Verified · Oct 15, 2026
Independently verifiedAnthropic releases Claude Haiku 5.5 — its cheapest, fastest small model, around 75% cheaper to run than Haiku 4.5 by its own math, priced at $0.10/$0.50 per million tokens under 100k — with Sonnet 5.5 cache reads halved and monthly API credits announced for Max and Team
2 sourcesOn October 7, 2026 (Wednesday, calendar-verified), Anthropic announced Claude Haiku 5.5: "the cheapest, fastest, and most capable small model we've ever released." Per the announcement: "Claude Haiku 5.5 is designed for high-volume, cost-sensitive tasks. It reliably handles quick and repetitive workloads (like summaries, compactions, database queries, and classification requests). It pairs well with Opus 5.5 and Sonnet 5.5 as a subagent on coding work." The speed claim carries Anthropic's footnote: "our fastest model to date at each model's standard speed, although it runs less quickly than our Opus models in Fast Mode." Price, per the announcement: "On average, it now costs around 75% less to run." It is footnoted as 90% lower for requests up to 100,000 tokens and 50% lower over, with the caveat that "Haiku 5.5 has an updated tokenizer... which means it uses slightly more tokens per task." The pricing table: $0.10 input / $0.50 output per million tokens up to 100k; cache reads $0.01. Per the announcement: "Haiku 5.5 is especially good value when used for tasks with prompts up to 100,000 tokens, which make up around 90% of requests to our previous Haiku model." It is "our first Haiku-class model to come with an adjustable effort setting". Anthropic-reported benchmarks: OSWorld 2.1 (offline subset) 72.4% versus Haiku 4.5's 15.7%; Humanity's Last Exam 45.9% no tools versus 10.2%; Terminal-Bench 4.0 39.2% versus Sonnet 5.5's 70.6% — with the announcement's own placement: "Sonnet 5.5 and Opus 5.5 remain better choices for complex agentic coding tasks like those measured by Terminal-Bench 4.0." Safety: cybersecurity safeguards are "more restrictive than Haiku 4.5's, but somewhat less restrictive than those we've applied to other recent models", and "still block penetration testing and other techniques more likely to be used by attackers". Availability: "available now on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure." Also announced: "starting today, we're lowering the price of cache reads on Claude Sonnet 5.5. Cache reads now cost 50% less: $0.10 per million tokens rather than $0.20" — cutting Sonnet 5.5's cost "on most agentic tasks by around 20%"; and "this week, we'll roll out a new monthly API credit to all Max and Team subscribers" — Max 5x $100/month, Max 20x $200/month, Team up to $500 pooled, usable "on any of our models". Per Simon Willison: "The new Haiku exactly matches the price of GPT-6 Luna—$0.10/$0.50—up to 100,000 tokens." His tokenizer measurement found "around 1.25x as many tokens" on the same long prompt versus Haiku 4.5, "so there's a hidden price increase there"; and on the credits, "The API credits exactly match the cost of the subscription itself." The monthly credits "do not roll over—use them or lose them".
Why now
The cheap-work layer of your AI workflow just got repriced. Per Anthropic's announcement, Haiku 5.5 handles "quick and repetitive workloads (like summaries, compactions, database queries, and classification requests)" at "around 75% less to run" than Haiku 4.5 — the exact tasks creators now hand to batch scripts. Second layer, the subagent pattern is official positioning: per the announcement it "pairs well with Opus 5.5 and Sonnet 5.5 as a subagent on coding work" — the big-model-plans, small-model-executes split your audience keeps asking how to build. Third layer, the subscription-to-API bridge is new: "this week, we'll roll out a new monthly API credit to all Max and Team subscribers" — Max 5x $100, Max 20x $200, Team up to $500 — and per Simon Willison "The API credits exactly match the cost of the subscription itself." That turns a chat subscription into build budget for tools and agents. Fourth layer, the honest-fine-print card: the fine print puts the same model at "50% lower" — not 90% — beyond 100,000 tokens, and Willison's tokenizer measurement found "around 1.25x as many tokens" on the same prompt — the price cut has edges, and the edges are the explainer.
Why it is worth publishing
The most build-relevant card of the day: a model priced for volume, official subagent positioning against Opus and Sonnet, and an API-credit program that converts subscriptions into build budget — that combination hands your audience a concrete weekend project. The differentiation play is the fine-print tour: the 75% average is a footnoted blend (90% under 100k tokens, 50% over, tokenizer cost baked in), Willison's Luna comparison is his analysis rather than Anthropic's positioning, and the Terminal-Bench numbers have Anthropic itself saying Sonnet and Opus remain better for complex agentic coding. Creators who teach where the cheap tier wins — and where it doesn't — own the pricing beat; everyone else will screenshot the benchmark table.
Evidence basis
Two opened sources: Anthropic's official announcement page (page date label 'October 7, 2026', Wednesday calendar-verified; no JSON-LD datePublished, so the rendered label anchors the date; raw HTML fetched and every quote grepped) and Simon Willison's blog (posted 7th October 2026 at 8:56 pm, Wednesday calendar-verified; raw HTML fetched and every quote grepped). Calendar checks: October 7, 2026 = Wednesday; October 11 (this card's publish date) = Sunday. Launch-state discipline: the model is live ("available now on all platforms") — the one present-tense fact; the Sonnet 5.5 cache-read cut is anchored to the announcement's 'starting today' (October 7); the API credits are a rollout announced for 'this week' with no confirmed completion — never written as already live in every subscriber's account. Price discipline: the ~75% average keeps its footnote (90%/50% split, 90% of Haiku 4.5 requests in the under-100k bucket, tokenizer uses slightly more tokens per task); benchmark figures stay Anthropic-reported with the placement sentence attached; customer figures (Asana 30%/2.5x, HubSpot 92.8%, AlphaSense 8M and 0.84-vs-0.76, Cognition 66.2) stay customer-reported and vendor-relayed. Willison layer: the Luna same-price comparison, the 1.25x tokenizer measurement, the credits observations, and the Codex comparison are his own analysis — attributed everywhere. The GDPval-AA v2.1 and AA-Briefcase v1.1 cells are garbled in extraction and are not used.
“Anthropic's new Haiku 5.5 costs about 75% less to run than Haiku 4.5 by Anthropic's own math — and it's positioned as the cheap subagent that does the repetitive work while Opus and Sonnet plan.”
Angle
Frame it as 'the cheap-work layer got repriced' in three beats. Beat one, the fit: per Anthropic's announcement, Haiku 5.5 is built for "high-volume, cost-sensitive tasks" — "summaries, compactions, database queries, and classification requests" — and "pairs well with Opus 5.5 and Sonnet 5.5 as a subagent on coding work"; demo the split by showing one job where the small model runs the loop and the big model does the planning. Beat two, the price with its fine print: the headline is "around 75% less to run", the footnote splits it 90% under 100,000 tokens and 50% over, and per Simon Willison the new tokenizer means "around 1.25x as many tokens" on the same prompt — show the buckets, not just the headline. Beat three, the subscription bridge: "this week, we'll roll out a new monthly API credit to all Max and Team subscribers" — Max 5x $100, Max 20x $200, Team up to $500 pooled — and per Willison the credits "exactly match the cost of the subscription itself" but "do not roll over" — close by asking your audience what they would build with a monthly budget that expires.
Format
Long-form explainer
Demo idea
A 'price bucket' walkthrough: the same task priced three ways — under 100k tokens ($0.10/$0.50 per million, cache reads $0.01), over 100k ($0.50/$2.50) — with the footnote caveats on screen (tokenizer uses slightly more tokens per task; Sonnet cache reads now $0.10), and a live subagent demo where Haiku 5.5 summarizes or classifies while Opus or Sonnet holds the plan. Caption every number as Anthropic-reported, and Willison's Luna comparison as his analysis.
Platform notes
The model is live ("available now on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure") — present tense is safe for the model only. The API credits stay announced-state: "this week, we'll roll out" per the October 7 announcement — never 'you already have credits', and no start date beyond 'this week'. Every price claim keeps its bucket: ~75% average is Anthropic's footnoted blend (90% under / 50% over 100k, tokenizer uses slightly more tokens). 'Fastest model to date' keeps its footnote (standard speed; Opus Fast Mode runs faster). Benchmarks stay Anthropic-reported with the placement sentence (Sonnet and Opus remain better for complex agentic coding; Terminal-Bench 4.0: 39.2% vs Sonnet 5.5's 70.6%). Customer figures stay customer-reported. Willison's Luna comparison, 1.25x tokenizer measurement, and credit observations stay attributed to Willison. The cache-read cut's 'starting today' is October 7 announcement voice — the card says October 7.
Usable claims
- On October 7, 2026 (Wednesday, calendar-verified), Anthropic announced Claude Haiku 5.5: "the cheapest, fastest, and most capable small model we've ever released." Per the announcement: "Claude Haiku 5.5 is designed for high-volume, cost-sensitive tasks. It reliably handles quick and repetitive workloads (like summaries, compactions, database queries, and classification requests). It pairs well with Opus 5.5 and Sonnet 5.5 as a subagent on coding work. And, since it's also our fastest model to date, it works especially well for speed-sensitive tasks like live customer support and browser use." The fastest-model claim carries Anthropic's own footnote: "Claude Haiku 5.5 is our fastest model to date at each model's standard speed, although it runs less quickly than our Opus models in Fast Mode." Pricing, per the announcement: "Haiku 5.5 is available at a much lower price than Haiku 4.5. On average, it now costs around 75% less to run." The footnote scopes that average: "Claude Haiku 5.5 is priced 90% lower than Claude Haiku 4.5 for requests up to 100,000 tokens, and 50% lower for requests over 100,000 tokens. On Haiku 4.5, 90% of requests fell into the former category. This calculation also accounts for changes between Haiku 4.5 and Haiku 5.5 in how many tokens are used to complete a given piece of work: Haiku 5.5 has an updated tokenizer (similar to Sonnet 5.5's and Opus 5.5's), which means it uses slightly more tokens per task." Per the pricing table, Haiku 5.5 costs $0.10 input / $0.50 output per million tokens for prompts up to 100,000 tokens ($0.50 / $2.50 over 100k), with cache reads at $0.01 / $0.05. Per the announcement: "Haiku 5.5 is especially good value when used for tasks with prompts up to 100,000 tokens, which make up around 90% of requests to our previous Haiku model." Haiku 5.5 is "our first Haiku-class model to come with an adjustable effort setting", per the announcement, which adds that "users can decide whether to optimize for cost or intelligence". On benchmarks reported by Anthropic: OSWorld 2.1 (offline subset) 72.4% versus Haiku 4.5's 15.7%; Humanity's Last Exam 45.9% without tools versus Haiku 4.5's 10.2%; Terminal-Bench 4.0 39.2% versus Sonnet 5.5's 70.6% — and the announcement itself places the model: "Sonnet 5.5 and Opus 5.5 remain better choices for complex agentic coding tasks like those measured by Terminal-Bench 4.0. By contrast, Haiku 5.5 is best suited to more narrowly scoped tasks that might otherwise have been cost-prohibitive with previous versions of Claude—like compaction, summarization, or subagent work." On safety, per the announcement, Haiku 5.5's cybersecurity safeguards are "more restrictive than Haiku 4.5's, but somewhat less restrictive than those we've applied to other recent models", permitting "a wider range of defensive tasks than our safeguards for Sonnet 5.5" while they "still block penetration testing and other techniques more likely to be used by attackers". Availability, per the announcement: "Claude Haiku 5.5 is available now on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure." And per the announcement: "For developers, we're also updating our Claude Python and TypeScript SDKs to add support for computer use and browser use in beta." Alongside the model, Anthropic announced: "First, starting today, we're lowering the price of cache reads on Claude Sonnet 5.5. Cache reads now cost 50% less: $0.10 per million tokens rather than $0.20." — which Anthropic says "reduces the cost of Sonnet 5.5 on most agentic tasks by around 20%". And: "Second, this week, we'll roll out a new monthly API credit to all Max and Team subscribers for use on the Claude Platform. Max 5x users will get $100 in credits per month, Max 20x users will get $200, and Team subscribers will receive up to $500, pooled across their users." — credits usable "on any of our models". Per Simon Willison (posting October 7): "The new Haiku exactly matches the price of GPT-6 Luna—$0.10/$0.50—up to 100,000 tokens." Willison also measured: "My Claude Token Counter tool shows that the same long prompt uses around 1.25x as many tokens with Haiku 5.5 compared to Haiku 4.5, so there's a hidden price increase there." On the credits, per Willison: "The API credits exactly match the cost of the subscription itself. This is really generous—it makes it much easier for subscribers to use the API." And: "Note that the monthly credits do not roll over—use them or lose them." Customer-reported results relayed on Anthropic's page: Asana (Aaron Vinh) saw "over a 30% reduction in latency for task completions and up to 2.5x faster inference per agent turn"; HubSpot (Ze'ev Klapow) reported "92.8% averaged over three runs" on its CRM suite; AlphaSense (Daniel Campos) runs "Ask in Document" at "about 8M calls a week in production" and measured "0.84 vs. 0.76" against Haiku 4.5; Cognition (Walden Yan) reports "a top-tier FrontierCode score of 66.2" with Haiku 5.5 as the sidekick in Devin Fusion.
Evidence pipeline
From the news
Breakdown
A launch story where rollout state and price scope are the content. Layer one, the launch state: the model is present-tense live — per the announcement, "Claude Haiku 5.5 is available now on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure." Meanwhile the Sonnet 5.5 cache-read cut is anchored to the announcement's "starting today" (October 7) and the API credits are a rollout announced for "this week" with no confirmed completion, so the card never writes credits as already in subscribers' accounts. Layer two, the price buckets: "On average, it now costs around 75% less to run." That figure is Anthropic's own calculation with its footnote attached — 90% lower under 100,000 tokens, 50% lower over, against a base where "On Haiku 4.5, 90% of requests fell into the former category." The tokenizer caveat ("uses slightly more tokens per task") rides every retelling. Layer three, the two analyst layers stay named: per Simon Willison, "The new Haiku exactly matches the price of GPT-6 Luna—$0.10/$0.50—up to 100,000 tokens." His tokenizer measurement found "around 1.25x as many tokens" on the same prompt, and his credits observations ("exactly match the cost of the subscription itself"; "do not roll over") are his — none of it is Anthropic positioning. Layer four, the benchmarks stay vendor-reported with the placement sentence: Anthropic's own line keeps Sonnet 5.5 and Opus 5.5 "better choices for complex agentic coding tasks" (Terminal-Bench 4.0: 39.2% versus Sonnet 5.5's 70.6%), and the speed superlative carries footnote 1 ("at each model's standard speed, although it runs less quickly than our Opus models in Fast Mode"). Layer five, the customer numbers (Asana's 30%/2.5x, HubSpot's 92.8%, AlphaSense's 8M calls and 0.84-vs-0.76, Cognition's 66.2) stay customer-reported and vendor-relayed. Editor's rules: present tense for the model, announced-state for the credits, and a bucket on every price.
Risks
- Before publishing, re-check each layer: the model is live but the credits are an announced-this-week rollout with no confirmed completion; the cache-read cut's 'today' is October 7; every price claim keeps its bucket (75% average, 90%/50% split, tokenizer caveat); every Willison line stays attributed to Willison; the speed claim keeps its standard-speed footnote; benchmarks stay Anthropic-reported with the Sonnet-and-Opus placement sentence; customer numbers stay customer-reported; the safety framing stays relative with the penetration-testing block; and the superlative keeps its 'we've ever released' scope. If your script compresses any of these, cut the detail rather than round it.
Demo ideas
- Price-bucket walkthrough: the same task priced under vs over 100k tokens with the footnote caveats on screen, plus a live subagent demo (Haiku runs the loop, Opus/Sonnet holds the plan)
- Credit-explainer card: Max 5x $100, Max 20x $200, Team up to $500 pooled, usable on any model — labeled as announced 'this week' from October 7, with Willison's no-rollover observation attributed