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Claude Haiku 5.5 Explained — 1M Context, $0.10 MTok, Not an Audio Ingestor.

TL;DR — As of 2026-10-16, Anthropic launched Claude Haiku 5.5 on 2026-10-07. It brings 1M context, 128K max output, and $0.10 input / $0.50 output per million tokens under 100k (with $0.01 cache reads). While optimized for high-volume summarization and routing, it does not ingest audio or video files directly. Pair raw models with BibiGPT's transcription and notes workflow.

Released · 2026-10-07 $0.10 / $0.50 MTok Live demo below

Fast text models still need multimedia transcripts

Paste a podcast, lecture, or meeting URL — BibiGPT converts audio and video into chapters, full transcripts, and interactive Q&A. Claude Haiku 5.5 is Anthropic's low-cost reasoning model.

Add BibiGPT as a preferred source on Google See more BibiGPT in Top Stories and AI answers.

Key facts (90-second read)

As of 2026-10-16, Anthropic released Claude Haiku 5.5 on 2026-10-07. It features a 1,000,000-token context window, 128K generation limit, and costs $0.10 input / $0.50 output per million tokens (prompts under 100k). Prompt caching reads cost $0.01 / MTok. Anthropic positions it for high-volume compaction, extraction, and subagents. It does not accept direct audio or video files.

Features

What Anthropic shipped on 2026-10-07

Public facts from the official Claude Haiku 5.5 release — not an integration claim for BibiGPT.

1M context window and 128K output

Claude Haiku 5.5 expands context to 1,000,000 tokens with up to 128,000 tokens of generation. Designed for large document analysis, codebases, and compaction.

$0.10 / $0.50 per MTok under 100k

At prompt lengths under 100k tokens, input costs $0.10 and output costs $0.50 per million tokens. Prompt cache reads cost just $0.01 / MTok — an ~75% reduction versus Haiku 4.5.

Targeted at high-volume compaction

Anthropic positions Haiku 5.5 for high-volume summarization, data extraction, classification, subagents, and routing across enterprise workflows.

Why lightweight models still need a video/audio bridge

Haiku 5.5 is a text-and-token reasoning engine. Recordings and streams still need transcription, timestamps, and structure.

No native audio or video URL ingestion

Haiku 5.5 accepts text and images, but does not parse raw MP4, YouTube, Bilibili, or Zoom links. An ASR layer like Whisper or Qwen3-ASR must produce clean text first.

Meetings consume ~30% of work time

Laxis State of Meetings 2026: knowledge workers average 21.7 meetings weekly. Low token pricing helps backend costs, but humans need searchable action items and chapters.

Podcasts need curation and timestamps

Edison Infinite Dial 2026: listeners consume 8+ hours of weekly audio across multiple shows. BibiGPT timestamps key moments and syncs transcripts so you never miss decisions.

5 key facts about Claude Haiku 5.5

Verified facts from Anthropic's official announcement and pricing cards, checked 2026-10-16.

  1. 1

    Released on 2026-10-07

    Anthropic launched Claude Haiku 5.5 (claude-haiku-5-5) as the lightweight member of the Claude 5 family alongside Sonnet 5.5 and Opus 5.

  2. 2

    1M context window and 128K output

    Native 1,000,000-token input window allows processing entire books, research corpora, or repository documentation in a single prompt.

  3. 3

    $0.10 / $0.50 pricing tier

    For prompts up to 100k tokens, pricing is $0.10 input and $0.50 output per million tokens. Prompts over 100k cost $0.50 input and $2.50 output.

  4. 4

    $0.01 prompt caching read

    Cache reads drop to $0.01 / MTok ($0.05 above 100k), offering an estimated 75% cost reduction compared to Claude Haiku 4.5.

  5. 5

    Fast summaries, distinct from audio transcription

    Haiku 5.5 excels at textual summarization and routing, but requires pre-processed transcripts. BibiGPT provides the multimedia audio/video bridge.

3 typical scenarios for BibiGPT users

How lightweight model breakthroughs combine with end-to-end video note workflows.

You follow weekly technical podcasts

US listeners average 8.4 hours of weekly audio across 6.8 podcasts (Edison 2026). Feed episodes through BibiGPT to generate timestamped chapter breakdowns before deciding where to dive deep.

You juggle back-to-back team meetings

Knowledge workers average 21.7 meetings weekly, consuming ~30% of work hours (Laxis 2026). BibiGPT archives team calls into searchable meeting minutes with action items, speakers, and quotes.

You study video lectures and courses

Paste YouTube, Bilibili, or Zoom lecture URLs into BibiGPT. Receive instant bilingual outlines, key concepts, and exported Markdown notes ready for your second brain.

Related BibiGPT pages

Explore related model updates, comparison guides, and AI productivity tools.

Sources & References

Launch details verified from official releases and research reports as of 2026-10-16.

  • On 2026-10-07 Anthropic released Claude Haiku 5.5 (claude-haiku-5-5). At prompts of 100k tokens or fewer: input $0.10 / output $0.50 per million tokens, cache read $0.01, cache write $0.125. Above 100k: input $0.50 / output $2.50, cache read $0.05, cache write $0.625. Context 1M, max output 128K. The announcement lists high-volume summaries, compaction, classification, extraction, routing, and subagents. It does not list audio or video URLs as an input.

    Anthropic — Claude Haiku 5.5 Model Card (2026-10-07) ↗
  • Knowledge workers attend 21.7 meetings a week, about 30% of the work week (Laxis State of Meetings 2026).

    Laxis — State of Meetings 2026 ↗
  • US podcast listeners average 8 hours 24 minutes a week and follow 6.8 shows. Time-poor users need triage desks rather than raw transcripts.

    Edison Research — The Infinite Dial 2026 ↗

What is Claude Haiku 5.5?

What is Claude Haiku 5.5?

Claude Haiku 5.5 is Anthropic's high-speed, cost-efficient model released on 2026-10-07. It features a 1M token context window, 128K max output, and pricing of $0.10 input / $0.50 output per million tokens under 100k, with prompt caching reads at $0.01.

Loved by creators, students & researchers

Why people use BibiGPT to turn videos into text every day.

Trusted by 50,000+ users worldwide

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“I paste a link and get clean captions in seconds — it saves me hours of retyping every single week.”

Maya R.

Content Creator · Repurposes short videos

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“Exporting the transcript lets me review new words at my own pace instead of pausing the video constantly.”

Daniel K.

Language Learner · Studies with real videos

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“Accurate, timestamped text I can quote directly. It has quietly become part of my daily workflow.”

Priya S.

Researcher · Cites public talks

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