Head-to-Head Model Comparison

Claude Sonnet 5.5 vs DeepSeek V4 Pro

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 5.5Profile

DeepSeek V4 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Anthropic

Claude Sonnet 5.5

Modelo Insignia de Frontera

Claude Sonnet 5.5 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 105 tokens/s, índice de inteligencia de 78/100 y

Intelligence Index78 / 100

Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.9%

DeepSeek

DeepSeek V4 Pro

IA Agéntica y Uso de Herramientas

DeepSeek V4 Pro de DeepSeek es un modelo de IA diseñado para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, con ventana de contexto de 1M, velocidad de 80 tokens/s, índice de inteligencia de 53/100

Intelligence Index53 / 100

Input Token:

$1.32 / 1M

Output Token:

$3.96 / 1M

Context Window:

1M tokens

SWE-bench Verified:

68.5%

Diferencias Clave de un Vistazo

DeepSeek V4 Pro is 2.1x cheaper for API usage (input + output tokens combined).
Claude Sonnet 5.5 is faster at 105 tok/s vs 80 tok/s.
Claude Sonnet 5.5 leads on SWE-bench coding (82.9% vs 68.5%).

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

Característica	Claude Sonnet 5.5	DeepSeek V4 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	78	53
Provider	Anthropic	DeepSeek
Input Price Cost per million input tokens	$2.00 / 1M	$1.32 / 1M
Output Price Cost per million output tokens	$10.00 / 1M	$3.96 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.54 / 1M	$0.76 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 A4 pages of text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	128K	128K
Throughput Speed Tokens generated per second	105 tok/s	80 tok/s
SWE-bench Verified Real-world software engineering	82.9%	68.5%
GPQA Diamond Graduate-level reasoning	79.4%	81.2%
Cached Input Price Prompt caching discount per 1M tokens	$0.20 / 1M	$0.14 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Claude Sonnet 5.5

+14.4% SWE-bench lead

Costo

DeepSeek V4 Pro

2.1x cheaper monthly runtime

Velocidad

Claude Sonnet 5.5

+31% faster generation

Contexto

Tied

1M tokens window

Puntuaciones de Benchmarks Verificadas

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

Claude Sonnet 5.5DeepSeek V4 Pro

SWE-bench Verified (Autonomous Coding)

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

82.9%vs68.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

79.4%vs81.2%

MMLU-Pro (Multi-task Language Understanding)

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

90.1%vs88.9%

LMSYS Chatbot Arena Elo

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

1490ptsvs1438pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs15.6%

Terminal-Bench (Agentic Coding & Terminal Use)

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

58.9%vs46.5%

SciCode (Scientific Computing)

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

N/Avs43%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs70.2%

AIME (Advanced Math Competition)

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

N/Avs91%

Long-Context Reasoning

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

N/Avs90%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs80 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 5.50.55s

DeepSeek V4 Pro0.58s

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

Claude Sonnet 5.55.31s

DeepSeek V4 Pro6.83s

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 5.5 Monthly API Bill

$12.30 / month

$2/1M in · $10/1M out

DeepSeek V4 Pro Monthly API Bill

$5.75 / month

$1.32/1M in · $3.96/1M out

DeepSeek V4 Pro saves approximately $6.55 / month (53%) under this workload.2.1x Savings

Claude Sonnet 5.5 · Strengths & Key Advantages

Ventana de contexto de 1M con hasta 128K tokens de salida máxima (SWE-bench Verified 82.9% · GPQA Diamond 79.4%)
Rendimiento ágil de 105 tokens/segundo con latencia inicial (TTFT) de solo 550 ms
Economía de API competitiva ($2/$10 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

DeepSeek V4 Pro · Strengths & Key Advantages

Ventana de contexto de 1M con hasta 128K tokens de salida máxima (SWE-bench Verified 68.5% · GPQA Diamond 81.2%)
Rendimiento ágil de 80 tokens/segundo con latencia inicial (TTFT) de solo 580 ms
Pesos abiertos (MoE (Colossal)) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama

Considerations & Trade-offs

Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
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 5.5	DeepSeek V4 Pro
Cost per Task Estimated USD to finish one task	$3.29	$0.67
Output Tokens / Task Tokens generated per task	72K	52K
Reasoning Tokens / Task Thinking tokens burned per task	37K	25K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	Claude Sonnet 5.5	DeepSeek V4 Pro
Official API Model ID (SDK)	claude-sonnet-5-5-20260901	deepseek-reasoner
API Protocol	Anthropic Messages API + AWS Bedrock + Vertex AI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-09	2026-08
Knowledge Cutoff	June 2026	May 2026
Architecture	Adaptive Frontier Multimodal Transformer	Next-Gen Sparse MoE with Agent RL Tuning
Parameters	Confidential	MoE (Colossal)
Enterprise Rate Limits (RPM / TPM)	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens	Flat rate ($1.32/1M in) across full 1000K window
Prompt Cache Policy & TTL	$0.2/1M cached read (90% off); 5-min default & 1-hour extended TTL	Automatic prefix caching at $0.14/1M (no extra cache-write fee)
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Custom Model Tuning via Amazon Bedrock & Prompt Distillation	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)
Safety & Frontier Classification	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text, vision	text
Output Modalities	text	text

Claude Sonnet 5.5 vs DeepSeek V4 Pro: Respuestas Rápidas (FAQ)

Which is more intelligent, Claude Sonnet 5.5 or DeepSeek V4 Pro?

Claude Sonnet 5.5 is more intelligent. It scores 78 compared with 53 on the composite Intelligence Index.

Which model is faster?

Claude Sonnet 5.5 is faster, generating 105 tokens per second compared with 80 tokens per second.

Which model is cheaper to run?

DeepSeek V4 Pro is cheaper at $0.76 per 1M tokens blended, compared with $1.54 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Sonnet 5.5 has lower latency, with a time to first token of 0.55s compared with 0.58s.

Veredicto

Tanto Claude Sonnet 5.5 (Ideal para razonamiento empresarial de frontera, programación avanzada y flujos de producción, sistemas RAG empresariales y automatización mediante API.) como DeepSeek V4 Pro (Ideal para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Claude Sonnet 5.5 lidera en inteligencia general y programación, Claude Sonnet 5.5 ofrece mayor velocidad de generación de tokens y DeepSeek V4 Pro resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Claude Sonnet 5.5 o DeepSeek V4 Pro?+

En las pruebas de inteligencia compuesta y resolución de código, Claude Sonnet 5.5 obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Claude Sonnet 5.5 frente a DeepSeek V4 Pro?+

Claude Sonnet 5.5 cuesta $2.00 / $10.00 por millón de tokens de entrada/salida, mientras que DeepSeek V4 Pro cuesta $1.32 / $3.96. En costo combinado, DeepSeek V4 Pro es la opción más económica.

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

Claude Sonnet 5.5 cuenta con 1M tokens de contexto frente a 1M tokens de DeepSeek V4 Pro. En velocidad de inferencia, Claude Sonnet 5.5 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)

Claude Sonnet 5.5 vs DeepSeek V4 Pro

Cambia y Compara Cualquier Modelo

Claude Sonnet 5.5

DeepSeek V4 Pro

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Claude Sonnet 5.5 · Strengths & Key Advantages

Considerations & Trade-offs

DeepSeek V4 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Claude Sonnet 5.5 vs DeepSeek V4 Pro: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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