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Claude 3.5 Haiku vs Claude Haiku 4.5

Compare Claude 3.5 Haiku and Claude Haiku 4.5 side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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AnthropicClaude 3.5 Haiku

Claude 3.5 Haiku is deprecated and can no longer be run. Details and evals are still available on its model page.

AnthropicClaude Haiku 4.5
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Claude 3.5 Haiku vs Claude Haiku 4.5: Overview

Claude 3.5 Haiku

Claude 3.5 Haiku, released by Anthropic in October 2024, is the fastest member of the Claude 3.5 family, optimized for low-latency, high-throughput applications. It is a multimodal model that handles both text and image inputs and supports a large ~200,000-token context window. Haiku is designed to balance efficiency with intelligence, outperforming even Claude 3 Opus on several reasoning benchmarks while maintaining its hallmark speed.

Typical applications include real-time chatbots, code completion, large-scale data extraction, and content moderation—scenarios where rapid response and scalability are essential.

Claude Haiku 4.5

Claude Haiku 4.5 is Anthropic’s lightweight model in the Claude 4.5 series, released in October 2025 under a proprietary license. Designed for speed and cost efficiency, it delivers near-frontier performance while maintaining Anthropic’s AI Safety Level 2 standard. Haiku 4.5 supports both text and multimodal (text and image) inputs, integrates tool use and extended reasoning, and features a 200,000 token context window, making it adept at handling long or complex workflows. Though the parameter count remains undisclosed, it achieves about 73.3% on SWE-bench Verified, reflecting strong coding and reasoning ability. Haiku 4.5 is ideal for developers and researchers seeking rapid, cost-effective model calls for analysis, coding, or multimodal understanding.

Claude 3.5 Haiku vs Claude Haiku 4.5 Comparison Table

PropertyClaude 3.5 HaikuClaude Haiku 4.5
OrganizationAnthropicAnthropic
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateOct 2024Oct 2025
Context Window200K200K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.00
Output $/1M$5.00
Vision Tasks
CaptioningDemo
ClassificationDemo
Object DetectionDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
58.21%
Avg Response Time3.15s
Median input tokensincl. image tokens2.2K
Median output tokens174
Est. cost / taskon this benchmark$0.0030
Defect Detection
80%(12/15)
Document Understanding
77.8%(7/9)
Object Counting
0%(0/10)
Object Understanding
71.4%(10/14)
Spatial Understanding
52.6%(10/19)
OCR
Overall Score
61.57%
Avg Response Time2.13s
Median input tokensincl. image tokens735
Median output tokens101
Est. cost / taskon this benchmark$0.0012
Focused Scene OCR
61.6%(61/99)
Handwritten Math
20%(2/10)
License Plate Recognition
66.7%(20/30)
Text Recognition
63.3%(19/30)
VQA & Extraction
65%(39/60)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology