Head-to-Head Model Comparison

Kimi K2 Thinking Turbo vs Claude Opus 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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Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Kimi K2 Thinking TurboProfile

Claude Opus 4.5Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Moonshot AI

Kimi K2 Thinking Turbo

Motor de Razonamiento Profundo

Kimi K2 Thinking Turbo de Moonshot AI es un modelo de IA diseñado para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, con ventana de contexto de 262K, velocidad de 90 tokens/s, índice de inteligenci

Intelligence Index84 / 100

Input Token:

$0.60 / 1M

Output Token:

$2.40 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

N/A

Anthropic

Claude Opus 4.5

Modelo Insignia de Frontera

Claude Opus 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 200K, velocidad de 62 tokens/s, índice de inteligencia de 63/100 y

Intelligence Index63 / 100

Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

77.2%

Diferencias Clave de un Vistazo

Kimi K2 Thinking Turbo is 9.8x cheaper for API usage (input + output tokens combined).
Kimi K2 Thinking Turbo has a larger context window (262K vs 200K tokens).
Kimi K2 Thinking Turbo is faster at 90 tok/s vs 62 tok/s.

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

Característica	Kimi K2 Thinking Turbo	Claude Opus 4.5
Intelligence Index Composite reasoning & knowledge score (0-100)	84	63
Provider	Moonshot AI	Anthropic
Input Price Cost per million input tokens	$0.60 / 1M	$5.00 / 1M
Output Price Cost per million output tokens	$2.40 / 1M	$25.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.40 / 1M	$3.85 / 1M
Context Window Maximum input + output tokens	262.1K tokens~393 A4 pages of text	200K tokens~300 A4 pages of text
Max Output Tokens Per single request	16K	64K
Throughput Speed Tokens generated per second	90 tok/s	62 tok/s
SWE-bench Verified Real-world software engineering	N/A	77.2%
GPQA Diamond Graduate-level reasoning	68.5%	74.8%
Cached Input Price Prompt caching discount per 1M tokens	$0.06 / 1M	$0.50 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Evaluations ongoing

Costo

Kimi K2 Thinking Turbo

9.8x cheaper monthly runtime

Velocidad

Kimi K2 Thinking Turbo

+45% faster generation

Contexto

Kimi K2 Thinking Turbo

262.1K tokens window

Puntuaciones de Benchmarks Verificadas

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

Kimi K2 Thinking TurboClaude Opus 4.5

SWE-bench Verified (Autonomous Coding)

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

N/Avs77.2%

GPQA Diamond (Doctorate-Level Science & Math)

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

68.5%vs74.8%

MMLU-Pro (Multi-task Language Understanding)

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

81.5%vs87.3%

LMSYS Chatbot Arena Elo

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

1365ptsvs1376pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs13.7%

Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs49.2%

SciCode (Scientific Computing)

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

N/Avs45.6%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs74.1%

AIME (Advanced Math Competition)

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

81%vs88.5%

Long-Context Reasoning

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

N/Avs79.4%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs62 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

Kimi K2 Thinking Turbo0.52s

Claude Opus 4.52.10s

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

Kimi K2 Thinking Turbo6.08s

Claude Opus 4.510.16s

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)

Kimi K2 Thinking Turbo Monthly API Bill

$3.15 / month

$0.6/1M in · $2.4/1M out

Claude Opus 4.5 Monthly API Bill

$30.75 / month

$5/1M in · $25/1M out

Kimi K2 Thinking Turbo saves approximately $27.60 / month (90%) under this workload.9.8x Savings

Kimi K2 Thinking Turbo · Strengths & Key Advantages

Ventana de contexto de 262K con hasta 16K tokens de salida máxima (GPQA Diamond 68.5% · MMLU-Pro 81.5%)
Rendimiento ágil de 90 tokens/segundo con latencia inicial (TTFT) de solo 520 ms
Economía de API competitiva ($0.6/$2.4 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

Claude Opus 4.5 · Strengths & Key Advantages

Ventana de contexto de 200K con hasta 64K tokens de salida máxima (SWE-bench Verified 77.2% · GPQA Diamond 74.8%)
Rendimiento ágil de 62 tokens/segundo con latencia inicial (TTFT) de solo 2100 ms
Economía de API competitiva ($5/$25 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

Token Use & Task Economics

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

Metric	Kimi K2 Thinking Turbo	Claude Opus 4.5
Cost per Task Estimated USD to finish one task	$0.18	$5.86
Output Tokens / Task Tokens generated per task	22K	73K
Reasoning Tokens / Task Thinking tokens burned per task	10K	43K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	Kimi K2 Thinking Turbo	Claude Opus 4.5
Official API Model ID (SDK)	kimi-k2-thinking-turbo	claude-opus-4-5-20251101
API Protocol	Moonshot AI REST API (OpenAI-Compatible)	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2025-11	2025-11
Knowledge Cutoff	September 2025	March 2025
Architecture	Hosted Accelerated Reasoning Engine	Hybrid Reasoning
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 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 ($0.6/1M in) across full 262K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Cached input at $0.06/1M tokens	$0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Native Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	API Prompt Engineering & RAG Distillation	Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token Billing	Text BPE (~4 chars/token)	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	Moonshot AI Production Safety & Alignment Verified	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	text, vision
Output Modalities	text	text

Kimi K2 Thinking Turbo vs Claude Opus 4.5: Respuestas Rápidas (FAQ)

Which is more intelligent, Kimi K2 Thinking Turbo or Claude Opus 4.5?

Kimi K2 Thinking Turbo is more intelligent. It scores 84 compared with 63 on the composite Intelligence Index.

Which model is faster?

Kimi K2 Thinking Turbo is faster, generating 90 tokens per second compared with 62 tokens per second.

Which model is cheaper to run?

Kimi K2 Thinking Turbo is cheaper at $0.40 per 1M tokens blended, compared with $3.85 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Kimi K2 Thinking Turbo has lower latency, with a time to first token of 0.52s compared with 2.10s.

Which model has a larger context window?

Kimi K2 Thinking Turbo has a larger context window, supporting 262.1K tokens compared with 200K tokens.

Veredicto

Tanto Kimi K2 Thinking Turbo (Ideal para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, sistemas RAG empresariales y automatización mediante API.) como Claude Opus 4.5 (Ideal para razonamiento empresarial de frontera, programación avanzada y flujos de producción, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Kimi K2 Thinking Turbo lidera en inteligencia general y programación, Kimi K2 Thinking Turbo ofrece mayor velocidad de generación de tokens y Kimi K2 Thinking Turbo resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Kimi K2 Thinking Turbo o Claude Opus 4.5?+

En las pruebas de inteligencia compuesta y resolución de código, Kimi K2 Thinking Turbo obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Kimi K2 Thinking Turbo frente a Claude Opus 4.5?+

Kimi K2 Thinking Turbo cuesta $0.60 / $2.40 por millón de tokens de entrada/salida, mientras que Claude Opus 4.5 cuesta $5.00 / $25.00. En costo combinado, Kimi K2 Thinking Turbo es la opción más económica.

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

Kimi K2 Thinking Turbo cuenta con 262.1K tokens de contexto frente a 200K tokens de Claude Opus 4.5. En velocidad de inferencia, Kimi K2 Thinking Turbo 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)

Kimi K2 Thinking Turbo vs Claude Opus 4.5

Cambia y Compara Cualquier Modelo

Kimi K2 Thinking Turbo

Claude Opus 4.5

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Kimi K2 Thinking Turbo · Strengths & Key Advantages

Considerations & Trade-offs

Claude Opus 4.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Kimi K2 Thinking Turbo vs Claude Opus 4.5: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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