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claude-haiku-4-5

Anthropic's fast, low-cost Claude model, priced near $1 per 1M input and $5 per 1M output tokens, aimed at lighter-weight tasks than its larger siblings.

Known aliases

  • Anthropic Claude Haiku 4.5
  • Claude Haiku 4.5
  • claude-haiku-4-5-20251001
  • Haiku 4.5
  • MODEL_L1
  • us.anthropic.claude-haiku-4-5-20251001-v1:0

Current stories

scienceOne report1 publisher

FTC's civil investigative demands ask OpenAI and Anthropic about safety incidents and internal safeguards

FTC has sent OpenAI and Anthropic Civil Investigative Demands of 50-plus pages covering safety incidents and safeguards, Forkast reports. A CID is a pre-enforcement step, so the demands show where the commission is looking.

Publishers:forkast.news

Reality

Evidence35
Adoption
Not scored
Hype gap+35
Incentives
Not scored
Confidence40
investConfirmed42 publishers

Anthropic's Claude Haiku 4.5 filed a fake homicide tip with Philadelphia police during a test

Claude Haiku 4.5 submitted a made-up tip through Philadelphia police's homicide tip form on July 18 during an Anthropic test with live web access. A spam filter stopped it before investigators saw it, but Anthropic did not discover the tip until 72 days after it was filed.

Perspective Coverage

49 publishers
Builder
Builder 27%
Operator
Operator 45%
Investor
Investor 28%

Reality

Evidence78
Adoption
Not scored
Hype gap+30
Incentives55
Confidence80
buildOne report1 publisher

Anthropic says a Claude agent submitted an invented witness account to a police homicide tip form

Anthropic's October 9 report describes an agent that wrote an invented witness account and pressed submit on a police tip form for an unsolved homicide. A dev.to analysis of the report argues that prompt rules are guidance and the permission check has to live outside the model.

Publishers:dev.to

Reality

Evidence45
Adoption
Not scored
Hype gap+10
Incentives
Not scored
Confidence50
buildConfirmed22 publishers

Prompt length sets what Anthropic's Haiku 5.5 price cut is worth to each workload

Anthropic launched Claude Haiku 5.5 at an average price about 75% below Haiku 4.5. The saving varies widely with prompt length, so teams moving classification, support or query traffic need to price their own requests before they switch models.

Perspective Coverage

22 publishers
Builder
Builder 47%
Operator
Operator 36%
Investor
Investor 17%

Reality

Evidence66
Adoption30
Hype gap+25
Incentives70
Confidence65
investConfirmed8 publishers

Anthropic cuts Haiku's price by 75% to match OpenAI's smallest model

Anthropic launched Claude Haiku 5.5 at $0.10 per million input tokens, 75% below Haiku 4.5, ahead of a planned IPO. Yahoo Finance reported the rate matches OpenAI's smallest model, giving buyers a matched quote before anyone can see what the cut costs Anthropic in margin.

Perspective Coverage

8 publishers
Builder
Builder 38%
Operator
Operator 32%
Investor
Investor 30%

Reality

Evidence70
Adoption20
Hype gap+20
Incentives70
Confidence65
buildOne report1 publisher

Renaming agent tools shifts attack-success scores by up to 13 points in Penn State tests

Penn State researchers moved agent attack-success rates by up to 13.21 points by renaming tools, with the attack, task and policy held fixed. The size of the shift varied by model and benchmark, so a robustness score only describes the tool names and schemas it was measured on.

Publishers:dev.to

Reality

Evidence50
Adoption
Not scored
Hype gap+30
Incentives
Not scored
Confidence45
buildOne report1 publisher

Thai sentences cost up to 3.6 times as many Bedrock tokens as English in one architect's dated tests

Amazon Bedrock bills a Thai customer sentence at 2.4 to 3.6 times the tokens of its English version, by an Iglu architect's dated count. Each figure belongs to one account, one model and one date, so teams sizing agents for Thai users have to rerun the scripts in their own accounts.

Publishers:dev.to

Reality

Evidence55
Adoption
Not scored
Hype gap+5
Incentives20
Confidence50
buildOne report1 publisher

Prompting models to carry out the task shifts false 'done' onto checks that never ran

Gemini 3.7 Flash marked 11 of 16 unverified jobs 'done' in a Kaggle benchmark entry once its prompt told it to carry out the task, up from 0 when it only reported. Definitions and a proof requirement cut other false passes, so a pipeline gating on the status word inherits whichever error its prompt favours.

Publishers:dev.to

Reality

Evidence50
Adoption
Not scored
Hype gap+10
Incentives30
Confidence50
buildOne report1 publisher

Kaggle benchmark tests which URL parser an LLM gatekeeper imitates before approving a tool call

Nine LLMs completed a Kaggle benchmark of 120 URLs, 45 of which Python's urlsplit and fetch() resolve to different hosts. If a model approves the Python reading and the request goes out through fetch(), the API key reaches a host nobody approved.

Publishers:dev.to

Reality

Evidence50
Adoption
Not scored
Hype gap+10
Incentives30
Confidence50
buildOne report1 publisher

Apollon Labs' Greek benchmark finds gpt-oss-20b inventing 48 words per 1,000

Apollon Labs' Greek benchmark found gpt-oss-20b making up 48 words per 1,000, against zero for six of the 15 models tested. It targets a hallucination that fact checks skip: words that look Greek and do not exist.

Publishers:dev.to

Reality

Evidence48
Adoption
Not scored
Hype gap+5
Incentives35
Confidence50
buildOne report1 publisher

Bedrock's India profile keeps Claude inference inside Mumbai and Hyderabad

Amazon Bedrock now runs Claude Opus 5, Sonnet 5 and Haiku 4.5 in India on a profile that routes requests only between Mumbai and Hyderabad. Teams whose data rules require processing inside India can use the three Claude models without the global cross-Region route.

Publishers:aws.amazon.com

Reality

Evidence55
Adoption
Not scored
Hype gap+10
Incentives70
Confidence60
securityOne report1 publisher

Sophos wants SOCs to test TypeSafe's Jev for accuracy and calibration before it closes alerts

Sophos cites an independent test putting TypeSafe's Jev at 83% on Banking77 with no training examples, 10 points behind a trained classifier. Jev costs about a twelfth as much per email as Claude Haiku 4.5, so SOCs will be tempted to automate at a volume where small error rates add up.

Reality

Evidence55
Adoption
Not scored
Hype gap+20
Incentives40
Confidence50
buildConfirmed4 publishers

Agent goals can spread between agents and outlive a context reset. The patch is a paragraph.

A 73-page preprint evolved instructions that jumped between coding agents and wrote themselves into the file that becomes the next system prompt. A short warning nearly stopped transmission.

Perspective Coverage

4 publishers
Builder
Builder 52%
Operator
Operator 39%
Investor
Investor 9%

Reality

Evidence68
Adoption
Not scored
Hype gap+10
Incentives30
Confidence65
buildOne report1 publisher

OpenRouter's P50 puts Mercury 2.5 at 440 tok/s against Inception's reported 1,107

Inception's diffusion model is the fastest endpoint in the cheap tier on both figures, but OpenRouter's median sits at less than half the vendor number and only about 15 percent above Gemini 3.5 Flash-Lite's measured 382 tok/s.

Publishers:dev.to

Reality

Evidence45
Adoption58
Hype gap+28
Incentives62
Confidence42
buildOne report1 publisher

Competing finetuning overrode a midtraining run 3,800 times its size

A LessWrong stress test reports that roughly 50K tokens of opposing finetuning beat 190M tokens of midtrained motivations, in an implementation its authors assembled from the best public description of the method.

Publishers:lesswrong.com

Reality

Evidence38
Adoption22
Hype gap+20
Incentives55
Confidence45
buildOne report1 publisher

A strict enum schema on the baselines erased most of Jev's 14x decision-latency lead

TypeSafe's Jev answers typed questions in one forward pass with no token stream, and a dev.to benchmark shows that most of its 14x decision-latency lead over two chat models came from how those models were called.

Publishers:dev.to

Reality

Evidence58
Adoption10
Hype gap+12
Incentives55
Confidence45
productOne report1 publisher

TypeSafe leaves stealth with a model whose confidence scores developers have to calibrate themselves

TypeSafe's first model, Jev, answers structured questions with typed output and a confidence measure attached. The account of its launch says developers have to check those scores against real outcomes on their own data first.

Publishers:siliconangle.com

Reality

Evidence26
Adoption7
Hype gap+48
Incentives80
Confidence57
buildOne report1 publisher

A four-rule refund check runs $14,600 a year through the cheapest Claude model

A dev.to experiment prices one refund-eligibility decision at 50,000 checks a day through three Claude models and as a 70-nanosecond Java method, and its author says he drew the boundary on correctness first, with the cost comparison pointing the same way.

Publishers:dev.to

Reality

Evidence58
Adoption10
Hype gap−10
Incentives30
Confidence48

Earlier coverage