DeepSeek V4 vs DeepSeek Reasoner
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
DeepSeek V4 da DeepSeek e DeepSeek Reasoner da DeepSeek são dois modelos de IA de destaque. O DeepSeek V4 oferece uma janela de contexto de 1M tokens a $0.30/$1.20 por milhão de tokens, enquanto o DeepSeek Reasoner oferece 1M tokens de contexto a $0.28/$0.42 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
DeepSeek V4
Modelo Base de Pesos AbertosO DeepSeek V4 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 1M, velocidade de 78 tokens/s, índice de inteligência de 56/100 e tarif
$0.30 / 1M
$1.20 / 1M
1M tokens
62.8%
DeepSeek Reasoner
Raciocínio de Pesos AbertosO DeepSeek Reasoner 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 1M, velocidade de 52 tokens/s, índice de inteligência de 54/100 e tari
$0.28 / 1M
$0.42 / 1M
1M tokens
56.5%
Principais Diferenças em Resumo
- 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%).
| Feature | DeepSeek V4 | DeepSeek Reasoner |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 56 | 54 |
Provider | DeepSeek | DeepSeek |
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 text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 66K | 33K |
Throughput Speed Tokens generated per second | 78 tok/s | 52 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 |
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 V4 · Strengths & Key Advantages
- Janela de contexto de 1M com limite máximo de saída de 66K tokens (SWE-bench Verified 62.8% · GPQA Diamond 78.4%)
- Taxa de transferência rápida de 78 tokens/segundo com latência inicial (TTFT) de 600 ms
- Pesos abertos (MoE (Colossal)) 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
DeepSeek Reasoner · Strengths & Key Advantages
- Janela de contexto de 1M com limite máximo de saída de 33K tokens (SWE-bench Verified 56.5% · GPQA Diamond 76.5%)
- Taxa de transferência rápida de 52 tokens/segundo com latência inicial (TTFT) de 820 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 | DeepSeek V4 | DeepSeek Reasoner |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.38 | $0.22 |
Output Tokens / Task Tokens generated per task | 48K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 26K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | DeepSeek V4 | DeepSeek Reasoner |
|---|---|---|
| Official API Model ID (SDK) | deepseek-reasoner | deepseek-reasoner |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-07 | 2025-12 |
| Knowledge Cutoff | April 2026 | September 2025 |
| Architecture | Next-Gen Sparse MoE with MLA | Reinforcement-Learned Reasoning MoE |
| Parameters | MoE (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 Cloud | 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 ($0.3/1M in) across full 1000K window | Flat rate ($0.28/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Automatic 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 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full 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 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) · 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 Classification | Open-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 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text | text |
| Output Modalities | text | text |
DeepSeek V4 vs DeepSeek Reasoner: Respostas 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.
Veredito
Tanto DeepSeek V4 (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) quanto DeepSeek Reasoner (Indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: DeepSeek V4 lidera em inteligência geral e programação, DeepSeek V4 oferece geração mais rápida e DeepSeek Reasoner apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, DeepSeek V4 ou DeepSeek Reasoner?+
Nas avaliações de inteligência e código, DeepSeek V4 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, DeepSeek V4 ou DeepSeek Reasoner?+
O DeepSeek V4 custa $0.30 / $1.20 por 1M de tokens (entrada/saída) e o DeepSeek Reasoner custa $0.28 / $0.42. No custo combinado, DeepSeek Reasoner é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O DeepSeek V4 suporta 1M tokens de contexto contra 1M tokens do DeepSeek Reasoner, enquanto DeepSeek V4 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
- DeepSeek Reasoner vs. DeepSeek-R1-0528: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- DeepSeek Reasoner vs. Nemotron 3 Nano 30B A3B: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- DeepSeek V4 vs. Gemma 4 E2B: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Aion-3.0 vs. Aion-Mini: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Aion-3.0 vs. Gemini 3.6 Flash: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Aion-Mini vs. Laguna XS 2.1: 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 DeepSeek e benchmarks independentes (2026).