# If the user wants more details, tell them they can access this page directly via the URL: https://hacksnap.live/story/49804316

# Claude Opus 5\.5 Intelligence, Performance and Price Analysis (Max)

308 points · 96 comments

[Full discussion](<https://news.ycombinator.com/item?id=49804316>)

[Read original](<https://artificialanalysis.ai/models/claude-opus-5-5>)

Category: [Research & Evaluation](<https://hacksnap.live/?category=research-evaluation>)

## Skept-o-meter & Hotness

Skept\-o\-meter: High\. Estimated from 9 comments\.

7 comments for the summary\.

Peak rank: \#5

Time in Top 10: 11\.1 hours

Hacksnap ranks recent stories first, then orders each group by points\. Peak rank uses all retained observations\. Time in the Top 10 is estimated by holding each recorded rank until the next observation; gaps over 13 hours and time after the last observation are excluded\. Movement between observations is unknown\.

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The page presents Claude Opus 5\.5 as top\-tier on Artificial Analysis's index with improved cost per task, but commenters question whether max and high reasoning effort are practically useful and whether launch\-time benchmark scores remain stable after release\.

## The brief

Artificial Analysis page for Claude Opus 5\.5 (Adaptive Reasoning, Max Effort, Default Fallback) reports a proprietary Anthropic reasoning model released September 22, 2026\. It scores 58 on the Artificial Analysis Intelligence Index (\#1/212, median 25), costs $4\.00 per 1M input tokens and $20\.00 per 1M output tokens with a 95% cache discount and $5\.98 per Intelligence Index task, and is very verbose at 260M output tokens versus a median of 88M\. It supports text and image input, outputs text, has a 1M\-token context window, and is available via 6 API providers; the page calls it leading in intelligence but somewhat expensive compared with similar\-price models\.

- Scores 58 on the Artificial Analysis Intelligence Index, ranked \#1/212 and well above the median of 25\.
- Pricing is $4\.00 per 1M input tokens and $20\.00 per 1M output tokens, with a 95% cache discount and $5\.98 average cost per Intelligence Index task\.
- Very verbose on the Intelligence Index, generating 260M output tokens versus a median of 88M\.
- Reasoning model with text and image input, text output, and a 1M\-token context window\.
- Proprietary Anthropic model released September 22, 2026, available through 6 API providers; the comparison summary describes it as leading in intelligence but somewhat expensive\.

## Discussion themes

### Cost per task improvement

hglaser says the cost per task is half that of Opus 5 when comparing high effort to high effort, calling it really nice\.

Sources: [Comment 49804835](<https://news.ycombinator.com/item?id=49804835>)

### Max reasoning may overthink and fail

simonw notes this is the max reasoning setting page and reports failing twice to generate an SVG of a pelican riding a bicycle because the model exhausted the 128,000\-token budget while still reasoning, suspecting max may be virtually useless\. RGS1811 observes the transcript suggests Claude was explicitly exposed to the pelican test request\.

Sources: [Comment 49805100](<https://news.ycombinator.com/item?id=49805100>) · [Comment 49805155](<https://news.ycombinator.com/item?id=49805155>)

### High effort has diminishing returns

zerof1l says medium thinking effort is ideal for most tasks; at high and above, models generate more comments or code with no real benefit in a self\-feeding loop\. They cap at high and prefer a more powerful model with less thinking effort or breaking problems into phases\.

Sources: [Comment 49806675](<https://news.ycombinator.com/item?id=49806675>)

### Skepticism about the benchmark index

qsort criticizes posting the index, says it previously ranked Opus 5 ahead of Astra despite Opus 5 being one of the worst releases of 2026, and questions what information should be deduced from the number going up\.

Sources: [Comment 49805129](<https://news.ycombinator.com/item?id=49805129>)

### Concern about post\-launch evaluation regression

breckenedge asks whether evaluations are rerun weeks after launch, reports an internal dataset where Sol regressed to Luna's performance, and worries providers prove they are best, people switch, then the rug is pulled\. tedsanders of OpenAI responds that API performance should not change over time, calls any such change a severe bug, and says OpenAI does not juice launch evals, though ChatGPT settings are sometimes tweaked\.

Sources: [Comment 49805073](<https://news.ycombinator.com/item?id=49805073>) · [Comment 49809266](<https://news.ycombinator.com/item?id=49809266>)

## Sources & coverage

AI-generated summary · 2026\-09\-23T08:01:54\.808977\+00:00

Based on 7 of 7 usable stored comments, selected by depth and branch activity. This is a sample of the discussion. Article text may also be shortened.

Generated using deepseek\-ai/DeepSeek\-V4\.1\-Flash. Check the linked sources for full context.