# claude-opus-5-5 decision evidence

Claude Opus 5.5 is Anthropic's closed-weight model for long-running agentic coding and knowledge work, released on 2026-09-22 with a 1M-token context window, 128K output tokens and text and image input. It leads AI Coding Daily's coding leaderboard (57.83) and scored 55/60 on kzhu's version-2.2 test, and several one-prompt comparisons preferred its results, but it cost more than GPT-6 Sol in every comparison and had a rough showing in one lava-lamp build; one user's cache-heavy Claude Code history re-prices 44% below Opus 5 rates.

Verified: 2026-09-24; snapshot: 2026-09-25.

## Published model card

As the vendor publishes it for the model and its weights; these are not the limits of a hosted endpoint.

- Context window: 1M tokens
- Maximum output: 128K tokens (up to 300K on the Message Batches API with a beta header)
- Modalities: Text and image input; text output
- Parameter count: Not disclosed

## Open weights and deployment

Status: Unavailable. Anthropic publishes no Claude Opus 5.5 weights. The model is available on the Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry and Claude Platform on AWS.

Open-weight alternatives: [deepseek-flash](https://dash.chinaapi.ai/models/deepseek-flash/deploy), [glm-5.3-flash](https://dash.chinaapi.ai/models/glm-5.3-flash/deploy)

## Real-task reports

### [Claude Opus 5.5 and GPT-6 Sol on one interactive website prompt](https://x.com/Kappaemme1926/status/2102729710174196022)

By [Kappaemme](https://x.com/Kappaemme1926) (@Kappaemme1926). X user who posted this side-by-side test

Published: 2026-09-23; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: Build an interactive website about imaginary planets from a single prompt
- Method: Same prompt with both models on High; the author reported wall-clock time, how much each result covered and the share of each subscription's usage.
- Finding: Opus 5.5 took 26 minutes and built a fuller, explorable solar system with more detail, using 16% of the $20 plan's usage; GPT-6 Sol took 10 minutes for three planets and 1% of the $200 plan's usage.
- Limitation: One prompt judged by the author; the usage shares are meters of two different subscription plans, not API costs.
- Opus 5.5 time: 26 min
- GPT-6 Sol time: 10 min

### [Four models build the Eiffel Tower in Three.js](https://x.com/Bhavani_00007/status/2102795814355763277)

By [Bhavy](https://x.com/Bhavani_00007) (@Bhavani_00007). X user who ran the same Three.js task on four models and reported cost and time

Published: 2026-09-23; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: Build the Eiffel Tower in Three.js
- Method: Same task on Claude Opus 5.5, GPT-6 Astra, GPT-6 Sol and Kimi K3; the author reported cost and time for each and compared the results by eye.
- Finding: Opus 5.5 cost $8.95 and took 10 minutes; the author preferred its frontend and 3D detailing to GPT-6 Astra's ($7.45, 8 minutes), found GPT-6 Sol ($3.90, 5 minutes) disappointing and Kimi K3 ($4.04, 6 minutes) strong for the price.
- Limitation: One task judged by eye by the author; the post does not say how the models were run or how the costs were counted.
- Opus 5.5: $8.95 · 10 min
- GPT-6 Astra: $7.45 · 8 min

### [Claude Pro, Codex Plus and SuperGrok on the same work at maximum settings](https://x.com/shownotover/status/2102950408465338855)

By [shownotover](https://x.com/shownotover) (@shownotover). X user comparing $20 AI subscriptions in their first video

Published: 2026-09-24; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: One piece of work run on each $20 subscription; the task itself is shown only in the author's video
- Method: Each plan's top model at maximum reasoning (Grok 4.7 at xhigh); the author recorded the share of the weekly limit, tokens, working time and a 1–10 quality score.
- Finding: Opus 5.5 used 10% of the weekly limit (115 million tokens) over 2 hours and scored 5/10, behind GPT-6 Sol at 7/10 (29 million tokens, 69 minutes) and Grok 4.7 at 6/10; the author still recommends Claude at $20 for its usage allowance.
- Limitation: The post does not describe the task, the quality score is the author's own, and the numbers are subscription meters rather than API usage.
- Quality (author): 5/10
- Working time: 2 h
- Tokens: 115M

### [Eight weeks of Claude Code usage re-priced at Opus 5 and Opus 5.5 rates](https://www.reddit.com/r/ClaudeCode/comments/1wom776/opus_55_reads_the_price_page_as_20_cheaper_on_8/)

By [Drasezv](https://www.reddit.com/user/Drasezv/) (u/Drasezv). r/ClaudeCode member who built the transcript-reading tool the analysis comes from

Published: 2026-09-23; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: Price every request from eight weeks of the author's own Claude Code transcripts at Opus 5 and Opus 5.5 list prices
- Method: Requests deduplicated by requestId and priced per row, with cache reads, 1h and 5m cache writes, output and plain input counted separately.
- Finding: 97% of the tokens were cache reads, so the same usage came to $2,849 at Opus 5.5 rates against $5,071 at Opus 5 rates — 44% less, rather than the 20% the headline input and output prices suggest.
- Limitation: It re-prices the same token counts and does not measure whether Opus 5.5 uses more or fewer tokens on the same work; list prices, not subscription billing; the author built the tool that read the transcripts.
- Cache reads: 97% of tokens
- At Opus 5 rates: $5,071
- At Opus 5.5 rates: $2,849

### [Four models build a lava lamp from one prompt](https://x.com/bridgebench/status/2102770788319310302)

By [Bridgebench](https://x.com/bridgebench) (@bridgebench). BridgeMind's benchmark account, which calls itself the official AI benchmark of the vibe coding movement

Published: 2026-09-23; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: Build a lava lamp from a single prompt
- Method: Same prompt on Claude Opus 5.5, GPT-6 Astra, GPT-6 Sol and GPT-6 Luna; the account reported cost and time, asked readers which did best and commented on their answers in replies.
- Finding: Claude Opus 5.5 was the slowest and most expensive at $1.27 and 9 min 35 s, and in replies the account agreed it had a rough showing, answering 'Not on this test' to a claim that Opus beat Sol.
- Limitation: One prompt with the quality verdict left mostly to readers; the account is BridgeMind's own benchmark and does not say how the models were accessed.
- Claude Opus 5.5: $1.27 · 9m 35s
- GPT-6 Sol: $0.08 · 50 s

### [Claude Opus 5.5 and GPT-6 Sol on a black hole merger test](https://x.com/bridgebench/status/2103091707021848921)

By [Bridgebench](https://x.com/bridgebench) (@bridgebench). BridgeMind's benchmark account, which calls itself the official AI benchmark of the vibe coding movement

Published: 2026-09-24; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: The account's black hole merger visualisation test
- Method: The same test on both models; the account reported cost and time and judged the design.
- Finding: Claude Opus 5.5 cost $0.69 and took 6 min 8 s; the account called it 'a significant leap for design', while GPT-6 Sol did the test for $0.08 in 1 min 33 s.
- Limitation: One test judged by the account; the task is shown only in the attached video.
- Claude Opus 5.5: $0.69 · 6m 8s
- GPT-6 Sol: $0.08 · 1m 33s

### [Claude Opus 5.5 and GPT-6 Sol on one motion-graphic prompt](https://x.com/TheHunterBohm/status/2102724864205566388)

By [Hunter Bohm](https://x.com/TheHunterBohm) (@TheHunterBohm). Builds agent systems for business and posted a longer comparison video

Published: 2026-09-23; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: Make a 20-second motion graphic explaining how a language model turns a prompt into an answer and why long answers cost more
- Method: Same prompt on both models; the author reported time and cost and posted the prompt and a full comparison video in replies.
- Finding: Claude Opus 5.5 took 12.7 minutes and $2.86 against GPT-6 Sol's 11.4 minutes and $1.09; the author called the gap 'not even close' and, in replies, agreed that Sol's result was far worse.
- Limitation: One subjective prompt; the verdict comes from the author's post and replies rather than a score.
- Claude Opus 5.5: 12.7 min · $2.86
- GPT-6 Sol: 11.4 min · $1.09

### [AI Coding Daily LLM Coding Leaderboard](https://aicodingdaily.com/leaderboard)

By [AI Coding Daily](https://www.youtube.com/@AICodingDaily) (@AICodingDaily). Coding-model testing channel and website that runs its own leaderboard and sells premium tutorials and channel advertising

Published: 2026-09-24; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: Implement and harden production-shaped projects in several stacks, including a Laravel app, a Go service and a React/TypeScript app, from the same prompts
- Method: Each model and reasoning setting is a separate row run in a coding harness, with the average cost and time per run. Code quality is graded by a judge model against a published 100-point rubric and scaled to 20 points per project; behavioural reliability runs each of four projects five times and scores the checks every attempt fails.
- Finding: Claude Opus 5.5 led the board at 57.83 on high reasoning ($0.79 and 3 min 10 s per run in Claude Code), with its medium setting second at 57.37.
- Limitation: One author's benchmark whose code-quality half is graded by a judge model; rows run in different harnesses, the page is updated as models are added (read on 2026-09-24, 47 rows), and the author sells premium tutorials and advertising.
- Points (high): 57.83
- Rank: 1 of 47
- Cost per run: $0.79

### [kzhu's six-question LLM test leaderboard](https://www.techgogogo.com/llm-benchmark/)

By [AI产品狙击手 kzhu](https://www.youtube.com/@kevinzhu9305) (@kevinzhu9305). Chinese YouTube reviewer who scores models on a six-question test and publishes every score with per-question notes

Published: 2026-09-24; retrieved: 2026-09-24; verified: 2026-09-24.

- Task: Six questions scored out of 10: constrained sentence writing, two reasoning puzzles (replaced by pelican and compound-bow SVG animations in version 2.2), a browser OS with a space shooter, a 3D racing game and a Trello-style board
- Method: Each row names the harness the model ran in (Pi, Claude Code, WorkBuddy and others) and the date; the author scores every question with a note, and warns that totals are only comparable within one test version.
- Finding: Claude Opus 5.5 scored 55/60 on version 2.2 in Pi (54 in the author's note), 9 or 10 on every question; the author called its pelican SVG the best implementation seen and found nothing to fault in the browser OS, racing game or Trello board.
- Limitation: One author's scores on six questions; rows use different harnesses and test versions (2.1 or 2.2), and a few rows' table total differs by one point from the author's note.
- Score: 55 / 60 (v2.2, Pi)

## Public leaderboard coverage

A board missing from this list has no figure for this model in this snapshot; missing coverage is not a zero.

- LMArena Text Arena — Arena score (Elo): 1504 ±9 (retrieved 2026-10-05) [source](https://arena.ai/leaderboard/text)
- Artificial Analysis Intelligence Index — Intelligence Index: 58 (retrieved 2026-09-22) [source](https://artificialanalysis.ai/leaderboards/models)
- Epoch Capabilities Index (ECI) — General ECI: 167 (164 - 172) (retrieved 2026-10-04) [source](https://epoch.ai/eci)
- Vals Index — Accuracy (GDP-weighted finance, coding, legal and tax): 70.18 ±1.00 (retrieved 2026-10-23) [source](https://www.vals.ai/benchmarks/vals_index)
- LMArena Text Arena · Chinese — Arena score (Elo): 1571 ±29 (retrieved 2026-10-05) [source](https://arena.ai/leaderboard/text/chinese)
- LMArena Text Arena · Coding — Arena score (Elo): 1538 ±18 (retrieved 2026-10-05) [source](https://arena.ai/leaderboard/text/coding)
- Artificial Analysis · GDPval-AA v2.1 — Agentic Real-World Work Tasks, (Elo-500)/2000 (%): 67 (retrieved 2026-09-22) [source](https://artificialanalysis.ai/leaderboards/models)
- Artificial Analysis · Terminal-Bench v4.0 — Agentic Coding & Terminal Use (%): 60 (retrieved 2026-09-22) [source](https://artificialanalysis.ai/leaderboards/models)

## Curated comparisons

- [claude-opus-5-5 vs gpt-6-astra](https://dash.chinaapi.ai/models/compare/claude-opus-5-5-vs-gpt-6-astra)
- [claude-opus-5-5 vs gpt-6-sol](https://dash.chinaapi.ai/models/compare/claude-opus-5-5-vs-gpt-6-sol)

## Official sources

- [Introducing Claude Opus 5.5](https://www.anthropic.com/claude-opus-5-5) — Anthropic, retrieved 2026-09-24
- [Claude Opus 5.5 model documentation](https://platform.claude.com/docs/en/models/opus-5-5/overview) — Anthropic, retrieved 2026-09-24
- [System Card: Claude Opus 5.5](https://www.anthropic.com/claude-opus-5-5-system-card) — Anthropic, retrieved 2026-09-24