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Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B: Benchmarks, Pricing & Speed Comparison

Nemotron 3 Nano Omni 30B A3B Reasoning von NVIDIA und Nemotron 3 Super 120B A12B von NVIDIA gehören zu den führenden KI-Modellen. Nemotron 3 Nano Omni 30B A3B Reasoning bietet ein Kontextfenster von 256K Tokens bei API-Preisen von $0.20/$0.60 pro 1M Tokens, während Nemotron 3 Super 120B A12B 262.1K Tokens Kontext zu $0.30/$0.80 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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NVIDIA

Nemotron 3 Nano Omni 30B A3B Reasoning

Nativ Multimodale KI

Nemotron 3 Nano Omni 30B A3B Reasoning von NVIDIA ist ein KI-Modell für nativ multimodale Verarbeitung von Text und Bild sowie visuelle Dokumentenanalyse mit 256K Kontextfenster, 105 Token/s Durchsatz, einem Intelligenz-Index von 48/100 und

Intelligence Index48 / 100
Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

256K tokens

SWE-bench Verified:

42%

NVIDIA

Nemotron 3 Super 120B A12B

Autonomes Agenten-Modell

Nemotron 3 Super 120B A12B von NVIDIA ist ein KI-Modell für autonome Agenten-Workflows, zuverlässiges Tool-Calling und mehrstufige Automatisierung mit 262K Kontextfenster, 85 Token/s Durchsatz, einem Intelligenz-Index von 53/100 und $0.3/$0

Intelligence Index53 / 100
Input Token:

$0.30 / 1M

Output Token:

$0.80 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

51%

Wichtigste Unterschiede auf einen Blick

  • 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%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3 Nano Omni 30B A3B ReasoningNemotron 3 Super 120B A12B
Intelligence Index
Composite reasoning & knowledge score (0-100)
4853
Provider
NVIDIANVIDIA
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 text262.1K tokens~393 A4 pages of text
Max Output Tokens
Per single request
16K33K
Throughput Speed
Tokens generated per second
105 tok/s85 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

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding
Nemotron 3 Super 120B A12B
+9.0% SWE-bench lead
Cost
Nemotron 3 Nano Omni 30B A3B Reasoning
1.4x cheaper monthly runtime
Speed
Nemotron 3 Nano Omni 30B A3B Reasoning
+24% faster generation
Context
Nemotron 3 Super 120B A12B
262.1K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Nemotron 3 Nano Omni 30B A3B ReasoningNemotron 3 Super 120B A12B
SWE-bench Verified (Autonomous Coding)

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

42%vs51%
GPQA Diamond (Doctorate-Level Science & Math)

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

56.5%vs64.5%
MMLU-Pro (Multi-task Language Understanding)

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

77.2%vs82.8%
LMSYS Chatbot Arena Elo

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

1310ptsvs1350pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

36.5%vs45%
AIME (Advanced Math Competition)

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

66%vs74%
Long-Context Reasoning

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

78%vs82%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs85 tok/s

Latenz & Antwortzeit

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
Nemotron 3 Super 120B A12B0.46s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3 Nano Omni 30B A3B Reasoning5.14s
Nemotron 3 Super 120B A12B6.34s

Interaktiver Token-Kosten-Simulator

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
Nemotron 3 Super 120B A12B Monthly API Bill
$1.26 / month
$0.3/1M in · $0.8/1M out
Nemotron 3 Nano Omni 30B A3B Reasoning saves approximately $0.34 / month (27%) under this workload.1.4x Savings

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

  • 256K Kontextfenster und bis zu 16K maximale Output-Token (SWE-bench Verified 42% · GPQA Diamond 56.5%)
  • Hohe Generierungsgeschwindigkeit von 105 Token/Sekunde bei nur 380 ms Erstlatenz (TTFT)
  • Offene Modellgewichte (30B (3B MoE)) für lokales Self-Hosting und Fine-Tuning über vLLM, SGLang oder Ollama
Considerations & Trade-offs
  • Erfordert dedizierte GPU-Hardware mit ausreichend VRAM für den lokalen Betrieb in voller Präzision
  • Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Nemotron 3 Super 120B A12B · Strengths & Key Advantages

  • 262K Kontextfenster und bis zu 33K maximale Output-Token (SWE-bench Verified 51% · GPQA Diamond 64.5%)
  • Hohe Generierungsgeschwindigkeit von 85 Token/Sekunde bei nur 460 ms Erstlatenz (TTFT)
  • Offene Modellgewichte (120B (12B MoE)) für lokales Self-Hosting und Fine-Tuning über vLLM, SGLang oder Ollama
Considerations & Trade-offs
  • Erfordert dedizierte GPU-Hardware mit ausreichend VRAM für den lokalen Betrieb in voller Präzision
  • Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Token Use & Task Economics

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

MetricNemotron 3 Nano Omni 30B A3B ReasoningNemotron 3 Super 120B A12B
Cost per Task
Estimated USD to finish one task
$0.22$0.38
Output Tokens / Task
Tokens generated per task
28K38K
Reasoning Tokens / Task
Thinking tokens burned per task
12K18K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3 Nano Omni 30B A3B ReasoningNemotron 3 Super 120B A12B
Official API Model ID (SDK)nemotron-3-nano-omni-30b-a3bnemotron-3-super-120b-a12b
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-042026-03
Knowledge CutoffFebruary 2026January 2026
ArchitectureOmnimodal Sparse MoE (30B Total / 3B Active)High-Throughput Sparse MoE (120B Total / 12B Active)
Parameters30B (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 CloudUnlimited (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 windowFlat rate ($0.3/1M in) across full 262K window
Prompt Cache Policy & TTLCached input at $0.05/1M tokensCached input at $0.06/1M tokens
Computer Use / GUI AgentAPI / 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 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 toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull 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 BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)Text BPE (~4 chars/token)
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)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 ClassificationOpen-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 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, vision, audiotext
Output Modalitiestexttext

Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B: Schnelle Antworten (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.

Fazit

Sowohl Nemotron 3 Nano Omni 30B A3B Reasoning (Optimal für nativ multimodale Verarbeitung von Text und Bild sowie visuelle Dokumentenanalyse, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Nemotron 3 Super 120B A12B (Optimal für autonome Agenten-Workflows, zuverlässiges Tool-Calling und mehrstufige Automatisierung, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Nemotron 3 Super 120B A12B führt bei komplexem Reasoning und Coding, Nemotron 3 Nano Omni 30B A3B Reasoning liefert den höheren Token-Durchsatz und Nemotron 3 Nano Omni 30B A3B Reasoning ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Nemotron 3 Nano Omni 30B A3B Reasoning oder Nemotron 3 Super 120B A12B?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Nemotron 3 Super 120B A12B vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Nemotron 3 Nano Omni 30B A3B Reasoning und Nemotron 3 Super 120B A12B?+

Nemotron 3 Nano Omni 30B A3B Reasoning kostet $0.20 / $0.60 pro 1M Input-/Output-Tokens, Nemotron 3 Super 120B A12B liegt bei $0.30 / $0.80. Beim gewichteten Gesamtpreis ist Nemotron 3 Nano Omni 30B A3B Reasoning günstiger.

Welches Modell hat das größere Kontextfenster und die höhere Geschwindigkeit?+

Nemotron 3 Nano Omni 30B A3B Reasoning bietet 256K Tokens Kontext gegenüber 262.1K Tokens bei Nemotron 3 Super 120B A12B. Bei der Generierungsgeschwindigkeit liegt Nemotron 3 Nano Omni 30B A3B Reasoning vorn.

AI Terminology & Guide
Explore Glossary →

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

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

Offizielle Quellen: Offizielle API-Dokumentation von NVIDIA und NVIDIA, Systemkarten und unabhängige Benchmark-Auswertungen (2026).