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Build Widely confirmed17 publishers 3 min read Published Updated

Opus 5.5 matched Opus 5's puzzle answers for up to 69 percent less at its lower default effort

Opus 5.5 matched Opus 5 on two reasoning puzzles in The New Stack's tests at 43 to 69 percent lower cost. Both ran at default effort, medium on the new model and high on the old, so the saving a team sees depends on the effort level it pins.

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Illustration accompanying Opus 5.5 matched Opus 5's puzzle answers for up to 69 percent less at its lower default effort
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What happened

  • Anthropic cut Opus 5.5's API price to $4 per million input tokens and $20 per million output tokens, from $5 and $25 on Opus 5.
  • The New Stack ran Opus 5 and Opus 5.5 once each on three reasoning problems through the API, with identical prompts and default effort.
  • Anthropic's prompting guide sets Opus 5.5's default effort to medium, against high on Opus 5, and tells developers to test several levels on their own evals.

Why it matters

  • Who has to decide decision Teams that swap model IDs without setting effort drop from high to medium effort, so pinning effort and rerunning their own evals becomes the first migration step.
  • What it costs cost On jobs that run to the token cap, the saving shrinks to the 20% list-price cut, so the larger savings apply only to problems the model actually finishes.
  • Who's exposed exposure Harnesses that only handle token exhaustion now need a separate branch for refusals that arrive after long, token-heavy reasoning runs.

Anthropic's 40% claim [2] has two parts, and they behave differently. The price part is fixed at 20% on every call [11]. The token part varies by problem, and The New Stack's writer notes it has to supply the rest of the claim [11]. Thinking tokens are billed as output [10], so a model that reasons longer pays the $20 rate for it [1]. Cache pricing fell further, to $0.20, 60% lower according to the LessWrong review [6].

Across these three problems the token part ranged widely. On the logic grid Opus 5.5 wrote 7,573 output tokens to Opus 5's 10,621 [12], about 29% fewer [18]. On the stone game it wrote 28,740 to 74,981 [13]. At a 48,000-token cap on the orderings problem, both models thought until the cap and never replied, costing $0.96 and $1.20 [14]. That gap is exactly 20%, the list-price cut, because both runs billed the same 48,000 tokens [19]. Opus 5.5 was faster at giving up, too: 489 seconds to 553 [14].

Put the test setup next to Anthropic's guide and the comparison was Opus 5.5 at medium effort against Opus 5 at high [3][8][17]. A team that swaps the model ID and changes nothing else gets the same pairing. So the test is a fair picture of migration and a weaker one of the model. The lower default is deliberate. Anthropic's guide says that at medium, Opus 5.5 matched or beat Opus 5 at high on multistep coding work, in fewer steps and with fewer tokens [9]. On the grid and the stone game, the answers held at medium [12][13].

Effort also bounds the saving. The LessWrong review, discussing Artificial Analysis results, says that tested on max, Opus 5.5 "uses so many tokens it is slightly more expensive than Opus 5" [4]. The same review reports Artificial Analysis putting Opus 5.5 in the overall intelligence lead at 58 [5].

With the cap raised to 128,000 tokens, Opus 5 used all of it over more than 25 minutes and cost $3.20 [7]. Opus 5.5 ran 19 minutes and 112,733 tokens before the API returned a refusal with no text [7]. The writer judged it most likely a safety-filter mistake, since the prompt only asks for a count of job orderings [20]. At the list output rate those tokens come to about $2.25 [16]; the article does not say what the call was billed. For a harness, this is a separate failure path from running out of tokens. Anthropic's guide has a section for requests that return stop_reason "refusal" [21].

The reasoning evidence is thin in both directions: three problems, one run each [3]. The hard problem separated neither model. Its third count, 159,019, is reachable by a program that checks every ordering, and neither model could run code [15]. For these numbers to transfer, a workload has to look like the grid and the stone game: bounded problems that finish inside the budget, run at medium effort. In my view that describes most cost-sensitive work. I would move it with effort pinned explicitly and a refusal handler in place. For the hardest jobs, Opus 5 was no safer here: it failed the same problem at a higher price [7].

What to watch

  • A rerun of The New Stack's three problems with both models pinned to the same effort level would separate the model's gains from the default change.
  • Whether Anthropic bills refused calls like the 112,733-token orderings run, and whether it adjusts the safeguard that flagged a harmless counting prompt.
  • A repeat of the job-ordering problem with code execution enabled, the route The New Stack's writer says can reach the 159,019 count.

Clarity's read

What the record supports and how the coverage leans. The claims behind it follow.

Reality

Evidence62
Adoption48
Hype gap+22
Incentives58
Confidence58

Perspective Coverage

17 publishers
Builder
Builder 43%
Operator
Operator 33%
Investor
Investor 24%
Why these scores

Claim ledger

Ranked by verification strength, evidence, and original report placement.

  1. [1]

    Opus 5.5 costs $4 per million input tokens and $20 per million output tokens through Anthropic's API, down from $5 and $25 for Opus 5.

    Reported SupportedView cited source
  2. [2]

    Anthropic claimed Opus 5.5 costs 40% less than Opus 5 on typical workloads and generates output more than 30% faster.

    Reported Supported Source: Anthropic, as reported by The New StackView cited source
  3. [3]

    The New Stack called both models through the Anthropic API with identical prompts, adaptive thinking at the default effort level (Opus 5.5 does not allow thinking to be turned off), and ran each of three reasoning problems once per model.

    Reported SupportedView cited source
  4. [4]

    The LessWrong review, discussing Artificial Analysis results, says that as tested on max, Opus 5.5 uses so many tokens it is slightly more expensive than Opus 5.

    Reported Supported Source: LessWrong review citing Artificial AnalysisView cited source
  5. [5]

    Artificial Analysis puts Opus 5.5 into the clear lead overall in intelligence at 58, according to the LessWrong review.

    Reported Supported Source: LessWrong review citing Artificial AnalysisView cited source
  6. [6]

    Opus 5.5 cache pricing is $0.20, 60% lower than Opus 5, according to the LessWrong review.

    Reported SupportedView cited source
  7. [7]

    With the limit raised to 128,000 tokens, Opus 5 used every token, took over 25 minutes, and stopped with no answer, costing $3.20. Opus 5.5 ran for 19 minutes and used 112,733 tokens, but the API ended the response with a 'refusal' stop reason and no text.

    Reported SupportedView cited source
  8. [8]

    Anthropic's prompting guide says effort is the main control for how much Opus 5.5 thinks, that thinking is always on, that medium is the default on Opus 5.5 while Opus 5 defaults to high, and that developers should set effort explicitly and test several levels against their own evals rather than carrying over the Opus 5 setting.

    Reported SupportedView cited source
  9. [9]

    In Anthropic's testing, Opus 5.5 at its default medium effort matched or beat Opus 5 at high effort on multistep agentic coding tasks, in fewer steps and with fewer tokens.

    Reported Supported Source: Anthropic prompting guideView cited source
  10. [10]

    Thinking tokens are billed as output tokens.

    Reported SupportedView cited source
  11. [11]

    The price cut alone accounts for a 20% saving; the rest of the claimed 40% saving has to come from the model using fewer tokens.

    Reported SupportedView cited source
  12. [12]

    On the logic grid both models got all 28 cells right. Opus 5.5 took 65 seconds and 7,573 output tokens for $0.16; Opus 5 took 108 seconds and 10,621 output tokens for $0.27. Opus 5.5 was 43% cheaper.

    Reported SupportedView cited source
  13. [13]

    On the stone game both models answered all three parts correctly. Opus 5.5 finished in 215 seconds with 28,740 output tokens, costing $0.58; Opus 5 took 624 seconds and 74,981 output tokens, costing $1.88. Opus 5.5 used 62% fewer tokens and cost 69% less.

    Reported SupportedView cited source
  14. [14]

    On the constrained-orderings problem with a 48,000-token output limit, both models spent the whole budget thinking and never replied. Opus 5.5 used 489 seconds and $0.96; Opus 5 used 553 seconds and $1.20.

    Reported SupportedView cited source
  15. [15]

    The correct counts for the orderings problem are 27, 1,695 and 159,019; the third is very hard to reach by reasoning alone, a program that checks every possible ordering can find it, and neither model could run code in the test.

    Reported SupportedView cited source
  16. [16]

    At Opus 5.5's list output price, 112,733 tokens come to about $2.25.

    Derived Supported
  17. [17]

    The New Stack's test compared Opus 5.5 at medium effort with Opus 5 at high effort.

    Derived Supported
  18. [18]

    Opus 5.5 used about 29% fewer output tokens than Opus 5 on the logic grid.

    Derived Supported
  19. [19]

    On the 48,000-token capped run, Opus 5.5 cost exactly 20% less than Opus 5, equal to the list-price cut, because both billed the full 48,000 output tokens.

    Derived Supported
  20. [20]

    The New Stack's writer said the prompt asks the model to count job orderings and contains nothing sensitive, so the refusal was most likely a mistake by Anthropic's safety filter.

    Reported Insufficient Source: The New Stack's testerView cited source
  21. [21]

    Anthropic's Opus 5.5 prompting guide includes a 'Safeguard refusals' section for requests that return stop_reason: "refusal".

    Reported InsufficientView cited source

Sources

17 independent publishers whose own reporting we read for this story.

  1. archive.thedeepview.com

    1 article · September 23, 2026

    OpenAI drives down cost of frontier AI again
  2. aws.amazon.com

    5 articles · September 22, 2026

    Claude Opus 5.5 is now available on AWS GovCloud (US)
  3. blog.vercel.com

    2 articles · September 21, 2026

    Claude Opus 5.5 now available on AI Gateway
  4. dev.to

    12 articles · September 25, 2026

    GPT-6 Sol vs Opus 5.5: Price and Benchmarks
  5. GPT-6 Sol Model | OpenAI API
  6. economictimes.indiatimes.com

    2 articles · September 22, 2026

    Anthropic unveils Claude Opus 5.5 - The Economic Times
  7. latent.space

    1 article · September 22, 2026

    [AINews] Claude Opus 5.5, the new default model for AINews — and everybody cuts prices 40-50%
  8. lesswrong.com

    2 articles · September 26, 2026

    Introducing Opus 5.5: Anthropic Linkpost
  9. mezha.net

    3 articles · September 22, 2026

    Anthropic представила Opus 5.5: модель випереджає Fable і працює дешевше
  10. What's new in Claude Opus 5.5 - Claude Platform Docs
  11. runtimewire.com

    3 articles · September 22, 2026

    Live Updates: Anthropic's Opus 5.5 surfaces in Claude Code; GPT-6 Sol remains a rumor
  12. simonwillison.net

    2 articles · September 22, 2026

    Claude Opus 5.5, GPT-6 Sol, GPT-6 Luna, and a new price war
  13. testingcatalog.com

    6 articles · September 22, 2026

    Anthropic tests Fable 5.2 and Opus 5.5 ahead of the release
  14. the-decoder.com

    4 articles · September 22, 2026

    Claude Opus 5.5 matches Fable 5.1 performance at lower cost and promises less "Claudish" writing
  15. theneuron.ai

    9 articles · September 24, 2026

    😺 GPT-6 Sol / Luna vs. Claude Opus 5.5 LIVE
  16. thenewstack.io

    12 articles · September 28, 2026

    Anthropic releases Opus 5.5 and cuts pricing by 20%. Your agent calls might secretly get routed to an older model.
  17. thesequence.substack.com

    1 article · September 27, 2026

    The Sequence Radar - Issue 940: Last Week in AI: Opus 5.5 Gets Leaner, Meta Goes Wearable, Washington Talks to Beijing, and Claude Explores DNA

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