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Nemotron Content Safety Reasoning 4B vs Llama 3.1 Nemotron Safety Guard 8B v3

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 Content Safety Reasoning 4B vs Llama 3.1 Nemotron Safety Guard 8B v3: Benchmarks, Pricing & Speed Comparison

Nemotron Content Safety Reasoning 4B von NVIDIA und Llama 3.1 Nemotron Safety Guard 8B v3 von NVIDIA gehören zu den führenden KI-Modellen. Nemotron Content Safety Reasoning 4B bietet ein Kontextfenster von 128K Tokens bei API-Preisen von $0.05/$0.15 pro 1M Tokens, während Llama 3.1 Nemotron Safety Guard 8B v3 128K Tokens Kontext zu $0.05/$0.10 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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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

NVIDIA

Llama 3.1 Nemotron Safety Guard 8B v3

Open-Weights-Basismodell

Llama 3.1 Nemotron Safety Guard 8B v3 von NVIDIA ist ein KI-Modell für Self-Hosting im eigenen Rechenzentrum, Fine-Tuning und volle Datensouveränität mit 128K Kontextfenster, 180 Token/s Durchsatz, einem Intelligenz-Index von 36/100 und $0.

Intelligence Index36 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Wichtigste Unterschiede auf einen Blick

  • Llama 3.1 Nemotron Safety Guard 8B v3 is 1.3x cheaper for API usage (input + output tokens combined).
  • Llama 3.1 Nemotron Safety Guard 8B v3 is faster at 180 tok/s vs 150 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron Content Safety Reasoning 4BLlama 3.1 Nemotron Safety Guard 8B v3
Intelligence Index
Composite reasoning & knowledge score (0-100)
3836
Provider
NVIDIANVIDIA
Input Price
Cost per million input tokens
$0.05 / 1M$0.05 / 1M
Output Price
Cost per million output tokens
$0.15 / 1M$0.10 / 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
4K2K
Throughput Speed
Tokens generated per second
150 tok/s180 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
Llama 3.1 Nemotron Safety Guard 8B v3
1.3x cheaper monthly runtime
Speed
Llama 3.1 Nemotron Safety Guard 8B v3
+20% faster generation
Context
Tied
128K tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Nemotron Content Safety Reasoning 4BLlama 3.1 Nemotron Safety Guard 8B v3
LMSYS Chatbot Arena Elo

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

1190ptsvs1160pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

150 tok/s vs180 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 Content Safety Reasoning 4B0.24s
Llama 3.1 Nemotron Safety Guard 8B v30.18s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron Content Safety Reasoning 4B3.57s
Llama 3.1 Nemotron Safety Guard 8B v32.96s

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 Content Safety Reasoning 4B Monthly API Bill
$0.23 / month
$0.05/1M in · $0.15/1M out
Llama 3.1 Nemotron Safety Guard 8B v3 Monthly API Bill
$0.18 / month
$0.05/1M in · $0.1/1M out
Llama 3.1 Nemotron Safety Guard 8B v3 saves approximately $0.05 / month (20%) under this workload.1.3x Savings

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

Llama 3.1 Nemotron Safety Guard 8B v3 · Strengths & Key Advantages

  • 128K Kontextfenster und bis zu 2K maximale Output-Token (Arena Elo 1160)
  • Hohe Generierungsgeschwindigkeit von 180 Token/Sekunde bei nur 180 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

Token Use & Task Economics

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

MetricNemotron Content Safety Reasoning 4BLlama 3.1 Nemotron Safety Guard 8B v3
Cost per Task
Estimated USD to finish one task
$0.02$0.01
Output Tokens / Task
Tokens generated per task
4K2K
Reasoning Tokens / Task
Thinking tokens burned per task
2K0K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron Content Safety Reasoning 4BLlama 3.1 Nemotron Safety Guard 8B v3
Official API Model ID (SDK)nemotron-content-safety-reasoning-4bllama-3-1-nemotron-safety-guard-8b-v3
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-012025-10
Knowledge CutoffNovember 2025August 2025
ArchitectureReasoning-Augmented Safety ClassifierSpecialized Guardrail Classifier Transformer
Parameters4B8B
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) · 2 GB VRAM (4-bit Quantized) · 9 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 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 Content Safety Reasoning 4B vs Llama 3.1 Nemotron Safety Guard 8B v3: Schnelle Antworten (FAQ)

Which is more intelligent, Nemotron Content Safety Reasoning 4B or Llama 3.1 Nemotron Safety Guard 8B v3?

Nemotron Content Safety Reasoning 4B is more intelligent. It scores 38 compared with 36 on the composite Intelligence Index.

Which model is faster?

Llama 3.1 Nemotron Safety Guard 8B v3 is faster, generating 180 tokens per second compared with 150 tokens per second.

Which model has lower latency?

Llama 3.1 Nemotron Safety Guard 8B v3 has lower latency, with a time to first token of 0.18s compared with 0.24s.

Fazit

Sowohl Nemotron Content Safety Reasoning 4B (Optimal für Open-Weights-Reasoning mit transparenter Gedankenketten-Verarbeitung (Chain-of-Thought), Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Llama 3.1 Nemotron Safety Guard 8B v3 (Optimal für Self-Hosting im eigenen Rechenzentrum, Fine-Tuning und volle Datensouveränität, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Nemotron Content Safety Reasoning 4B führt bei komplexem Reasoning und Coding, Llama 3.1 Nemotron Safety Guard 8B v3 liefert den höheren Token-Durchsatz und Llama 3.1 Nemotron Safety Guard 8B v3 ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Nemotron Content Safety Reasoning 4B oder Llama 3.1 Nemotron Safety Guard 8B v3?+

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 Content Safety Reasoning 4B und Llama 3.1 Nemotron Safety Guard 8B v3?+

Nemotron Content Safety Reasoning 4B kostet $0.05 / $0.15 pro 1M Input-/Output-Tokens, Llama 3.1 Nemotron Safety Guard 8B v3 liegt bei $0.05 / $0.10. Beim gewichteten Gesamtpreis ist Llama 3.1 Nemotron Safety Guard 8B v3 günstiger.

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

Nemotron Content Safety Reasoning 4B bietet 128K Tokens Kontext gegenüber 128K Tokens bei Llama 3.1 Nemotron Safety Guard 8B v3. Bei der Generierungsgeschwindigkeit liegt Llama 3.1 Nemotron Safety Guard 8B v3 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).