Anthropic发布Claude Opus 5.5：性能对标Fable

OpenAI made a valiant effort with GPT-6 Sol and Luna launching 50% lower than GPT-5.6, but with 17M views on the launch and counting, today was always going to belong to Claude Opus 5.5, “the first model in our new Claude 5.5 family” performing like “Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5.”

Opus 5.5 beats Fable or challenges Astra at most benchmarks, and both labs credited efficiency work for the API price cuts, but there are HUGE double digit gains everywhere from prefill to decode to overall compute…

… with offsetting inefficiency in token usage on some frontier tasks.

HOWEVER something that is a rare emphasis in the Claude launch was the writing improvements: “It puts the most important information up front and follows the writing rules you give it, which makes long sessions easier to follow.”

We can confirm - here is today’s AINews section run on Opus 5.5 and Sol 6. The difference is night and day - we are migrating to Opus 5.5 immediately for AINews going forward until we reach the next model/version of AINews.

They have also published initial work on large multiagent swarms (and efficiency):

AI News for 9/21/2026-9/22/2026. We checked 12 subreddits, 544 Twitters and no further Discords. AINews’ website lets you search all past issues. As a reminder, AINews is now a section of Latent Space. You can opt in/out of email frequencies!

AI Twitter Recap

Top Story: Claude Opus 5.5 launch, numbers, and reactions

What happened

Anthropic shipped Claude Opus 5.5, the first model in a new Claude 5.5 family. Its pitch is Fable 5.1‑level capability at Opus pricing, with more speed and better writing. OpenAI released GPT‑6 Sol and Luna about an hour later.

• Launch claims. Opus 5.5 “performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5” (@claudeai; @AnthropicAI).
• Where it leads. Anthropic says it leads on agentic coding, computer use, and knowledge work (@claudeai).
• Speed and cost. It is about 30% faster and about 40% cheaper per task than Opus 5 (@ClaudeDevs, @lydiahallie).
• Communication fixes. The model puts the most important information up front and follows user writing rules. This targets the most common feedback on Opus 5 (@claudeai).
• Subscription changes:
• 5‑hour session limits are up 20%.
• Lower pricing means limits go 25% further.
• Pro, Max, and Team users get a banked rate‑limit reset they can use whenever they choose (@claudeai, @ClaudeDevs, @trq212).
• New defaults. Opus 5.5 is now the default in Claude Code and the Claude app, including Cowork. Default effort is medium, described as “comparable to Fable 5.1 on intelligence but faster” (@_catwu).
• Availability. It is live in Claude Code and the Claude Platform API (@ClaudeDevs), and in Claude Tag for Slack (@_catwu).
• Roadmap. Sonnet 5.5 and Haiku 5.5 follow “in the coming weeks” (@mikeyk, @AiBattle_). This contradicts rumors that Haiku was discontinued (@kimmonismus).
• Safeguards. Opus 5.5 is the first Opus with Fable 5.1‑class safeguards on cyber, bio, and frontier LLM development. Flagged requests fall back to another model, and Anthropic says it is “working to reduce incorrect flags” (@ClaudeDevs).
• Pre-release signals. The model was spotted in Claude Code shortly before the announcement (@kimmonismus).
• System card. It was published at launch (@scaling01).

Pricing and token economics (facts)

• List price. Token pricing was cut 20%, from $5/$25 to $4/$20 per 1M input/output tokens (@ValsAI).
• Offset by higher token use. Vals notes Opus 5.5 often uses more tokens, especially on coding, where it posts its largest gains. The lower sticker price is partly offset by usage.
• Artificial Analysis cost breakdown. At max effort, Opus 5.5 costs $5.98 per Intelligence Index task versus $5.86 for Opus 5 (max). Their decomposition (@ArtificialAnlys):
• Higher token usage alone would raise cost per task about 80%, to $10.51.
• The 20% base-price cut brings that to $8.41.
• Cheaper cache reads ($0.20) bring it to $5.98.
• What that means. At max effort, the per‑task saving over Opus 5 disappears. The “40% cheaper” claim applies to default (medium) settings.
• Relative to Fable 5.1. Cline reports Opus 5.5 beats Fable 5.1 on the Artificial Analysis Intelligence Index at about 2.5x lower cost (@cline).
• Prompt caching. Switching effort mid‑session does not break the prompt cache on Claude Code v2.1.280+ (@lydiahallie).
• Model size (speculation). @theo claimed Opus 5.5 is smaller than Opus 5 and credited post‑training. This was not confirmed in official posts.

Benchmarks and independent evals

Anthropic’s own table. Opus 5.5 beats Fable 5.1 on every row of Anthropic’s headline comparison and beats GPT‑6 Astra on most (@kimmonismus, @synthwavedd, @scaling01).

@ShayneRedford (Anthropic) summarized the claimed gains:

• Stronger than Astra on CursorBench, KWBench, and OSWorld.
• Much better style and instruction following.
• Stronger science and health capabilities.
• More robust against cyber and bio misuse.

Third‑party and partner evals:

EvalResultSourceVals Index#1, up 2 spots / 2 pts vs Opus 5; Anthropic holds the top three spots (GPT‑6 Sol pending)@ValsAIVals RSI Index#1; first model to beat the published reference on LM Training under their protocol; beats Fable 5.1@ValsAI, @ValsAIFrontierSWE (Proximal)62.3%, #2 behind GPT‑6 Astra (65.5%); ahead of Fable 5.1 (56.3%) and Opus 5 (52.0%)@ProximalHQFrontierCode 1.1 (Cognition)65.3% on Extended; takes #1 from Fable 5 “at a fraction of the cost”@cognitionCursorBench57.8% (Max), new top model; 40% less per task than Opus 5@cursor_aiPerplexity WANDR0.610 at $4.13/task; slightly above Fable 5.1 at 67.6% lower cost@perplexity_aiParseBench (tables)93.9%, +7 pts over Opus 5; beats Fable, Gemini, Astra@jerryjliu0Roboflow vision/detection”By far the best vision model from Anthropic”; now among the models ahead of Google on the Playground leaderboard@skalskip92, @skalskip92

Eval details and caveats:

• Vals run settings. RSI was run in native Claude Code at max effort, with 1M context, 128K max output tokens, and temperature 1 (@ValsAI).
• ParseBench caveats. The model still struggles on charts, formatting, and layout. At 5.8¢/page, LlamaIndex calls it too expensive for production OCR. That verdict comes from a vendor with a competing product.
• AI R&D vs coding. @eliebakouch reads the system card as “roughly similar on AI R&D but a beast on agentic coding.”
• Saturation. @scaling01 asked whether CoBench is “cooked.” @synthwavedd joked about a new benchmark that launched already saturated.
• Arena. Opus 5.5 is in Agent Arena and in Battle Mode for WebDev, Text, Vision, and Document. No scores yet (@arena).

Effort‑scaling anomaly. On an agentic coding chart, xhigh effort costs about 2.8x more than medium for a 3.2‑point lower score (@LearnOpenCV). @Yuchenj_UW called it the “most bizarre benchmark result” and advised sticking with medium.

@nrehiew_ offered an explanation:

• Opus 5 showed the same pattern on FrontierCode.
• FrontierCode penalizes unnecessary changes, and higher effort produces scope creep.
• As a result, models “consistently perform worse at higher reasoning efforts.”

System card details

• Multi‑agent scaling. The system card reports scaling up to 100 parallel agents in Section 8.12. @scaling01 called it the first lab report of its kind. @maksym_andr highlighted it as evidence on multi-agent scaling laws.
• ProgramBench caveats. ProgramBench author @OfirPress flagged that Anthropic’s near‑100% solve rate comes from a 166/200 subset. That subset likely excludes the hardest programs, such as FFmpeg and the PHP compiler. He also flagged a metric mismatch (@OfirPress, @OfirPress):
• Anthropic reports average test pass rate.
• ProgramBench reports full task completion.
• Partial solves often pass 60–70% of tests, which inflates the pass-rate metric.