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Nemotron 3 Content Safety vs Nemotron Content Safety Reasoning 4B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Nemotron 3 Content Safety vs Nemotron Content Safety Reasoning 4B: Benchmarks, Pricing & Speed Comparison

Nemotron 3 Content Safety von NVIDIA und Nemotron Content Safety Reasoning 4B von NVIDIA gehören zu den führenden KI-Modellen. Nemotron 3 Content Safety bietet ein Kontextfenster von 128K Tokens bei API-Preisen von $0.05/$0.10 pro 1M Tokens, während Nemotron Content Safety Reasoning 4B 128K Tokens Kontext zu $0.05/$0.15 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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NVIDIA

Nemotron 3 Content Safety

Open-Weights-Basismodell

Nemotron 3 Content Safety von NVIDIA ist ein KI-Modell für Self-Hosting im eigenen Rechenzentrum, Fine-Tuning und volle Datensouveränität mit 128K Kontextfenster, 190 Token/s Durchsatz, einem Intelligenz-Index von 37/100 und $0.05/$0.1 pro

Intelligence Index37 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

NVIDIA

Nemotron Content Safety Reasoning 4B

Open-Weights-Reasoning-Modell

Nemotron Content Safety Reasoning 4B von NVIDIA ist ein KI-Modell für Open-Weights-Reasoning mit transparenter Gedankenketten-Verarbeitung (Chain-of-Thought) mit 128K Kontextfenster, 150 Token/s Durchsatz, einem Intelligenz-Index von 38/100

Intelligence Index38 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.15 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Wichtigste Unterschiede auf einen Blick

  • Nemotron 3 Content Safety is 1.3x cheaper for API usage (input + output tokens combined).
  • Nemotron 3 Content Safety is faster at 190 tok/s vs 150 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3 Content SafetyNemotron Content Safety Reasoning 4B
Intelligence Index
Composite reasoning & knowledge score (0-100)
3738
Provider
NVIDIANVIDIA
Input Price
Cost per million input tokens
$0.05 / 1M$0.05 / 1M
Output Price
Cost per million output tokens
$0.10 / 1M$0.15 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.03 / 1M$0.03 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
2K4K
Throughput Speed
Tokens generated per second
190 tok/s150 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A
Cached Input Price
Prompt caching discount per 1M tokens
$0.01 / 1M$0.01 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Nemotron 3 Content Safety
1.3x cheaper monthly runtime
Speed
Nemotron 3 Content Safety
+27% faster generation
Context
Tied
128K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Nemotron 3 Content SafetyNemotron Content Safety Reasoning 4B
LMSYS Chatbot Arena Elo

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

1175ptsvs1190pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

190 tok/s vs150 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 Content Safety0.16s
Nemotron Content Safety Reasoning 4B0.24s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3 Content Safety2.79s
Nemotron Content Safety Reasoning 4B3.57s

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 Content Safety Monthly API Bill
$0.18 / month
$0.05/1M in · $0.1/1M out
Nemotron Content Safety Reasoning 4B Monthly API Bill
$0.23 / month
$0.05/1M in · $0.15/1M out
Nemotron 3 Content Safety saves approximately $0.05 / month (20%) under this workload.1.3x Savings

Nemotron 3 Content Safety · Strengths & Key Advantages

  • 128K Kontextfenster und bis zu 2K maximale Output-Token (Arena Elo 1175)
  • Hohe Generierungsgeschwindigkeit von 190 Token/Sekunde bei nur 160 ms Erstlatenz (TTFT)
  • Offene Modellgewichte (8B) 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 Content Safety Reasoning 4B · Strengths & Key Advantages

  • 128K Kontextfenster und bis zu 4K maximale Output-Token (Arena Elo 1190)
  • Hohe Generierungsgeschwindigkeit von 150 Token/Sekunde bei nur 240 ms Erstlatenz (TTFT)
  • Offene Modellgewichte (4B) 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 Content SafetyNemotron Content Safety Reasoning 4B
Cost per Task
Estimated USD to finish one task
$0.01$0.02
Output Tokens / Task
Tokens generated per task
2K4K
Reasoning Tokens / Task
Thinking tokens burned per task
0K2K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3 Content SafetyNemotron Content Safety Reasoning 4B
Official API Model ID (SDK)nemotron-3-content-safetynemotron-content-safety-reasoning-4b
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-042026-01
Knowledge CutoffFebruary 2026November 2025
ArchitectureEnterprise Safety Classifier TransformerReasoning-Augmented Safety Classifier
Parameters8B4B
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 ($0.05/1M in) across full 128K windowFlat rate ($0.05/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.01/1M tokensCached input at $0.01/1M tokens
Computer Use / GUI AgentText-only completion (No GUI action loop)Text-only completion (No GUI action loop)
MCP & Parallel Tool CallingPrompt-based JSON extraction onlyPrompt-based JSON extraction only
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)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 9 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 Modalitiestexttext
Output Modalitiestexttext

Nemotron 3 Content Safety vs Nemotron Content Safety Reasoning 4B: Schnelle Antworten (FAQ)

Which is more intelligent, Nemotron 3 Content Safety or Nemotron Content Safety Reasoning 4B?

Nemotron Content Safety Reasoning 4B is more intelligent. It scores 38 compared with 37 on the composite Intelligence Index.

Which model is faster?

Nemotron 3 Content Safety is faster, generating 190 tokens per second compared with 150 tokens per second.

Which model has lower latency?

Nemotron 3 Content Safety has lower latency, with a time to first token of 0.16s compared with 0.24s.

Fazit

Sowohl Nemotron 3 Content Safety (Optimal für Self-Hosting im eigenen Rechenzentrum, Fine-Tuning und volle Datensouveränität, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Nemotron Content Safety Reasoning 4B (Optimal für Open-Weights-Reasoning mit transparenter Gedankenketten-Verarbeitung (Chain-of-Thought), Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Nemotron Content Safety Reasoning 4B führt bei komplexem Reasoning und Coding, Nemotron 3 Content Safety liefert den höheren Token-Durchsatz und Nemotron 3 Content Safety ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Nemotron 3 Content Safety oder Nemotron Content Safety Reasoning 4B?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Nemotron Content Safety Reasoning 4B vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Nemotron 3 Content Safety und Nemotron Content Safety Reasoning 4B?+

Nemotron 3 Content Safety kostet $0.05 / $0.10 pro 1M Input-/Output-Tokens, Nemotron Content Safety Reasoning 4B liegt bei $0.05 / $0.15. Beim gewichteten Gesamtpreis ist Nemotron 3 Content Safety günstiger.

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

Nemotron 3 Content Safety bietet 128K Tokens Kontext gegenüber 128K Tokens bei Nemotron Content Safety Reasoning 4B. Bei der Generierungsgeschwindigkeit liegt Nemotron 3 Content Safety 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).