o3-pro vs DeepSeek R1
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
o3-pro da OpenAI e DeepSeek R1 da DeepSeek são dois modelos de IA de destaque. O o3-pro oferece uma janela de contexto de 200K tokens a $20.00/$80.00 por milhão de tokens, enquanto o DeepSeek R1 oferece 128K tokens de contexto a $0.55/$2.19 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
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o3-pro
Motor de Raciocínio ProfundoO o3-pro da OpenAI é um modelo de IA projetado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, oferecendo janela de contexto de 200K, velocidade de 30 tokens/s, índice de inteligência de 58/100 e tar
$20.00 / 1M
$80.00 / 1M
200K tokens
71.5%
DeepSeek R1
Raciocínio de Pesos AbertosO DeepSeek R1 da DeepSeek é um modelo de IA projetado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, oferecendo janela de contexto de 128K, velocidade de 45 tokens/s, índice de inteligência de 49/100 e tarifa d
$0.55 / 1M
$2.19 / 1M
128K tokens
49.2%
Principais Diferenças em Resumo
- 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%).
| Feature | o3-pro | DeepSeek R1 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 49 |
Provider | OpenAI | DeepSeek |
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 text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 100K | 8K |
Throughput Speed Tokens generated per second | 30 tok/s | 45 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 |
Quem vence em cada categoria?
At-a-glance decision frameworkPontuações de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
o3-pro · Strengths & Key Advantages
- Janela de contexto de 200K com limite máximo de saída de 100K tokens (SWE-bench Verified 71.5% · GPQA Diamond 79.5%)
- Taxa de transferência rápida de 30 tokens/segundo com latência inicial (TTFT) de 5200 ms
- Economia de API competitiva ($20/$80 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
DeepSeek R1 · Strengths & Key Advantages
- Janela de contexto de 128K com limite máximo de saída de 8K tokens (SWE-bench Verified 49.2% · GPQA Diamond 71.5%)
- Taxa de transferência rápida de 45 tokens/segundo com latência inicial (TTFT) de 950 ms
- Pesos abertos (671B Total (37B )) 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | o3-pro | DeepSeek R1 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $11.68 | $0.65 |
Output Tokens / Task Tokens generated per task | 58K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 38K | 25K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | o3-pro | DeepSeek R1 |
|---|---|---|
| Official API Model ID (SDK) | o3-pro | deepseek-reasoner |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-06 | 2025-01 |
| Knowledge Cutoff | June 2024 | July 2024 |
| Architecture | High-effort reasoning transformer | Open-Weights Reasoning MoE |
| Parameters | Confidential | 671B Total (37B Active) |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($20/1M in) across full 200K window | Flat rate ($0.55/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Automatic 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 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 tool + Hosted Code Interpreter & File Search RAG | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | 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) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16) |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | 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 |
o3-pro vs DeepSeek R1: Respostas 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.
Veredito
Tanto o3-pro (Indicado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, arquiteturas RAG corporativas e integração escalável via API.) quanto DeepSeek R1 (Indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: o3-pro lidera em inteligência geral e programação, DeepSeek R1 oferece geração mais rápida e DeepSeek R1 apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, o3-pro ou DeepSeek R1?+
Nas avaliações de inteligência e código, o3-pro leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, o3-pro ou DeepSeek R1?+
O o3-pro custa $20.00 / $80.00 por 1M de tokens (entrada/saída) e o DeepSeek R1 custa $0.55 / $2.19. No custo combinado, DeepSeek R1 é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O o3-pro suporta 200K tokens de contexto contra 128K tokens do DeepSeek R1, enquanto DeepSeek R1 entrega maior velocidade de geração.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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- DeepSeek R1 vs. o3-mini: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- GPT-5 Chat vs. o3-pro: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Grok 4.20 (Reasoning) vs. DeepSeek R1: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- o3-pro vs. Claude Opus 5.5: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Fontes oficiais: Documentação oficial de API da OpenAI e DeepSeek e benchmarks independentes (2026).