DeepSeek Reasoner vs Nemotron 3 Nano 30B A3B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
DeepSeek Reasoner da DeepSeek e Nemotron 3 Nano 30B A3B da NVIDIA são dois modelos de IA de destaque. O DeepSeek Reasoner oferece uma janela de contexto de 1M tokens a $0.28/$0.42 por milhão de tokens, enquanto o Nemotron 3 Nano 30B A3B oferece 262.1K tokens de contexto a $0.10/$0.25 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
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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%
Nemotron 3 Nano 30B A3B
Modelo Base de Pesos AbertosO Nemotron 3 Nano 30B A3B da NVIDIA é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 262K, velocidade de 130 tokens/s, índice de inteligência de 4
$0.10 / 1M
$0.25 / 1M
262.1K tokens
38%
Principais Diferenças em Resumo
- Nemotron 3 Nano 30B A3B is 2.1x cheaper for API usage (input + output tokens combined).
- DeepSeek Reasoner has a larger context window (1M vs 262K tokens).
- Nemotron 3 Nano 30B A3B is faster at 130 tok/s vs 52 tok/s.
- DeepSeek Reasoner leads on SWE-bench coding (56.5% vs 38.0%).
| Feature | DeepSeek Reasoner | Nemotron 3 Nano 30B A3B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 54 | 45 |
Provider | DeepSeek | NVIDIA |
Input Price Cost per million input tokens | $0.28 / 1M | $0.10 / 1M |
Output Price Cost per million output tokens | $0.42 / 1M | $0.25 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.12 / 1M | $0.06 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 262.1K tokens~393 A4 pages of text |
Max Output Tokens Per single request | 33K | 16K |
Throughput Speed Tokens generated per second | 52 tok/s | 130 tok/s |
SWE-bench Verified Real-world software engineering | 56.5% | 38% |
GPQA Diamond Graduate-level reasoning | 76.5% | 54% |
Cached Input Price Prompt caching discount per 1M tokens | $0.03 / 1M | $0.02 / 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 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
Nemotron 3 Nano 30B A3B · Strengths & Key Advantages
- Janela de contexto de 262K com limite máximo de saída de 16K tokens (SWE-bench Verified 38% · GPQA Diamond 54%)
- Taxa de transferência rápida de 130 tokens/segundo com latência inicial (TTFT) de 320 ms
- Pesos abertos (30B (3B MoE)) 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 Reasoner | Nemotron 3 Nano 30B A3B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $0.12 |
Output Tokens / Task Tokens generated per task | 45K | 28K |
Reasoning Tokens / Task Thinking tokens burned per task | 26K | 10K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | DeepSeek Reasoner | Nemotron 3 Nano 30B A3B |
|---|---|---|
| Official API Model ID (SDK) | deepseek-reasoner | nemotron-3-nano-30b-a3b |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-12 | 2025-12 |
| Knowledge Cutoff | September 2025 | October 2025 |
| Architecture | Reinforcement-Learned Reasoning MoE | Sparse Mixture-of-Experts (30B Total / 3B Active) |
| Parameters | 671B Total (37B Active) | 30B (3B active MoE) |
| 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 ($0.28/1M in) across full 1000K window | Flat rate ($0.1/1M in) across full 262K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.028/1M (no extra cache-write fee) | Cached input at $0.02/1M tokens |
| 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) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 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 Reasoner vs Nemotron 3 Nano 30B A3B: Respostas Rápidas (FAQ)
Which is more intelligent, DeepSeek Reasoner or Nemotron 3 Nano 30B A3B?
DeepSeek Reasoner is more intelligent. It scores 54 compared with 45 on the composite Intelligence Index.
Which model is faster?
Nemotron 3 Nano 30B A3B is faster, generating 130 tokens per second compared with 52 tokens per second.
Which model is cheaper to run?
Nemotron 3 Nano 30B A3B is cheaper at $0.06 per 1M tokens blended, compared with $0.12 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nemotron 3 Nano 30B A3B has lower latency, with a time to first token of 0.32s compared with 0.82s.
Which model has a larger context window?
DeepSeek Reasoner has a larger context window, supporting 1M tokens compared with 262.1K tokens.
Veredito
Tanto DeepSeek Reasoner (Indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas RAG corporativas e integração escalável via API.) quanto Nemotron 3 Nano 30B A3B (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: DeepSeek Reasoner lidera em inteligência geral e programação, Nemotron 3 Nano 30B A3B oferece geração mais rápida e Nemotron 3 Nano 30B A3B apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, DeepSeek Reasoner ou Nemotron 3 Nano 30B A3B?+
Nas avaliações de inteligência e código, DeepSeek Reasoner leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, DeepSeek Reasoner ou Nemotron 3 Nano 30B A3B?+
O DeepSeek Reasoner custa $0.28 / $0.42 por 1M de tokens (entrada/saída) e o Nemotron 3 Nano 30B A3B custa $0.10 / $0.25. No custo combinado, Nemotron 3 Nano 30B A3B é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O DeepSeek Reasoner suporta 1M tokens de contexto contra 262.1K tokens do Nemotron 3 Nano 30B A3B, enquanto Nemotron 3 Nano 30B A3B 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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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 NVIDIA e benchmarks independentes (2026).