GetInfoUs
Head-to-Head Model Comparison

o3-pro vs DeepSeek R1

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
Compartir
Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
o3-pro vs DeepSeek R1: Benchmarks, Pricing & Speed Comparison

o3-pro de OpenAI y DeepSeek R1 de DeepSeek compiten directamente en el ecosistema actual de IA. o3-pro ofrece una ventana de contexto de 200K tokens a $20.00/$80.00 por millón de tokens (entrada/salida), mientras que DeepSeek R1 ofrece 128K tokens de contexto a $0.55/$2.19 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.

Comparación Directa (VS)

Cambia y Compara Cualquier Modelo

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
OpenAI

o3-pro

Motor de Razonamiento Profundo

o3-pro de OpenAI es un modelo de IA diseñado para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, con ventana de contexto de 200K, velocidad de 30 tokens/s, índice de inteligencia de 58/100 y tarifa

Intelligence Index58 / 100
Input Token:

$20.00 / 1M

Output Token:

$80.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

71.5%

DeepSeek

DeepSeek R1

Razonamiento de Pesos Abiertos

DeepSeek R1 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 128K, velocidad de 45 tokens/s, índice de inteligencia de 49/100 y t

Intelligence Index49 / 100
Input Token:

$0.55 / 1M

Output Token:

$2.19 / 1M

Context Window:

128K tokens

SWE-bench Verified:

49.2%

Diferencias Clave de un Vistazo

  • DeepSeek R1 is 36.4x cheaper for API usage (input + output tokens combined).
  • o3-pro has a larger context window (200K vs 128K tokens).
  • DeepSeek R1 is faster at 45 tok/s vs 30 tok/s.
  • o3-pro leads on SWE-bench coding (71.5% vs 49.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Característicao3-proDeepSeek R1
Intelligence Index
Composite reasoning & knowledge score (0-100)
5849
Provider
OpenAIDeepSeek
Input Price
Cost per million input tokens
$20.00 / 1M$0.55 / 1M
Output Price
Cost per million output tokens
$80.00 / 1M$2.19 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$15.50 / 1M$0.43 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
100K8K
Throughput Speed
Tokens generated per second
30 tok/s45 tok/s
SWE-bench Verified
Real-world software engineering
71.5%49.2%
GPQA Diamond
Graduate-level reasoning
79.5%71.5%
Cached Input Price
Prompt caching discount per 1M tokens
$5.00 / 1M$0.14 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
o3-pro
+22.3% SWE-bench lead
Costo
DeepSeek R1
36.4x cheaper monthly runtime
Velocidad
DeepSeek R1
+50% faster generation
Contexto
o3-pro
200K tokens window

Puntuaciones de Benchmarks Verificadas

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

o3-proDeepSeek R1
SWE-bench Verified (Autonomous Coding)

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

71.5%vs49.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

79.5%vs71.5%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs84%
LMSYS Chatbot Arena Elo

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

1352ptsvs1340pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

13.6%vs11.4%
Terminal-Bench (Agentic Coding & Terminal Use)

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

47.5%vs32.5%
SciCode (Scientific Computing)

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

45.5%vs29.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs51.7%
AIME (Advanced Math Competition)

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

93%vs82.2%
Long-Context Reasoning

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

80.5%vs75.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

30 tok/s vs45 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
o3-pro5.20s
DeepSeek R10.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
o3-pro21.87s
DeepSeek R112.06s

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)
o3-pro Monthly API Bill
$109.50 / month
$20/1M in · $80/1M out
DeepSeek R1 Monthly API Bill
$3.01 / month
$0.55/1M in · $2.19/1M out
DeepSeek R1 saves approximately $106.49 / month (97%) under this workload.36.4x Savings

o3-pro · Strengths & Key Advantages

  • Ventana de contexto de 200K con hasta 100K tokens de salida máxima (SWE-bench Verified 71.5% · GPQA Diamond 79.5%)
  • Rendimiento ágil de 30 tokens/segundo con latencia inicial (TTFT) de solo 5200 ms
  • Economía de API competitiva ($20/$80 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 R1 · Strengths & Key Advantages

  • Ventana de contexto de 128K con hasta 8K tokens de salida máxima (SWE-bench Verified 49.2% · GPQA Diamond 71.5%)
  • Rendimiento ágil de 45 tokens/segundo con latencia inicial (TTFT) de solo 950 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.

Metrico3-proDeepSeek R1
Cost per Task
Estimated USD to finish one task
$11.68$0.65
Output Tokens / Task
Tokens generated per task
58K45K
Reasoning Tokens / Task
Thinking tokens burned per task
38K25K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característicao3-proDeepSeek R1
Official API Model ID (SDK)o3-prodeepseek-reasoner
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-062025-01
Knowledge CutoffJune 2024July 2024
ArchitectureHigh-effort reasoning transformerOpen-Weights Reasoning MoE
ParametersConfidential671B Total (37B Active)
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPMUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($20/1M in) across full 200K windowFlat rate ($0.55/1M in) across full 128K window
Prompt Cache Policy & TTLAutomatic prefix caching at $5/1M (no extra cache-write fee)Automatic prefix caching at $0.14/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)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 & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMCloud-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) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpen-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 Tier100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext
Output Modalitiestexttext

o3-pro vs DeepSeek R1: Respuestas Rápidas (FAQ)

Which is more intelligent, o3-pro or DeepSeek R1?

o3-pro is more intelligent. It scores 58 compared with 49 on the composite Intelligence Index.

Which model is faster?

DeepSeek R1 is faster, generating 45 tokens per second compared with 30 tokens per second.

Which model is cheaper to run?

DeepSeek R1 is cheaper at $0.43 per 1M tokens blended, compared with $15.50 (7:2:1 cache:input:output ratio).

Which model has lower latency?

DeepSeek R1 has lower latency, with a time to first token of 0.95s compared with 5.20s.

Which model has a larger context window?

o3-pro has a larger context window, supporting 200K tokens compared with 128K tokens.

Veredicto

Tanto o3-pro (Ideal para razonamiento lógico profundo, matemáticas avanzadas y resolución científica paso a paso, sistemas RAG empresariales y automatización mediante API.) como DeepSeek R1 (Ideal para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, sistemas RAG empresariales y automatización mediante API.) destacan en producción: o3-pro lidera en inteligencia general y programación, DeepSeek R1 ofrece mayor velocidad de generación de tokens y DeepSeek R1 resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, o3-pro o DeepSeek R1?+

En las pruebas de inteligencia compuesta y resolución de código, o3-pro obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de o3-pro frente a DeepSeek R1?+

o3-pro cuesta $20.00 / $80.00 por millón de tokens de entrada/salida, mientras que DeepSeek R1 cuesta $0.55 / $2.19. En costo combinado, DeepSeek R1 es la opción más económica.

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

o3-pro cuenta con 200K tokens de contexto frente a 128K tokens de DeepSeek R1. En velocidad de inferencia, DeepSeek R1 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 OpenAI y DeepSeek, tarjetas de sistema y benchmarks independientes (2026).