DeepSeek R1 vs o3-mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
DeepSeek R1 da DeepSeek e o3-mini da OpenAI são dois modelos de IA de destaque. O DeepSeek R1 oferece uma janela de contexto de 128K tokens a $0.55/$2.19 por milhão de tokens, enquanto o o3-mini oferece 200K tokens de contexto a $1.10/$4.40 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
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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%
o3-mini
Motor de Raciocínio ProfundoO o3-mini 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 85 tokens/s, índice de inteligência de 51/100 e ta
$1.10 / 1M
$4.40 / 1M
200K tokens
49%
Principais Diferenças em Resumo
- DeepSeek R1 is 2.1x cheaper for API usage (input + output tokens combined).
- o3-mini has a larger context window (200K vs 128K tokens).
- o3-mini is faster at 85 tok/s vs 45 tok/s.
- DeepSeek R1 leads on SWE-bench coding (49.2% vs 49.0%).
| Feature | DeepSeek R1 | o3-mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 49 | 51 |
Provider | DeepSeek | OpenAI |
Input Price Cost per million input tokens | $0.55 / 1M | $1.10 / 1M |
Output Price Cost per million output tokens | $2.19 / 1M | $4.40 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.43 / 1M | $1.05 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 8K | 100K |
Throughput Speed Tokens generated per second | 45 tok/s | 85 tok/s |
SWE-bench Verified Real-world software engineering | 49.2% | 49% |
GPQA Diamond Graduate-level reasoning | 71.5% | 79.7% |
Cached Input Price Prompt caching discount per 1M tokens | $0.14 / 1M | $0.55 / 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.
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
o3-mini · Strengths & Key Advantages
- Janela de contexto de 200K com limite máximo de saída de 100K tokens (SWE-bench Verified 49% · GPQA Diamond 79.7%)
- Taxa de transferência rápida de 85 tokens/segundo com latência inicial (TTFT) de 1400 ms
- Economia de API competitiva ($1.1/$4.4 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
- 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 | DeepSeek R1 | o3-mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.65 | $1.30 |
Output Tokens / Task Tokens generated per task | 45K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 25K | 25K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | DeepSeek R1 | o3-mini |
|---|---|---|
| Official API Model ID (SDK) | deepseek-reasoner | o3-mini |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-01 | 2025-01 |
| Knowledge Cutoff | July 2024 | October 2023 |
| Architecture | Open-Weights Reasoning MoE | Chain-of-Thought Reasoning Dense |
| Parameters | 671B Total (37B Active) | 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 ($0.55/1M in) across full 128K window | Flat rate ($1.1/1M in) across full 200K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.14/1M (no extra cache-write fee) | Automatic prefix caching at $0.55/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / 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 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) |
| 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 |
| Output Modalities | text | text |
DeepSeek R1 vs o3-mini: Respostas Rápidas (FAQ)
Which is more intelligent, DeepSeek R1 or o3-mini?
o3-mini is more intelligent. It scores 51 compared with 49 on the composite Intelligence Index.
Which model is faster?
o3-mini is faster, generating 85 tokens per second compared with 45 tokens per second.
Which model is cheaper to run?
DeepSeek R1 is cheaper at $0.43 per 1M tokens blended, compared with $1.05 (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 1.40s.
Which model has a larger context window?
o3-mini has a larger context window, supporting 200K tokens compared with 128K tokens.
Veredito
Tanto DeepSeek R1 (Indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas RAG corporativas e integração escalável via API.) quanto o3-mini (Indicado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: o3-mini lidera em inteligência geral e programação, o3-mini oferece geração mais rápida e DeepSeek R1 apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, DeepSeek R1 ou o3-mini?+
Nas avaliações de inteligência e código, o3-mini leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, DeepSeek R1 ou o3-mini?+
O DeepSeek R1 custa $0.55 / $2.19 por 1M de tokens (entrada/saída) e o o3-mini custa $1.10 / $4.40. No custo combinado, DeepSeek R1 é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O DeepSeek R1 suporta 128K tokens de contexto contra 200K tokens do o3-mini, enquanto o3-mini 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
- Claude 3.7 Sonnet vs. DeepSeek R1: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Claude 3.7 Sonnet vs. o3-mini: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- DeepSeek R1 vs. OpenAI o1: 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
- o1-pro vs. o3-mini: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- o3-pro vs. DeepSeek R1: 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 DeepSeek e OpenAI e benchmarks independentes (2026).