OpenAI releases GPT-6 Astra, and ARC Prize publishes its ARC-AGI-3 analysis of it the same day.
• 6 September 2026: our Astra review reads Artificial Analysis index v4.2 (Astra 55 at max), LMArena WebDev (Astra 1797, Fable 5.1 1762) and Epoch AI's model page (Capability Index 169).
• 22 September 2026: Anthropic releases Claude Opus 5.5 at $4 and $20, and Artificial Analysis and METR publish on it the same day. LMArena's Code board, dated that day, has Astra first at 1793 and no Opus 5.5 entry.
• 23 September 2026: Artificial Analysis's v4.3.2 data puts Astra at 52.67 at max. Epoch AI's data file gives Astra 166.6; we have not established whether that revises the 169 on its model page or is a separate figure.

Still open on the day of publication: Opus 5.5 results on LMArena, Epoch AI, ARC-AGI-3 and the Coding Agent Index; Astra's default effort; OpenAI's own documents behind its Terminal-Bench figures; and whether Anthropic's detailed pricing page carries a long-context rule. We will re-read both rate cards and each evaluator at least monthly, sooner when any of them publishes on either model, and date every change on this page.