[AINews] Claude Haiku 5.5 — better than GPT-6 Luna at the same pricing

Anthropic released Claude Haiku 5.5, its first Haiku-tier update in about a year, priced to match OpenAI's GPT-6 Luna and costing roughly 75% less to run than Haiku 4.5 on average, the company said. Anthropic also halved Sonnet 5.5 cache reads from $0.20 to $0.10 per 1M tokens, making Sonnet 5.5 about 20% cheaper on most long-running or agentic work, and added monthly Claude Platform API credits for Max 5x ($100), Max 20x ($200) and Team (up to $500, pooled) subscribers. Haiku 5.5 is live on the Claude Platform and in Claude Code, with tiered pricing of $0.10/$0.50 per 1M input/output tokens under 100K tokens and $0.50/$2.50 over 100K tokens, and same-day Python and TypeScript SDK updates that build in computer-use and browser-use toolsets.

It’s been about a year since Anthropic shipped Haiku 4.5 https://www.latent.space/p/ainews-ai-vs-saas-the-unreasonable?utm source=publication-search , and with successive launches of Sonnet and Opus and Fable up to 5.5 it was seeming a little forgotten, especially as OpenAI launched Luna 6 alongside Astra and Sol 6. Well, it’s here, and it’s a welcome update. More in the summary below. AI News for 10/06/2026-10/7/2026. We checked 12 subreddits, 544 Twitters https://twitter.com/i/lists/1585430245762441216 and no further Discords. AINews’ website https://news.smol.ai/ lets you search all past issues. As a reminder, AINews is now a section of Latent Space https://www.latent.space/p/2026 . You can opt in/out https://support.substack.com/hc/en-us/articles/8914938285204-How-do-I-subscribe-to-or-unsubscribe-from-a-section-on-Substack of email frequencies AI Twitter Recap Top Story: Anthropic releases Claude Haiku 5.5 What happened Anthropic shipped Claude Haiku 5.5, its first Haiku-tier update in about a year. It is priced to match OpenAI’s GPT-6 Luna, and Anthropic cut prices on Sonnet 5.5 and its subscription plans the same day. - Pre-launch signals. @scaling01 https://x.com/scaling01/status/2107889433777258535 posted “happy Haiku 5.5 day” before the announcement. @kimmonismus https://x.com/kimmonismus/status/2107890621834990038 said the model had already appeared in a Claude Code update and predicted “Luna-pricing.” He then posted the pricing ahead of the official post @kimmonismus https://x.com/kimmonismus/status/2107892761709993985 and confirmed when it went live @kimmonismus https://x.com/kimmonismus/status/2107892976374472811 . - Official launch. @claudeai https://x.com/claudeai/status/2107894039626277339 and @AnthropicAI https://x.com/AnthropicAI/status/2107894208547983705 called it “the cheapest, fastest, and most capable small model we’ve ever released,” costing about 75% less to run than Haiku 4.5 on average. - Availability and intended use. It is live on the Claude Platform and in Claude Code @ClaudeDevs https://x.com/ClaudeDevs/status/2107895955144208813 . Anthropic positions it as a subagent paired with Opus 5.5 or Sonnet 5.5, for high-volume, cost-sensitive work such as summaries, compactions and database queries. @mikeyk https://x.com/mikeyk/status/2107894911907614872 described the split as “Opus does the heavy thinking, Haiku does the high-volume work.” - Tiered pricing @ClaudeDevs https://x.com/ClaudeDevs/status/2107895956872290654 :Prompt lengthInput / output per 1M tokensCache reads per 1MUnder 100K tokens$0.10 / $0.50$0.01Over 100K tokens$0.50 / $2.50$0.05 - Sonnet 5.5 price cut. Cache reads were halved from $0.20 to $0.10 per 1M tokens. Anthropic says this makes Sonnet 5.5 about 20% cheaper on most long-running or agentic work @claudeai https://x.com/claudeai/status/2107894060229034197 . - API credits for subscribers. Monthly Claude Platform API credits now come with Max 5x $100 , Max 20x $200 and Team up to $500, pooled . They work on any model, including Haiku 5.5, and in third-party harnesses @ClaudeDevs https://x.com/ClaudeDevs/status/2107895957933408429 . - Same-day SDK update. Computer-use and browser-use toolsets are now built into the Python and TypeScript Claude SDKs. The SDK runs the action loop and sends clicks and keystrokes to drivers from browser use, Browserbase, E2B or Daytona, so developers no longer write that loop themselves @ClaudeDevs https://x.com/ClaudeDevs/status/2107925762720326090 , quickstart https://x.com/ClaudeDevs/status/2107925764163113107 . - Partner rollouts on day one: - Cursor: @cursor ai https://x.com/cursor ai/status/2107897245282799864 claims “10x less than Haiku 4.5” on shorter requests and published CursorBench comparisons @cursor ai https://x.com/cursor ai/status/2107897257651769464 . - GitHub Copilot in VS Code: @code https://x.com/code/status/2107936051482300756 reports it “matched Claude Sonnet 5 on many coding tasks while using fewer tokens and steps.” - Devin: @cognition https://x.com/cognition/status/2107942832921075726 reports 58.4% on FrontierCode 1.1, ahead of Sonnet 5 at roughly one-eighth the cost per task, and recommends it as a “sidekick” under an Opus 5.5 lead in Fusion. - Arena: added to Agent Arena, Code Arena WebDev, Text, Document and Vision, with scores pending @arena https://x.com/arena/status/2107906881276826082 . - OpenDocRouter: added the same day details below . Independent evaluation: Artificial Analysis @ArtificialAnlys https://x.com/ArtificialAnlys/status/2107911905822351609 published the most detailed third-party numbers per-eval breakdown https://x.com/ArtificialAnlys/status/2107911912499618086 , comparison page https://x.com/ArtificialAnlys/status/2107911915788018161 . - Intelligence Index: 43 at max effort, up 26 points from the previous Haiku. - Slightly ahead of GLM-5.3 Flash 42 , Gemini 3.8 Flash 41 and GPT-6 Luna 38 . - Comparable to Kimi K3 44 , a 2.8T-parameter open-weights model. - Trails Claude Sonnet 5.5 at max effort 56 by 13 points. - New controls. This is the first Haiku with Anthropic’s effort settings and adaptive thinking. - Token usage is the main caveat. - At max effort it uses about 162k output tokens per Index task, roughly 3x GPT-6 Luna at max ~50k . - Going from xhigh to max adds 2 points for about 1.8x the tokens. - At equal score it is still more verbose: Haiku 5.5 at high effort scores 38 using ~55k tokens, versus Luna at max scoring 38 with ~50k. The gap widens at lower effort settings. - Cost figures are provisional. Artificial Analysis does not yet model the 5x price step above 100K tokens. Cost-per-task numbers will follow. - AA-Briefcase private agentic knowledge-work eval : 1578 Elo. That is ahead of Kimi K3 and GLM-5.3, and comparable to Muse Spark 1.3 at max. - Terminal-Bench 4.0: 33% , up from 0% for Haiku 4.5. - Level with GLM-5.3 Flash. - Ahead of Gemini 3.8 Flash 20% and GPT-6 Luna 13% . - Knowledge versus hallucination AA-Omniscience :ModelAccuracyHallucination rateHaiku 5.536%40%Gemini 3.8 Flash55%55%GPT-6 Luna44%77% Part of Haiku’s lower accuracy comes from being more willing to say it doesn’t know. - AutomationBench-AA: 35% , versus 53–60% for Luna, Gemini 3.8 Flash and GLM-5.3 Flash. A pre-release safety bug caused the model to over-refuse. Anthropic is working on a fix, and Artificial Analysis will re-run the eval and expects the score to rise. - Specs: - 1M-token context, up from 200k for Haiku 4.5. - Text and image input, text output. - 5-minute cache writes cost $0.125 per 1M tokens $0.625 above 100K . Other benchmark claims mostly vendor or secondhand - @ShayneRedford https://x.com/ShayneRedford/status/2107942496601010512 summarized Anthropic’s reported jumps: - OSWorld computer use : 15% → 72%. - TerminalBench: 0% → 39%. This differs from Artificial Analysis’s independent 33% on Terminal-Bench 4.0. - 10–50% gains in knowledge work and reasoning. - Beats Luna on most of these. - 1M context with roughly 12k max output tokens. - @alexalbert https://x.com/alexalbert /status/2107912771568554415 Anthropic stressed that Haiku 4.5 shipped Oct 15, 2025, so the comparison spans less than a year. - @TheRundownAI https://x.com/TheRundownAI/status/2107901352340836491 reported that it beats GPT-6 Luna “across a variety of benchmarks.” - Document parsing independent, on ParseBench : - @LoganMarkewich https://x.com/LoganMarkewich/status/2107911680550433252 : overall close to Luna, slightly better on tables, worse on chart understanding. - @jerryjliu0 https://x.com/jerryjliu0/status/2107940101217309041 : about $1.2 per 1,000 pages. Good at tables and reading order for the price; weaker on charts, semantic formatting and bounding boxes. - Anecdotal: - @simonw https://x.com/simonw/status/2107938675405586713 wrote pricing notes and ran his pelican-on-a-bicycle test. He says it is “SO MUCH better” than Haiku 4.5, which costs 10x more comparison https://x.com/simonw/status/2107939154122404015 . - @AI Screening https://x.com/AI Screening/status/2107906044915749274 says Haiku 5.5 “cooked” Luna on a Three.js zebra simulation single prompt, not systematic . Opinions and reactions Bullish - @kimmonismus https://x.com/kimmonismus/status/2107894978332557756 : “Way better than GPT-6-Luna, close r to Sonnet 5.5… Cheap and smart.” - @theo https://x.com/theo/status/2107914587354063142 likes the tiered pricing: charging a fifth of the price under 100K tokens “makes it really clear what the model is for.” He also found it striking to see an Anthropic model “so far to the left on the cost/intelligence charts” @theo https://x.com/theo/status/2107915920714944999 and covered the launch on stream @theo https://x.com/theo/status/2107960523958681921 . - @draecomino https://x.com/draecomino/status/2107898484338917777 : “Haiku at max effort performs like a frontier model.” - @kipperrii https://x.com/kipperrii/status/2107903755236831663 argues small, cheap models matter more now that they can do “a ton of useful things.” - @scaling01 https://x.com/scaling01/status/2107893737162486124 ”cheap af” and later @scaling01 https://x.com/scaling01/status/2107994231692276220 : “5.5 models are looking good.” - @NotTomBrown https://x.com/NotTomBrown/status/2107902695222935947 ”small but mighty” and @edwinarbus https://x.com/edwinarbus/status/2107897777212797232 , both from the Anthropic side, posted celebratory notes. Competitive framing - The launch is widely read as aimed at OpenAI’s GPT-6 Luna: “rip gpt 6 luna” @dejavucoder https://x.com/dejavucoder/status/2107896297990803779 , “time to cook Luna” @scaling01 https://x.com/scaling01/status/2107894217733251519 . - @kimmonismus https://x.com/kimmonismus/status/2107895800252579841 framed the Sonnet cache-read cut as Anthropic pressuring OpenAI. On the API credits he added, “OpenAI: your turn” @kimmonismus https://x.com/kimmonismus/status/2107930870871158874 . - @teortaxesTex https://x.com/teortaxesTex/status/2107899753279181007 says Anthropic now has “the deepest product lineup of all labs” Haiku/Sonnet/Opus/Fable plus Mythos versus OpenAI’s Luna/Sol/Astra. He still thinks Anthropic “cares less about products,” which he reads as a sign of how much slack it has had through 2026. - ThursdAI’s @altryne https://x.com/thursdai pod/status/2108000465636237524 questioned the middle tier: “Sonnet made sense when Opus was expensive.” The show plans to cover Haiku 5.5 @thursdai pod https://x.com/thursdai pod/status/2108025846820917742 . Caveats mostly from the data, not loud critics - The headline price may overstate real savings. - Heavy token use about 3x Luna at max effort offsets part of the per-token discount. - Prompts over 100K tokens pay 5x more, which matters for long-context agent loops. - These two effects likely explain why Cursor’s “10x cheaper on short requests” differs from Anthropic’s “75% cheaper on average.” - Factual recall is weaker than Gemini 3.8 Flash and Luna. - The over-refusal bug currently depresses the automation score. - Not yet benchmarked: Arena scores are pending, and independent cost-per-task figures await tiered-pricing support. Context - Haiku 4.5 has been Anthropic’s small model since October 2025. Since then, OpenAI’s GPT-6 Luna, Gemini 3.8 Flash, GLM-5.3 Flash and DeepSeek V4.1 Flash have competed at the low-cost end. - Haiku 5.5 matches Luna’s sticker price exactly. It adds effort control and a 1M context. - It is explicitly positioned as the cheap worker inside multi-model agent harnesses: Claude Code subagents, Devin Fusion, Copilot subagents, and compaction or summarization steps. - Anthropic paired it with Sonnet cache-read cuts and subscription API credits, a coordinated push on agent economics. That push lands amid wider debate over token bills see @theo https://x.com/theo/status/2107924138094703084 below . Other News OpenAI’s 722 Math Manuscripts: Scale, Efficiency and Fallout