Head-to-Head Model Comparison

DeepSeek V3 vs GPT-4o

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial

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DeepSeek V3Profile

GPT-4oProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:DeepSeek V3 vs GPT-4o

DeepSeek

DeepSeek V3

Modelo Base de Pesos Abertos

O DeepSeek V3 da DeepSeek é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 128K, velocidade de 60 tokens/s, índice de inteligência de 44/100 e tar

Intelligence Index44 / 100

Input Token:

$0.27 / 1M

Output Token:

$1.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

49.2%

OpenAI

GPT-4o

Modelo Nativo de Voz e Áudio

O GPT-4o da OpenAI é um modelo de IA projetado para síntese de voz natural, transcrição de áudio e interação falada em tempo real, oferecendo janela de contexto de 128K, velocidade de 105 tokens/s, índice de inteligência de 41/100 e tarifa

Intelligence Index41 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.8%

Principais Diferenças em Resumo

DeepSeek V3 is 9.8x cheaper for API usage (input + output tokens combined).
GPT-4o is faster at 105 tok/s vs 60 tok/s.
DeepSeek V3 leads on SWE-bench coding (49.2% vs 38.8%).

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

Feature	DeepSeek V3	GPT-4o
Intelligence Index Composite reasoning & knowledge score (0-100)	44	41
Provider	DeepSeek	OpenAI
Input Price Cost per million input tokens	$0.27 / 1M	$2.50 / 1M
Output Price Cost per million output tokens	$1.10 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.21 / 1M	$2.38 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	8K	16K
Throughput Speed Tokens generated per second	60 tok/s	105 tok/s
SWE-bench Verified Real-world software engineering	49.2%	38.8%
GPQA Diamond Graduate-level reasoning	59.1%	53.6%
Cached Input Price Prompt caching discount per 1M tokens	$0.07 / 1M	$1.25 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

DeepSeek V3

+10.4% SWE-bench lead

Cost

DeepSeek V3

9.8x cheaper monthly runtime

Speed

GPT-4o

+75% faster generation

Context

Tied

128K tokens window

Pontuações de Benchmarks Verificadas

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

DeepSeek V3GPT-4o

SWE-bench Verified (Autonomous Coding)

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

49.2%vs38.8%

GPQA Diamond (Doctorate-Level Science & Math)

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

59.1%vs53.6%

MMLU-Pro (Multi-task Language Understanding)

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

75.9%vs72.6%

LMSYS Chatbot Arena Elo

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

1300ptsvs1286pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

9.5%vs4.1%

Terminal-Bench (Agentic Coding & Terminal Use)

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

32.5%vs18.5%

SciCode (Scientific Computing)

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

29.5%vs27.3%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

51.7%vs43.9%

AIME (Advanced Math Competition)

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

68%vs29.7%

Long-Context Reasoning

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

68.3%vs58.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

60 tok/s vs105 tok/s

Latência e Tempo de Resposta

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 V30.68s

GPT-4o0.41s

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

DeepSeek V39.01s

GPT-4o5.17s

Simulador Interativo de Custo 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)

DeepSeek V3 Monthly API Bill

$1.50 / month

$0.27/1M in · $1.1/1M out

GPT-4o Monthly API Bill

$14.63 / month

$2.5/1M in · $10/1M out

DeepSeek V3 saves approximately $13.13 / month (90%) under this workload.9.8x Savings

DeepSeek V3 · Strengths & Key Advantages

Janela de contexto de 128K com limite máximo de saída de 8K tokens (SWE-bench Verified 49.2% · GPQA Diamond 59.1%)
Taxa de transferência rápida de 60 tokens/segundo com latência inicial (TTFT) de 680 ms
Pesos abertos (671B) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama

Considerations & Trade-offs

Requer servidores GPU com memória VRAM adequada para execução local em precisão total
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

GPT-4o · Strengths & Key Advantages

Janela de contexto de 128K com limite máximo de saída de 16K tokens (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
Taxa de transferência rápida de 105 tokens/segundo com latência inicial (TTFT) de 410 ms
Economia de API competitiva ($2.5/$10 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos

Token Use & Task Economics

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

Metric	DeepSeek V3	GPT-4o
Cost per Task Estimated USD to finish one task	$0.14	$0.68
Output Tokens / Task Tokens generated per task	45K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	DeepSeek V3	GPT-4o
Official API Model ID (SDK)	deepseek-chat	gpt-4o
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI Responses API & Chat Completions v1
Release Date	2024-12	2024-05
Knowledge Cutoff	July 2024	October 2023
Architecture	671B Mixture-of-Experts (37B active)	Omni-Multimodal Dense
Parameters	671B	Confidential
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($0.27/1M in) across full 128K window	Flat rate ($2.5/1M in) across full 128K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.07/1M (no extra cache-write fee)	Automatic prefix caching at $1.25/1M (no extra cache-write fee)
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 tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token Billing	Text BPE (~4 chars/token)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	OpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text	text, vision, audio
Output Modalities	text	text, audio

DeepSeek V3 vs GPT-4o: Respostas Rápidas (FAQ)

Which is more intelligent, DeepSeek V3 or GPT-4o?

DeepSeek V3 is more intelligent. It scores 44 compared with 41 on the composite Intelligence Index.

Which model is faster?

GPT-4o is faster, generating 105 tokens per second compared with 60 tokens per second.

Which model is cheaper to run?

DeepSeek V3 is cheaper at $0.21 per 1M tokens blended, compared with $2.38 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4o has lower latency, with a time to first token of 0.41s compared with 0.68s.

Veredito

Tanto DeepSeek V3 (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) quanto GPT-4o (Indicado para síntese de voz natural, transcrição de áudio e interação falada em tempo real, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: DeepSeek V3 lidera em inteligência geral e programação, GPT-4o oferece geração mais rápida e DeepSeek V3 apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, DeepSeek V3 ou GPT-4o?+

Nas avaliações de inteligência e código, DeepSeek V3 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, DeepSeek V3 ou GPT-4o?+

O DeepSeek V3 custa $0.27 / $1.10 por 1M de tokens (entrada/saída) e o GPT-4o custa $2.50 / $10.00. No custo combinado, DeepSeek V3 é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O DeepSeek V3 suporta 128K tokens de contexto contra 128K tokens do GPT-4o, enquanto GPT-4o entrega maior velocidade de geração.

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)

DeepSeek V3 vs GPT-4o

Troque e Compare Qualquer Modelo

DeepSeek V3

GPT-4o

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

DeepSeek V3 · Strengths & Key Advantages

Considerations & Trade-offs

GPT-4o · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

DeepSeek V3 vs GPT-4o: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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