Head-to-Head Model Comparison

Claude Sonnet 4.5 vs Claude Haiku 4.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial

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Claude Sonnet 4.5Profile

Claude Haiku 4.5Profile

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Popular Matchups:

Anthropic

Claude Sonnet 4.5

Modelo Insignia de Frontera

Claude Sonnet 4.5 de Anthropic es un modelo de IA diseñado para razonamiento empresarial de frontera, programación avanzada y flujos de producción, con ventana de contexto de 1M, velocidad de 90 tokens/s, índice de inteligencia de 91/100 y

Intelligence Index91 / 100

Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

77.8%

Anthropic

Claude Haiku 4.5

Inferencia Ultrarrápida

Claude Haiku 4.5 de Anthropic es un modelo de IA diseñado para interacción en tiempo real, baja latencia y enrutamiento de alto volumen, con ventana de contexto de 200K, velocidad de 140 tokens/s, índice de inteligencia de 54/100 y tarifa d

Intelligence Index54 / 100

Input Token:

$1.00 / 1M

Output Token:

$5.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

58.2%

Diferencias Clave de un Vistazo

Claude Haiku 4.5 is 3.0x cheaper for API usage (input + output tokens combined).
Claude Sonnet 4.5 has a larger context window (1M vs 200K tokens).
Claude Haiku 4.5 is faster at 140 tok/s vs 90 tok/s.
Claude Sonnet 4.5 leads on SWE-bench coding (77.8% vs 58.2%).

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

Característica	Claude Sonnet 4.5	Claude Haiku 4.5
Intelligence Index Composite reasoning & knowledge score (0-100)	91	54
Provider	Anthropic	Anthropic
Input Price Cost per million input tokens	$3.00 / 1M	$1.00 / 1M
Output Price Cost per million output tokens	$15.00 / 1M	$5.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.31 / 1M	$0.77 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 A4 pages of text	200K tokens~300 A4 pages of text
Max Output Tokens Per single request	64K	64K
Throughput Speed Tokens generated per second	90 tok/s	140 tok/s
SWE-bench Verified Real-world software engineering	77.8%	58.2%
GPQA Diamond Graduate-level reasoning	70.2%	62.1%
Cached Input Price Prompt caching discount per 1M tokens	$0.30 / 1M	$0.10 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Claude Sonnet 4.5

+19.6% SWE-bench lead

Costo

Claude Haiku 4.5

3.0x cheaper monthly runtime

Velocidad

Claude Haiku 4.5

+56% faster generation

Contexto

Claude Sonnet 4.5

1M tokens window

Puntuaciones de Benchmarks Verificadas

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

Claude Sonnet 4.5Claude Haiku 4.5

SWE-bench Verified (Autonomous Coding)

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

77.8%vs58.2%

GPQA Diamond (Doctorate-Level Science & Math)

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

70.2%vs62.1%

MMLU-Pro (Multi-task Language Understanding)

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

84.5%vs79.5%

LMSYS Chatbot Arena Elo

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

1355ptsvs1324pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

10.4%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

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

50.1%vsN/A

SciCode (Scientific Computing)

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

43.9%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

72.6%vsN/A

AIME (Advanced Math Competition)

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

84.7%vsN/A

Long-Context Reasoning

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

74.8%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs140 tok/s

Latencia y Tiempo de Respuesta

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 Sonnet 4.50.90s

Claude Haiku 4.50.28s

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

Claude Sonnet 4.56.46s

Claude Haiku 4.53.85s

Simulador Interactivo de Costos de Tokens

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)

Claude Sonnet 4.5 Monthly API Bill

$18.45 / month

$3/1M in · $15/1M out

Claude Haiku 4.5 Monthly API Bill

$6.15 / month

$1/1M in · $5/1M out

Claude Haiku 4.5 saves approximately $12.30 / month (67%) under this workload.3.0x Savings

Claude Sonnet 4.5 · Strengths & Key Advantages

Ventana de contexto de 1M con hasta 64K tokens de salida máxima (SWE-bench Verified 77.8% · GPQA Diamond 70.2%)
Rendimiento ágil de 90 tokens/segundo con latencia inicial (TTFT) de solo 900 ms
Economía de API competitiva ($3/$15 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos

Claude Haiku 4.5 · Strengths & Key Advantages

Ventana de contexto de 200K con hasta 64K tokens de salida máxima (SWE-bench Verified 58.2% · GPQA Diamond 62.1%)
Rendimiento ágil de 140 tokens/segundo con latencia inicial (TTFT) de solo 280 ms
Economía de API competitiva ($1/$5 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Token Use & Task Economics

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

Metric	Claude Sonnet 4.5	Claude Haiku 4.5
Cost per Task Estimated USD to finish one task	$2.10	$0.70
Output Tokens / Task Tokens generated per task	55K	20K
Reasoning Tokens / Task Thinking tokens burned per task	30K	10K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Claude Sonnet 4.5 vs Claude Haiku 4.5: Respuestas Rápidas (FAQ)

Which is more intelligent, Claude Sonnet 4.5 or Claude Haiku 4.5?

Claude Sonnet 4.5 is more intelligent. It scores 91 compared with 54 on the composite Intelligence Index.

Which model is faster?

Claude Haiku 4.5 is faster, generating 140 tokens per second compared with 90 tokens per second.

Which model is cheaper to run?

Claude Haiku 4.5 is cheaper at $0.77 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Haiku 4.5 has lower latency, with a time to first token of 0.28s compared with 0.90s.

Which model has a larger context window?

Claude Sonnet 4.5 has a larger context window, supporting 1M tokens compared with 200K tokens.

Veredicto

Tanto Claude Sonnet 4.5 (Ideal para razonamiento empresarial de frontera, programación avanzada y flujos de producción, sistemas RAG empresariales y automatización mediante API.) como Claude Haiku 4.5 (Ideal para interacción en tiempo real, baja latencia y enrutamiento de alto volumen, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Claude Sonnet 4.5 lidera en inteligencia general y programación, Claude Haiku 4.5 ofrece mayor velocidad de generación de tokens y Claude Haiku 4.5 resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Claude Sonnet 4.5 o Claude Haiku 4.5?+

En las pruebas de inteligencia compuesta y resolución de código, Claude Sonnet 4.5 obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Claude Sonnet 4.5 frente a Claude Haiku 4.5?+

Claude Sonnet 4.5 cuesta $3.00 / $15.00 por millón de tokens de entrada/salida, mientras que Claude Haiku 4.5 cuesta $1.00 / $5.00. En costo combinado, Claude Haiku 4.5 es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

Claude Sonnet 4.5 cuenta con 1M tokens de contexto frente a 200K tokens de Claude Haiku 4.5. En velocidad de inferencia, Claude Haiku 4.5 ofrece un rendimiento superior.

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)

Característica	Claude Sonnet 4.5	Claude Haiku 4.5
Official API Model ID (SDK)	claude-sonnet-4-5-20251101	claude-haiku-4-5-20251001
API Protocol	Anthropic Messages API + AWS Bedrock + Vertex AI	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2025-11	2025-10
Knowledge Cutoff	March 2025	July 2025
Architecture	Hybrid Reasoning	Lightweight High-Speed Multimodal Transformer
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM	4,000 – 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 tokens	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL	$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 Citations + Code Execution Tool + MCP Connectors	Native Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	Custom Model Tuning via Amazon Bedrock & Prompt Distillation	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	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated	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

Claude Sonnet 4.5 vs Claude Haiku 4.5

Cambia y Compara Cualquier Modelo

Claude Sonnet 4.5

Claude Haiku 4.5

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Claude Sonnet 4.5 · Strengths & Key Advantages

Considerations & Trade-offs

Claude Haiku 4.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Claude Sonnet 4.5 vs Claude Haiku 4.5: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

Related reading