Head-to-Head Model Comparison

Nemotron 3 Nano Omni 30B A3B Reasoning vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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Compare Nemotron 3 Nano Omni 30B A3B Reasoning by NVIDIA against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Comparación Directa (VS)

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NVIDIA

Nemotron 3 Nano Omni 30B A3B Reasoning

MoE omni

Unified omnimodal MoE combining texto, alto-resolución visión, y direct audio ingesta con paso un paso razonamiento.

Intelligence Index48 / 100
Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

256K tokens

SWE-bench Verified:

42%

OpenAI

GPT-6.1 Sol

Valor cercano a Astra

ofrece results close un GPT-6 Astra un roughly one fifth del precio — el latest 2026 lanzamiento.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Diferencias Clave de un Vistazo

  • Nemotron 3 Nano Omni 30B A3B Reasoning is 13.3x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol has a larger context window (1M vs 256K tokens).
  • GPT-6.1 Sol is faster at 120 tok/s vs 105 tok/s.
  • GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 42.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaNemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
4894
Provider
NVIDIAOpenAI
Input Price
Cost per million input tokens
$0.20 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.60 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.14 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
105 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
42%82.3%
GPQA Diamond
Graduate-level reasoning
56.5%80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.10 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
GPT-6.1 Sol
+40.3% SWE-bench lead
Costo
Nemotron 3 Nano Omni 30B A3B Reasoning
13.3x cheaper monthly runtime
Velocidad
GPT-6.1 Sol
+14% faster generation
Contexto
GPT-6.1 Sol
1M tokens window

Puntuaciones de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

Nemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

42%vs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

56.5%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

77.2%vs89.9%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1310ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

36.5%vs63.6%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.7%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

66%vs93.5%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

78%vs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs120 tok/s

Latencia y Tiempo de Respuesta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Nemotron 3 Nano Omni 30B A3B Reasoning0.38s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3 Nano Omni 30B A3B Reasoning5.14s
GPT-6.1 Sol5.29s

Simulador Interactivo de Costos de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Nemotron 3 Nano Omni 30B A3B Reasoning Monthly API Bill
$0.92 / month
$0.2/1M in · $0.6/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Nemotron 3 Nano Omni 30B A3B Reasoning saves approximately $11.23 / month (92%) under this workload.13.3x Savings

Nemotron 3 Nano Omni 30B A3B Reasoning · Strengths & Key Advantages

  • nativo tri-modal comprensión un través de texto, alto-res visión, y audio streams
  • 3B activo parámetro inferencia velocidad con 256K token ventana de contexto
  • de pesos abiertos deployable en perimetral robotics y local workstation rigs
Considerations & Trade-offs
  • voz generación es texto-solo (requiere external TTS para voz responses)
  • Trails especializado 100B+ modelos en competitivo codificación

GPT-6.1 Sol · Strengths & Key Advantages

  • Near-Astra results un roughly un fifth del costo
  • Excellent codificación y de largo alcance agente rendimiento
  • sólido reliability con far menor latencia que Astra
  • Near-insignia results un roughly un fifth del precio
Considerations & Trade-offs
  • Still marginally behind Astra en el muy hardest razonamiento
  • Same precio as GPT-6 Sol, so el upgrade decision es easy

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricNemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.22$2.05
Output Tokens / Task
Tokens generated per task
28K62K
Reasoning Tokens / Task
Thinking tokens burned per task
12K36K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaNemotron 3 Nano Omni 30B A3B ReasoningGPT-6.1 Sol
Official API Model ID (SDK)nemotron-3-nano-omni-30b-a3bgpt-6-1-sol
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2026-042026-09
Knowledge CutoffFebruary 2026April 2026
ArchitectureOmnimodal Sparse MoE (30B Total / 3B Active)Near-Astra unified reasoning model
Parameters30B (3B active MoE)Confidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.2/1M in) across full 256K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.05/1M tokensAutomatic prefix caching at $0.1/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-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 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, audiotext, vision
Output Modalitiestexttext

Nemotron 3 Nano Omni 30B A3B Reasoning vs GPT-6.1 Sol: Respuestas Rápidas (FAQ)

Which is more intelligent, Nemotron 3 Nano Omni 30B A3B Reasoning or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 48 on the composite Intelligence Index.

Which model is faster?

GPT-6.1 Sol is faster, generating 120 tokens per second compared with 105 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 $1.47 (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 1.12s.

Which model has a larger context window?

GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 256K tokens.

Veredicto

Choose Nemotron 3 Nano Omni 30B A3B Reasoning for interactivo robotics, smart camera análisis, y multimodal cliente kiosks, or choose GPT-6.1 Sol for el mejor valor modelo de frontera para profesional y agentic trabajo.

Preguntas frecuentes

Which is cheaper: Nemotron 3 Nano Omni 30B A3B Reasoning or GPT-6.1 Sol?+

Nemotron 3 Nano Omni 30B A3B Reasoning costs $0.2/1M input and $0.6/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Nemotron 3 Nano Omni 30B A3B Reasoning or GPT-6.1 Sol?+

Nemotron 3 Nano Omni 30B A3B Reasoning supports 256K tokens whereas GPT-6.1 Sol supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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: NVIDIA & OpenAI Official Documentation