Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Nemotron 3 Nano Omni 30B A3B Reasoning de NVIDIA y Nemotron 3 Super 120B A12B de NVIDIA compiten directamente en el ecosistema actual de IA. Nemotron 3 Nano Omni 30B A3B Reasoning ofrece una ventana de contexto de 256K tokens a $0.20/$0.60 por millón de tokens (entrada/salida), mientras que Nemotron 3 Super 120B A12B ofrece 262.1K tokens de contexto a $0.30/$0.80 por millón de tokens. Analizamos sus benchmarks, latencia y costos reales.
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Nemotron 3 Nano Omni 30B A3B Reasoning
IA Multimodal NativaNemotron 3 Nano Omni 30B A3B Reasoning de NVIDIA es un modelo de IA diseñado para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, con ventana de contexto de 256K, velocidad de 105 tokens/s, índice de intelig
$0.20 / 1M
$0.60 / 1M
256K tokens
42%
Nemotron 3 Super 120B A12B
IA Agéntica y Uso de HerramientasNemotron 3 Super 120B A12B de NVIDIA es un modelo de IA diseñado para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, con ventana de contexto de 262K, velocidad de 85 tokens/s, índice de inteligencia
$0.30 / 1M
$0.80 / 1M
262.1K tokens
51%
Diferencias Clave de un Vistazo
- Nemotron 3 Nano Omni 30B A3B Reasoning is 1.4x cheaper for API usage (input + output tokens combined).
- Nemotron 3 Super 120B A12B has a larger context window (262K vs 256K tokens).
- Nemotron 3 Nano Omni 30B A3B Reasoning is faster at 105 tok/s vs 85 tok/s.
- Nemotron 3 Super 120B A12B leads on SWE-bench coding (51.0% vs 42.0%).
| Característica | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 48 | 53 |
Provider | NVIDIA | NVIDIA |
Input Price Cost per million input tokens | $0.20 / 1M | $0.30 / 1M |
Output Price Cost per million output tokens | $0.60 / 1M | $0.80 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.14 / 1M | $0.18 / 1M |
Context Window Maximum input + output tokens | 256K tokens~384 A4 pages of text | 262.1K tokens~393 A4 pages of text |
Max Output Tokens Per single request | 16K | 33K |
Throughput Speed Tokens generated per second | 105 tok/s | 85 tok/s |
SWE-bench Verified Real-world software engineering | 42% | 51% |
GPQA Diamond Graduate-level reasoning | 56.5% | 64.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.05 / 1M | $0.06 / 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.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
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.
Nemotron 3 Nano Omni 30B A3B Reasoning · Strengths & Key Advantages
- Ventana de contexto de 256K con hasta 16K tokens de salida máxima (SWE-bench Verified 42% · GPQA Diamond 56.5%)
- Rendimiento ágil de 105 tokens/segundo con latencia inicial (TTFT) de solo 380 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
Nemotron 3 Super 120B A12B · Strengths & Key Advantages
- Ventana de contexto de 262K con hasta 33K tokens de salida máxima (SWE-bench Verified 51% · GPQA Diamond 64.5%)
- Rendimiento ágil de 85 tokens/segundo con latencia inicial (TTFT) de solo 460 ms
- Pesos abiertos (120B (12B 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 | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $0.38 |
Output Tokens / Task Tokens generated per task | 28K | 38K |
Reasoning Tokens / Task Thinking tokens burned per task | 12K | 18K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B |
|---|---|---|
| Official API Model ID (SDK) | nemotron-3-nano-omni-30b-a3b | nemotron-3-super-120b-a12b |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-04 | 2026-03 |
| Knowledge Cutoff | February 2026 | January 2026 |
| Architecture | Omnimodal Sparse MoE (30B Total / 3B Active) | High-Throughput Sparse MoE (120B Total / 12B Active) |
| Parameters | 30B (3B active MoE) | 120B (12B 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 ($0.2/1M in) across full 256K window | Flat rate ($0.3/1M in) across full 262K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Cached input at $0.06/1M 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) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 74 GB VRAM (4-bit Quantized) · 258 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, vision, audio | text |
| Output Modalities | text | text |
Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B: Respuestas Rápidas (FAQ)
Which is more intelligent, Nemotron 3 Nano Omni 30B A3B Reasoning or Nemotron 3 Super 120B A12B?
Nemotron 3 Super 120B A12B is more intelligent. It scores 53 compared with 48 on the composite Intelligence Index.
Which model is faster?
Nemotron 3 Nano Omni 30B A3B Reasoning is faster, generating 105 tokens per second compared with 85 tokens per second.
Which model is cheaper to run?
Nemotron 3 Nano Omni 30B A3B Reasoning is cheaper at $0.14 per 1M tokens blended, compared with $0.18 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nemotron 3 Nano Omni 30B A3B Reasoning has lower latency, with a time to first token of 0.38s compared with 0.46s.
Which model has a larger context window?
Nemotron 3 Super 120B A12B has a larger context window, supporting 262.1K tokens compared with 256K tokens.
Veredicto
Tanto Nemotron 3 Nano Omni 30B A3B Reasoning (Ideal para comprensión multimodal nativa de texto e imagen y análisis visual de documentos, sistemas RAG empresariales y automatización mediante API.) como Nemotron 3 Super 120B A12B (Ideal para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Nemotron 3 Super 120B A12B lidera en inteligencia general y programación, Nemotron 3 Nano Omni 30B A3B Reasoning ofrece mayor velocidad de generación de tokens y Nemotron 3 Nano Omni 30B A3B Reasoning resulta más rentable para cargas de trabajo API de alto volumen.
Preguntas frecuentes
¿Cuál es mejor para programación y razonamiento, Nemotron 3 Nano Omni 30B A3B Reasoning o Nemotron 3 Super 120B A12B?+
En las pruebas de inteligencia compuesta y resolución de código, Nemotron 3 Super 120B A12B obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.
¿Cuánto cuesta la API de Nemotron 3 Nano Omni 30B A3B Reasoning frente a Nemotron 3 Super 120B A12B?+
Nemotron 3 Nano Omni 30B A3B Reasoning cuesta $0.20 / $0.60 por millón de tokens de entrada/salida, mientras que Nemotron 3 Super 120B A12B cuesta $0.30 / $0.80. En costo combinado, Nemotron 3 Nano Omni 30B A3B Reasoning es la opción más económica.
¿Qué modelo tiene mayor ventana de contexto y menor latencia?+
Nemotron 3 Nano Omni 30B A3B Reasoning cuenta con 256K tokens de contexto frente a 262.1K tokens de Nemotron 3 Super 120B A12B. En velocidad de inferencia, Nemotron 3 Nano Omni 30B A3B Reasoning 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 NVIDIA y NVIDIA, tarjetas de sistema y benchmarks independientes (2026).