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Head-to-Head Model Comparison

DeepSeek V4 vs DeepSeek Reasoner

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
DeepSeek V4 vs DeepSeek Reasoner: Benchmarks, Pricing & Speed Comparison

DeepSeek V4 de DeepSeek y DeepSeek Reasoner de DeepSeek compiten directamente en el ecosistema actual de IA. DeepSeek V4 ofrece una ventana de contexto de 1M tokens a $0.30/$1.20 por millón de tokens (entrada/salida), mientras que DeepSeek Reasoner ofrece 1M tokens de contexto a $0.28/$0.42 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.

Comparación Directa (VS)

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DeepSeek

DeepSeek V4

Modelo Base de Pesos Abiertos

DeepSeek V4 de DeepSeek es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 1M, velocidad de 78 tokens/s, índice de inteligencia de 56/100 y tari

Intelligence Index56 / 100
Input Token:

$0.30 / 1M

Output Token:

$1.20 / 1M

Context Window:

1M tokens

SWE-bench Verified:

62.8%

DeepSeek

DeepSeek Reasoner

Razonamiento de Pesos Abiertos

DeepSeek Reasoner de DeepSeek es un modelo de IA diseñado para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, con ventana de contexto de 1M, velocidad de 52 tokens/s, índice de inteligencia de 54/100

Intelligence Index54 / 100
Input Token:

$0.28 / 1M

Output Token:

$0.42 / 1M

Context Window:

1M tokens

SWE-bench Verified:

56.5%

Diferencias Clave de un Vistazo

  • DeepSeek Reasoner is 1.9x cheaper for API usage (input + output tokens combined).
  • DeepSeek V4 is faster at 78 tok/s vs 52 tok/s.
  • DeepSeek V4 leads on SWE-bench coding (62.8% vs 56.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaDeepSeek V4DeepSeek Reasoner
Intelligence Index
Composite reasoning & knowledge score (0-100)
5654
Provider
DeepSeekDeepSeek
Input Price
Cost per million input tokens
$0.30 / 1M$0.28 / 1M
Output Price
Cost per million output tokens
$1.20 / 1M$0.42 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.20 / 1M$0.12 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K33K
Throughput Speed
Tokens generated per second
78 tok/s52 tok/s
SWE-bench Verified
Real-world software engineering
62.8%56.5%
GPQA Diamond
Graduate-level reasoning
78.4%76.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$0.03 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
DeepSeek V4
+6.3% SWE-bench lead
Costo
DeepSeek Reasoner
1.9x cheaper monthly runtime
Velocidad
DeepSeek V4
+50% faster generation
Contexto
Tied
1M tokens window

Puntuaciones de Benchmarks Verificadas

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

DeepSeek V4DeepSeek Reasoner
SWE-bench Verified (Autonomous Coding)

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

62.8%vs56.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

78.4%vs76.5%
MMLU-Pro (Multi-task Language Understanding)

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

87.5%vs86.2%
LMSYS Chatbot Arena Elo

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

1415ptsvs1368pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

14.5%vs13.5%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42%vs37.5%
SciCode (Scientific Computing)

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

39.5%vs35%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65%vs58.5%
AIME (Advanced Math Competition)

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

89%vs87.5%
Long-Context Reasoning

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

88%vs85%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

78 tok/s vs52 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
DeepSeek V40.60s
DeepSeek Reasoner0.82s
Est. End-to-End Response (500 tokens)TTFT + generation time
DeepSeek V47.01s
DeepSeek Reasoner10.44s

Simulador Interactivo de Costos de Tokens

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)
DeepSeek V4 Monthly API Bill
$1.57 / month
$0.3/1M in · $1.2/1M out
DeepSeek Reasoner Monthly API Bill
$0.84 / month
$0.28/1M in · $0.42/1M out
DeepSeek Reasoner saves approximately $0.73 / month (47%) under this workload.1.9x Savings

DeepSeek V4 · Strengths & Key Advantages

  • Ventana de contexto de 1M con hasta 66K tokens de salida máxima (SWE-bench Verified 62.8% · GPQA Diamond 78.4%)
  • Rendimiento ágil de 78 tokens/segundo con latencia inicial (TTFT) de solo 600 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

DeepSeek Reasoner · Strengths & Key Advantages

  • Ventana de contexto de 1M con hasta 33K tokens de salida máxima (SWE-bench Verified 56.5% · GPQA Diamond 76.5%)
  • Rendimiento ágil de 52 tokens/segundo con latencia inicial (TTFT) de solo 820 ms
  • Pesos abiertos (671B Total (37B )) 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.

MetricDeepSeek V4DeepSeek Reasoner
Cost per Task
Estimated USD to finish one task
$0.38$0.22
Output Tokens / Task
Tokens generated per task
48K45K
Reasoning Tokens / Task
Thinking tokens burned per task
22K26K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaDeepSeek V4DeepSeek Reasoner
Official API Model ID (SDK)deepseek-reasonerdeepseek-reasoner
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-072025-12
Knowledge CutoffApril 2026September 2025
ArchitectureNext-Gen Sparse MoE with MLAReinforcement-Learned Reasoning MoE
ParametersMoE (Colossal)671B Total (37B Active)
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($0.3/1M in) across full 1000K windowFlat rate ($0.28/1M in) across full 1000K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0.03/1M (no extra cache-write fee)Automatic prefix caching at $0.028/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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 & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext
Output Modalitiestexttext

DeepSeek V4 vs DeepSeek Reasoner: Respuestas Rápidas (FAQ)

Which is more intelligent, DeepSeek V4 or DeepSeek Reasoner?

DeepSeek V4 is more intelligent. It scores 56 compared with 54 on the composite Intelligence Index.

Which model is faster?

DeepSeek V4 is faster, generating 78 tokens per second compared with 52 tokens per second.

Which model is cheaper to run?

DeepSeek Reasoner is cheaper at $0.12 per 1M tokens blended, compared with $0.20 (7:2:1 cache:input:output ratio).

Which model has lower latency?

DeepSeek V4 has lower latency, with a time to first token of 0.60s compared with 0.82s.

Veredicto

Tanto DeepSeek V4 (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) como DeepSeek Reasoner (Ideal para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, sistemas RAG empresariales y automatización mediante API.) destacan en producción: DeepSeek V4 lidera en inteligencia general y programación, DeepSeek V4 ofrece mayor velocidad de generación de tokens y DeepSeek Reasoner resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, DeepSeek V4 o DeepSeek Reasoner?+

En las pruebas de inteligencia compuesta y resolución de código, DeepSeek V4 obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de DeepSeek V4 frente a DeepSeek Reasoner?+

DeepSeek V4 cuesta $0.30 / $1.20 por millón de tokens de entrada/salida, mientras que DeepSeek Reasoner cuesta $0.28 / $0.42. En costo combinado, DeepSeek Reasoner es la opción más económica.

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

DeepSeek V4 cuenta con 1M tokens de contexto frente a 1M tokens de DeepSeek Reasoner. En velocidad de inferencia, DeepSeek V4 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 & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.

Fuentes: Documentación oficial de API de DeepSeek y DeepSeek, tarjetas de sistema y benchmarks independientes (2026).