Head-to-Head Model Comparison

Claude 3.5 Haiku vs Claude 3 Haiku

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude 3.5 Haiku vs Claude 3 Haiku: Benchmarks, Pricing & Speed Comparison

Claude 3.5 Haiku by Anthropic and Claude 3 Haiku by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Claude 3 Haiku holds a notable pricing advantage for token ingestion. On output generation, Claude 3 Haiku is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 200K tokens. In latency-sensitive production environments, Claude 3.5 Haiku leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

1:1 모델 맞대결 비교 (VS)

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Anthropic

Claude 3.5 Haiku

고성능 AI 모델

Anthropic의 Claude 3.5 Haiku 모델은 200K 토큰 컨텍스트 윈도우와 입력 $0.8/1M 토큰, 출력 $4/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.

Intelligence Index36 / 100
Input Token:

$0.80 / 1M

Output Token:

$4.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

40.6%

Anthropic

Claude 3 Haiku

고성능 AI 모델

Anthropic의 Claude 3 Haiku 모델은 200K 토큰 컨텍스트 윈도우와 입력 $0.25/1M 토큰, 출력 $1.25/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.

Intelligence Index33 / 100
Input Token:

$0.25 / 1M

Output Token:

$1.25 / 1M

Context Window:

200K tokens

SWE-bench Verified:

10.5%

한눈에 보는 핵심 차이점

  • Claude 3 Haiku is 3.2x cheaper for API usage (input + output tokens combined).
  • Claude 3.5 Haiku is faster at 130 tok/s vs 125 tok/s.
  • Claude 3.5 Haiku leads on SWE-bench coding (40.6% vs 10.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude 3.5 HaikuClaude 3 Haiku
Intelligence Index
Composite reasoning & knowledge score (0-100)
3633
Provider
AnthropicAnthropic
Input Price
Cost per million input tokens
$0.80 / 1M$0.25 / 1M
Output Price
Cost per million output tokens
$4.00 / 1M$1.25 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.62 / 1M$0.19 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
8K4K
Throughput Speed
Tokens generated per second
130 tok/s125 tok/s
SWE-bench Verified
Real-world software engineering
40.6%10.5%
GPQA Diamond
Graduate-level reasoning
41.6%33%
Cached Input Price
Prompt caching discount per 1M tokens
$0.08 / 1M$0.03 / 1M

부문별 우위 모델

At-a-glance decision framework
Coding
Claude 3.5 Haiku
+30.1% SWE-bench lead
Cost
Claude 3 Haiku
3.2x cheaper monthly runtime
Speed
Claude 3.5 Haiku
+4% faster generation
Context
Tied
200K tokens window

검증된 벤치마크 점수 비교

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

Claude 3.5 HaikuClaude 3 Haiku
SWE-bench Verified (Autonomous Coding)

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

40.6%vs10.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

41.6%vs33%
MMLU-Pro (Multi-task Language Understanding)

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

69.2%vs61.2%
LMSYS Chatbot Arena Elo

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

1260ptsvs1175pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

6.7%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

26.8%vsN/A
SciCode (Scientific Computing)

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

24.4%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

43.6%vsN/A
AIME (Advanced Math Competition)

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

47.8%vsN/A
Long-Context Reasoning

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

62.3%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs125 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
Claude 3.5 Haiku0.38s
Claude 3 Haiku0.35s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude 3.5 Haiku4.23s
Claude 3 Haiku4.35s

실시간 API 토큰 비용 시뮬레이터

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

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Claude 3.5 Haiku Monthly API Bill
$4.92 / month
$0.8/1M in · $4/1M out
Claude 3 Haiku Monthly API Bill
$1.54 / month
$0.25/1M in · $1.25/1M out
Claude 3 Haiku saves approximately $3.38 / month (69%) under this workload.3.2x Savings

Claude 3.5 Haiku · Strengths & Key Advantages

  • Anthropic의 첨단 Optimized Lightweight Transformer 아키텍처와 최대 200K 토큰 컨텍스트 지원
  • 경쟁력 있는 API 가격(입력 $0.8/1M, 출력 $4/1M)과 빠른 응답 속도
  • 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
  • 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
  • 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨

Claude 3 Haiku · Strengths & Key Advantages

  • Anthropic의 첨단 Compact High-Throughput Transformer 아키텍처와 최대 200K 토큰 컨텍스트 지원
  • 경쟁력 있는 API 가격(입력 $0.25/1M, 출력 $1.25/1M)과 빠른 응답 속도
  • 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
  • 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
  • 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨

Token Use & Task Economics

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

MetricClaude 3.5 HaikuClaude 3 Haiku
Cost per Task
Estimated USD to finish one task
$0.90$0.20
Output Tokens / Task
Tokens generated per task
45K24K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

FeatureClaude 3.5 HaikuClaude 3 Haiku
Official API Model ID (SDK)claude-3-5-haiku-20241101claude-3-haiku-20240301
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2024-112024-03
Knowledge CutoffJuly 2024August 2023
ArchitectureOptimized Lightweight TransformerCompact High-Throughput Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL$0.08/1M cached read (90% off); 5-min default & 1-hour extended TTL$0.025/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search Citations + Code Execution Tool + MCP ConnectorsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText 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 VRAMCloud-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 ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedAnthropic 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 TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Claude 3.5 Haiku vs Claude 3 Haiku: 핵심 요약 문답 (FAQ)

Which is more intelligent, Claude 3.5 Haiku or Claude 3 Haiku?

Claude 3.5 Haiku is more intelligent. It scores 36 compared with 33 on the composite Intelligence Index.

Which model is faster?

Claude 3.5 Haiku is faster, generating 130 tokens per second compared with 125 tokens per second.

Which model is cheaper to run?

Claude 3 Haiku is cheaper at $0.19 per 1M tokens blended, compared with $0.62 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude 3 Haiku has lower latency, with a time to first token of 0.35s compared with 0.38s.

종합 평가

Verdict & Model Selection Recommendation: Choose Claude 3.5 Haiku if your priority is Rapid customer support chatbots, data extraction agents, and interactive tool-using loops. Its performance in demanding tasks justifies its operational token cost. Choose Claude 3 Haiku if your workflow prioritizes Real-time customer chat, instant content moderation, and high-frequency document triage. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

자주 묻는 질문 (FAQ)

How does Claude 3.5 Haiku compare to Claude 3 Haiku in API token pricing and cost per token?+

Claude 3.5 Haiku costs $0.80 per 1M input tokens and $4.00 per 1M output tokens, whereas Claude 3 Haiku costs $0.25 input and $1.25 output. Overall, Claude 3 Haiku is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Claude 3.5 Haiku or Claude 3 Haiku?+

Both Claude 3.5 Haiku and Claude 3 Haiku offer an identical context window of 200K tokens (~150k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.

Which AI model is better for software engineering and coding: Claude 3.5 Haiku or Claude 3 Haiku?+

Claude 3.5 Haiku scores 40.6% on SWE-bench Verified while Claude 3 Haiku scores 10.5%. For autonomous software engineering and multi-file debugging, Claude 3.5 Haiku holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Claude 3.5 Haiku and Claude 3 Haiku?+

Claude 3.5 Haiku is optimized for low-latency direct generation. In contrast, Claude 3 Haiku focuses on standard fast inference.

How does inference speed (tokens per second) compare between Claude 3.5 Haiku and Claude 3 Haiku?+

Claude 3.5 Haiku generates approximately 130 tokens per second, while Claude 3 Haiku delivers 125 tokens per second. In latency-sensitive production environments, Claude 3.5 Haiku provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Claude 3.5 Haiku and Claude 3 Haiku to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude 3 Haiku to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude 3.5 Haiku. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
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