Browse all Anthropic text models
Provider logo

Claude Haiku 4.5 Thinking

anthropic/claude-haiku-4.5:thinking
Provider logo

Claude Haiku 4.5 Thinking

anthropic/claude-haiku-4.5:thinking

Claude Haiku 4.5 with extended thinking enabled for deeper planning, more deliberate coding, and multi-step reasoning without moving up to Sonnet pricing.

Added Oct 15, 2025

Context Window

200.0K

Max Output

64.0K

Avg output tokens (7d)

581 tokens

48%

Input Price (Auto)

$1.00/1M

Output Price (Auto)

$5.00/1M

Cache Read (Auto)

$0.10/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

17.6

Better than 64% of models compared

Coding Index

43.9

Better than 51% of models compared

Agentic Index

10.3

Better than 43% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

3.2%

Better than 28% of models compared

AA-Briefcase

Agentic knowledge work (Elo)

614 Elo

Better than 31% of models compared

GDPval-AA v2

Economically valuable tasks (Elo)

854 Elo

Better than 40% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

3.8%

Better than 25% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

74.3%

Better than 76% of models compared

Reasoning

HLE

Humanity's Last Exam

10.4%

Better than 55% of models compared

IFBench

Instruction-following benchmark

54.3%

Better than 65% of models compared

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

0.0%

Better than 18% of models compared

SciCode

Python programming for scientific computing

42.2%

Better than 34% of models compared

LiveCodeBench

Contamination-free coding benchmark

61.5%

Better than 67% of models compared

Math

AIME 2025

American Invitational Mathematics Examination 2025

83.7%

Better than 80% of models compared

Knowledge

MMLU-Pro

Professional and academic subject knowledge

76.0%

Better than 52% of models compared

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

67.2%

Better than 44% of models compared

Terminal-Bench Hard (legacy)

Agentic coding and terminal use

27.3%

Better than 69% of models compared

T²-Bench Telecom (legacy)

Conversational AI agents in dual-control scenarios

54.7%

Better than 55% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

74.3%

Better than 76% of models compared

Last updated Sep 11, 2026

Artificial Analysis

Providers

Auto routing is available for this model. Explicit provider selection is not available.

Loading provider options…

Compare Claude Haiku 4.5 Thinking with similar models from the same provider or model family.