Head-to-Head Model Comparison

o4-mini vs Claude Haiku 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책

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o4-miniProfile

Claude Haiku 5.5Profile

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OpenAI

o4-mini

심층 추론 및 논리 엔진

OpenAI의 o4-mini 모델은 심층 논리 추론, 고급 수학 문제 해결 및 다단계 과학적 분석에 최적화된 AI 모델로, 200K 컨텍스트 윈도우, 초당 105 토큰의 생성 속도, 종합 지능 지수 50/100점(1M 토큰당 입력 $1.1 / 출력 $4.4)을 제공합니다.

Intelligence Index50 / 100

Input Token:

$1.10 / 1M

Output Token:

$4.40 / 1M

Context Window:

200K tokens

SWE-bench Verified:

57.5%

Anthropic

Claude Haiku 5.5

초고속 저지연 추론 모델

Anthropic의 Claude Haiku 5.5 모델은 초저지연 실시간 대화, 고속 라우팅 및 대규모 트래픽 처리에 최적화된 AI 모델로, 200K 컨텍스트 윈도우, 초당 160 토큰의 생성 속도, 종합 지능 지수 62/100점(1M 토큰당 입력 $1 / 출력 $5)을 제공합니다.

Intelligence Index62 / 100

Input Token:

$1.00 / 1M

Output Token:

$5.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

68.4%

한눈에 보는 핵심 차이점

o4-mini is 1.0x cheaper for API usage (input + output tokens combined).
Claude Haiku 5.5 is faster at 160 tok/s vs 105 tok/s.
Claude Haiku 5.5 leads on SWE-bench coding (68.4% vs 57.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	o4-mini	Claude Haiku 5.5
Intelligence Index Composite reasoning & knowledge score (0-100)	50	62
Provider	OpenAI	Anthropic
Input Price Cost per million input tokens	$1.10 / 1M	$1.00 / 1M
Output Price Cost per million output tokens	$4.40 / 1M	$5.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.85 / 1M	$0.77 / 1M
Context Window Maximum input + output tokens	200K tokens~300 A4 pages of text	200K tokens~300 A4 pages of text
Max Output Tokens Per single request	100K	64K
Throughput Speed Tokens generated per second	105 tok/s	160 tok/s
SWE-bench Verified Real-world software engineering	57.5%	68.4%
GPQA Diamond Graduate-level reasoning	73%	69.8%
Cached Input Price Prompt caching discount per 1M tokens	$0.28 / 1M	$0.10 / 1M

부문별 우위 모델

At-a-glance decision framework

Coding

Claude Haiku 5.5

+10.9% SWE-bench lead

Cost

o4-mini

1.0x cheaper monthly runtime

Speed

Claude Haiku 5.5

+52% faster generation

Context

Tied

200K tokens window

검증된 벤치마크 점수 비교

Official evaluation metrics verified by independent third-party research labs.

o4-miniClaude Haiku 5.5

SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

57.5%vs68.4%

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

73%vs69.8%

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

83%vs83.2%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1325ptsvs1370pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

11.2%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

36%vsN/A

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

38.5%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65%vsN/A

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

89.5%vsN/A

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

74.5%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs160 tok/s

지연 시간(Latency) 및 응답 속도

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

o4-mini1.80s

Claude Haiku 5.50.22s

Est. End-to-End Response (500 tokens)TTFT + generation time

o4-mini6.56s

Claude Haiku 5.53.35s

실시간 API 토큰 비용 시뮬레이터

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

o4-mini Monthly API Bill

$6.02 / month

$1.1/1M in · $4.4/1M out

Claude Haiku 5.5 Monthly API Bill

$6.15 / month

$1/1M in · $5/1M out

o4-mini saves approximately $0.13 / month (2%) under this workload.1.0x Savings

o4-mini · Strengths & Key Advantages

200K 컨텍스트 윈도우 및 최대 100K 출력 토큰 생성 지원 (SWE-bench Verified 57.5% · GPQA Diamond 73%)
초당 105 토큰의 빠른 처리 속도와 1800ms에 불과한 첫 토큰 지연 시간(TTFT)
합리적인 API 요금 체계(1M 토큰당 입력 $1.1 / 출력 $4.4)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원

Considerations & Trade-offs

독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Claude Haiku 5.5 · Strengths & Key Advantages

200K 컨텍스트 윈도우 및 최대 64K 출력 토큰 생성 지원 (SWE-bench Verified 68.4% · GPQA Diamond 69.8%)
초당 160 토큰의 빠른 처리 속도와 220ms에 불과한 첫 토큰 지연 시간(TTFT)
합리적인 API 요금 체계(1M 토큰당 입력 $1 / 출력 $5)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원

Considerations & Trade-offs

독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	o4-mini	Claude Haiku 5.5
Cost per Task Estimated USD to finish one task	$0.72	$0.70
Output Tokens / Task Tokens generated per task	45K	20K
Reasoning Tokens / Task Thinking tokens burned per task	25K	10K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

Feature	o4-mini	Claude Haiku 5.5
Official API Model ID (SDK)	o4-mini	claude-haiku-5-5-20261001
API Protocol	OpenAI Responses API & Chat Completions v1	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2025-04	2026-10
Knowledge Cutoff	June 2024	August 2026
Architecture	Compact reasoning transformer	Ultra-Fast Lightweight Reasoning Transformer
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($1.1/1M in) across full 200K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Automatic prefix caching at $0.275/1M (no extra cache-write fee)	$0.1/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Native Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	OpenAI Preparedness Framework Audited & System Card Published	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision	text, vision
Output Modalities	text	text

o4-mini vs Claude Haiku 5.5: 핵심 요약 문답 (FAQ)

Which is more intelligent, o4-mini or Claude Haiku 5.5?

Claude Haiku 5.5 is more intelligent. It scores 62 compared with 50 on the composite Intelligence Index.

Which model is faster?

Claude Haiku 5.5 is faster, generating 160 tokens per second compared with 105 tokens per second.

Which model is cheaper to run?

Claude Haiku 5.5 is cheaper at $0.77 per 1M tokens blended, compared with $0.85 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Haiku 5.5 has lower latency, with a time to first token of 0.22s compared with 1.80s.

종합 평가

o4-mini(심층 논리 추론, 고급 수학 문제 해결 및 다단계 과학적 분석, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.)와 Claude Haiku 5.5(초저지연 실시간 대화, 고속 라우팅 및 대규모 트래픽 처리, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.) 모두 뛰어난 성능을 자랑합니다. 고난도 추론과 코딩 벤치마크에서는 Claude Haiku 5.5가 앞서며, 토큰 생성 속도에서는 Claude Haiku 5.5가 빠르고, 대규모 API 운영 비용 면에서는 Claude Haiku 5.5가 더 경제적입니다.

자주 묻는 질문 (FAQ)

코딩과 복잡한 추론에는 o4-mini와 Claude Haiku 5.5 중 어느 모델이 더 나은가요?+

종합 지능 지수 및 코딩 벤치마크에서는 Claude Haiku 5.5가 우위를 보입니다. 상단의 SWE-bench 및 GPQA 점수를 함께 확인해 보세요.

o4-mini와 Claude Haiku 5.5의 API 요금 차이는 얼마인가요?+

o4-mini는 100만 토큰당 입력 $1.10 / 출력 $4.40이며, Claude Haiku 5.5는 입력 $1.00 / 출력 $5.00입니다. 혼합 비용 기준으로는 Claude Haiku 5.5가 더 저렴합니다.

어느 모델이 더 큰 컨텍스트 윈도우와 빠른 속도를 제공하나요?+

컨텍스트 길이는 o4-mini가 200K 토큰, Claude Haiku 5.5가 200K 토큰를 지원하며, 출력 속도 면에서는 Claude Haiku 5.5가 더 빠릅니다.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

o4-mini vs Claude Haiku 5.5

원하는 AI 모델 선택 및 실시간 비교

o4-mini

Claude Haiku 5.5

부문별 우위 모델

검증된 벤치마크 점수 비교

지연 시간(Latency) 및 응답 속도

실시간 API 토큰 비용 시뮬레이터

o4-mini · Strengths & Key Advantages

Considerations & Trade-offs

Claude Haiku 5.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

기술 사양 (Specifications)

o4-mini vs Claude Haiku 5.5: 핵심 요약 문답 (FAQ)

종합 평가

자주 묻는 질문 (FAQ)

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