DeepSeek Reasoner vs Nemotron 3 Nano 30B A3B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
DeepSeek Reasoner de DeepSeek y Nemotron 3 Nano 30B A3B de NVIDIA compiten directamente en el ecosistema actual de IA. DeepSeek Reasoner ofrece una ventana de contexto de 1M tokens a $0.28/$0.42 por millón de tokens (entrada/salida), mientras que Nemotron 3 Nano 30B A3B ofrece 262.1K tokens de contexto a $0.10/$0.25 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.
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DeepSeek Reasoner
Razonamiento de Pesos AbiertosDeepSeek Reasoner de DeepSeek es un modelo de IA diseñado para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, con ventana de contexto de 1M, velocidad de 52 tokens/s, índice de inteligencia de 54/100
$0.28 / 1M
$0.42 / 1M
1M tokens
56.5%
Nemotron 3 Nano 30B A3B
Modelo Base de Pesos AbiertosNemotron 3 Nano 30B A3B de NVIDIA es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 262K, velocidad de 130 tokens/s, índice de inteligencia de
$0.10 / 1M
$0.25 / 1M
262.1K tokens
38%
Diferencias Clave de un Vistazo
- 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%).
| Característica | 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 |
¿Quién gana en cada área?
At-a-glance decision frameworkPuntuaciones 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.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
DeepSeek Reasoner · Strengths & Key Advantages
- Ventana de contexto de 1M con hasta 33K tokens de salida máxima (SWE-bench Verified 56.5% · GPQA Diamond 76.5%)
- Rendimiento ágil de 52 tokens/segundo con latencia inicial (TTFT) de solo 820 ms
- Pesos abiertos (671B Total (37B )) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama
Considerations & Trade-offs
- Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
- En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad
Nemotron 3 Nano 30B A3B · Strengths & Key Advantages
- Ventana de contexto de 262K con hasta 16K tokens de salida máxima (SWE-bench Verified 38% · GPQA Diamond 54%)
- Rendimiento ágil de 130 tokens/segundo con latencia inicial (TTFT) de solo 320 ms
- Pesos abiertos (30B (3B MoE)) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama
Considerations & Trade-offs
- Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
- En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad
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 |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | 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: Respuestas 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.
Veredicto
Tanto DeepSeek Reasoner (Ideal para razonamiento de cadena de pensamiento con pesos abiertos y alta eficiencia algorítmica, sistemas RAG empresariales y automatización mediante API.) como Nemotron 3 Nano 30B A3B (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) destacan en producción: DeepSeek Reasoner lidera en inteligencia general y programación, Nemotron 3 Nano 30B A3B ofrece mayor velocidad de generación de tokens y Nemotron 3 Nano 30B A3B resulta más rentable para cargas de trabajo API de alto volumen.
Preguntas frecuentes
¿Cuál es mejor para programación y razonamiento, DeepSeek Reasoner o Nemotron 3 Nano 30B A3B?+
En las pruebas de inteligencia compuesta y resolución de código, DeepSeek Reasoner obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.
¿Cuánto cuesta la API de DeepSeek Reasoner frente a Nemotron 3 Nano 30B A3B?+
DeepSeek Reasoner cuesta $0.28 / $0.42 por millón de tokens de entrada/salida, mientras que Nemotron 3 Nano 30B A3B cuesta $0.10 / $0.25. En costo combinado, Nemotron 3 Nano 30B A3B es la opción más económica.
¿Qué modelo tiene mayor ventana de contexto y menor latencia?+
DeepSeek Reasoner cuenta con 1M tokens de contexto frente a 262.1K tokens de Nemotron 3 Nano 30B A3B. En velocidad de inferencia, Nemotron 3 Nano 30B A3B ofrece un rendimiento superior.
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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Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: Documentación oficial de API de DeepSeek y NVIDIA, tarjetas de sistema y benchmarks independientes (2026).