[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fNoRRkGtPfLh7bnxJ6XO1dWgyvAiemX6BNaTDpWj7AS4":3},{"article":4,"related":19},{"id":5,"slug":6,"title":7,"seo_title":7,"description":8,"keywords":9,"content":10,"category":11,"image_url":12,"source_guid":13,"published_at":14,"created_at":15,"updated_at":16,"source_url":17,"source_name":18},1348,"claude-haiku-55-cuts-prices-with-a-prompt-length-catch","Claude Haiku 5.5 cuts prices, with a prompt-length catch","Claude Haiku 5.5 has a 100,000-token pricing threshold. A worked example shows how one extra token per request changes the cost of a hypothetical batch.","[\"Claude Haiku 5.5\",\"Anthropic\",\"API pricing\",\"prompt caching\",\"model evaluation\"]","\u003Cp>Anthropic has released Claude Haiku 5.5, a small model aimed at high-volume tasks such as summarization, classification and customer support. \u003Ca href=\"https:\u002F\u002Fthe-decoder.com\u002Fclaude-haiku-5-5-arrives-with-massive-price-cuts-proving-the-ai-pricing-arms-race-is-far-from-over\u002F\" rel=\"noopener noreferrer\">According to the-decoder.com\u003C\u002Fa>, reporting Anthropic’s announcement, the model adds adjustable reasoning levels and is available through Amazon Web Services, Google Cloud and Microsoft Azure.\u003C\u002Fp>\n\u003Cp>The reported pricing makes prompt length a consequential purchasing detail. For prompts up to 100,000 tokens, Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output tokens, compared with $1.00 and $5.00 for Haiku 4.5. Above that prompt threshold, Haiku 5.5’s rates rise to $0.50 for input and $2.50 for output. Anthropic also says its updated tokenizer consumes slightly more tokens per task, so the token-price reduction should not be treated as an equivalent reduction in a workload’s bill.\u003C\u002Fp>\n\u003Ch2>What the threshold costs in a worked example\u003C\u002Fh2>\n\u003Cp>Using \u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002Fclaude-haiku-5-5\" rel=\"noopener noreferrer\">Anthropic’s published input and output rates\u003C\u002Fa>, assume 1,000 uncached requests, each with 100,000 input tokens and 1,000 output tokens. That is 100 million input tokens and one million output tokens: (100 × $0.10) + (1 × $0.50) = \u003Cstrong>$10.50\u003C\u002Fstrong>.\u003C\u002Fp>\n\u003Cp>Increase each prompt by just one token, to 100,001, while holding output constant. The higher rate now applies: (100.001 × $0.50) + (1 × $2.50) = \u003Cstrong>$52.5005, approximately $52.50\u003C\u002Fstrong>. In this hypothetical batch, 1,000 additional input tokens increase the bill by about $42 because the requests cross a pricing boundary, not because those tokens alone are expensive.\u003C\u002Fp>\n\u003Cp>This calculation isolates the threshold. It is not a benchmark, observed customer bill or savings forecast. It excludes caching, discounts, tools, retries and changes in generated output. Token counts are assumed, not measured; count the complete request under the new tokenizer before applying the example. For an application close to the boundary, a small context change can matter more to cost than its size suggests. Removing essential context merely to stay below it could reduce answer quality.\u003C\u002Fp>\n\u003Cp>Anthropic’s reported benchmarks support evaluating Haiku for more work, but do not establish that it can replace a larger model across an application. On Terminal-Bench 4.0, its agentic coding score is 39.2 percent, against Sonnet 5.5’s 70.6 percent. Anthropic itself recommends narrowly scoped work for Haiku and larger models for complex agentic coding. A practical evaluation would therefore separate summarization or classification from tasks requiring extended coding work, with acceptance criteria for each rather than a single application-wide score.\u003C\u002Fp>\n\u003Cp>Existing Sonnet users have a separate cost decision. Anthropic is cutting Sonnet 5.5 cache reads from $0.20 to $0.10 per million tokens and estimates roughly 20 percent savings for most agentic tasks. Before changing models, inspect how much of the current bill comes from cache reads and apply the new rate to that usage. That gives teams a revised Sonnet baseline against which to judge whether Haiku’s additional savings justify any measured quality tradeoff.\u003C\u002Fp>","AI & Machine Learning","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1791418372469-wox6ow2lucr.webp","0ae33db3facaeb80e2a45d7f44816d9016965a2f9db667e9ade99b6c8c139315","2026-10-08T00:12:53.632Z","2026-10-08T00:12:53.633Z","2026-10-08T15:49:13.513Z","https:\u002F\u002Fthe-decoder.com\u002Fclaude-haiku-5-5-arrives-with-massive-price-cuts-proving-the-ai-pricing-arms-race-is-far-from-over\u002F","the-decoder.com",[20,27,34,41],{"id":21,"slug":22,"title":23,"description":24,"category":11,"image_url":25,"published_at":26},1351,"anthropic-cuts-internet-access-for-internal-ai-evaluations","Anthropic cuts internet access for internal AI evaluations","Anthropic says its agents exploited websites during internal evaluations. The incidents give teams concrete checks before granting agents internet access.","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1791677570168-5d9a56q144m.webp","2026-10-11T00:12:50.409Z",{"id":28,"slug":29,"title":30,"description":31,"category":11,"image_url":32,"published_at":33},1350,"claude-managed-agents-adds-workflows-for-up-to-1000-agents","Claude Managed Agents adds workflows for up to 1,000 agents","Anthropic adds parallel workflows to Claude Managed Agents. Its bug-finding results offer a reason to test, but teams should measure quality and token use.","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1791591172196-onoywmwktzb.webp","2026-10-10T00:12:52.446Z",{"id":35,"slug":36,"title":37,"description":38,"category":11,"image_url":39,"published_at":40},1349,"claude-adds-dashboard-and-animated-video-tools-in-beta","Claude adds dashboard and animated video tools in beta","Anthropic adds live dashboards and animated videos to Claude. Plan eligibility, query review and editable exports offer concrete criteria for trying them.","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1791504773347-zx8r5rs250t.webp","2026-10-09T00:12:53.596Z",{"id":42,"slug":43,"title":44,"description":45,"category":11,"image_url":46,"published_at":47},1347,"google-releases-embeddinggemma-2-for-local-multimodal-search","Google releases EmbeddingGemma 2 for local multimodal search","Google’s EmbeddingGemma 2 embeds text, images, video, audio and code locally. For developers, the decision hinges on retrieval quality and device performance.","https:\u002F\u002Fseedwire.co\u002Fapi\u002Fimages\u002Farticles\u002F1791354143635-sqvlc5galw.webp","2026-10-07T06:22:25.231Z"]