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Nemotron 3.5 Content Safety vs Nemotron 3 Content Safety

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Nemotron 3.5 Content Safety vs Nemotron 3 Content Safety: Benchmarks, Pricing & Speed Comparison

Nemotron 3.5 Content Safety di NVIDIA e Nemotron 3 Content Safety di NVIDIA sono due modelli di IA di riferimento. Nemotron 3.5 Content Safety offre una finestra di contesto di 128K token a $0.08/$0.16 per milione di token, mentre Nemotron 3 Content Safety mette a disposizione 128K token di contesto a $0.05/$0.10 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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NVIDIA

Nemotron 3.5 Content Safety

Modello Base a Pesi Aperti

Nemotron 3.5 Content Safety di NVIDIA è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 128K, velocità di 160 token/s, indice di intelligen

Intelligence Index39 / 100
Input Token:

$0.08 / 1M

Output Token:

$0.16 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

NVIDIA

Nemotron 3 Content Safety

Modello Base a Pesi Aperti

Nemotron 3 Content Safety di NVIDIA è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 128K, velocità di 190 token/s, indice di intelligenza

Intelligence Index37 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

  • Nemotron 3 Content Safety is 1.6x cheaper for API usage (input + output tokens combined).
  • Nemotron 3 Content Safety is faster at 190 tok/s vs 160 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3.5 Content SafetyNemotron 3 Content Safety
Intelligence Index
Composite reasoning & knowledge score (0-100)
3937
Provider
NVIDIANVIDIA
Input Price
Cost per million input tokens
$0.08 / 1M$0.05 / 1M
Output Price
Cost per million output tokens
$0.16 / 1M$0.10 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.05 / 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
2K2K
Throughput Speed
Tokens generated per second
160 tok/s190 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$0.01 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Nemotron 3 Content Safety
1.6x cheaper monthly runtime
Speed
Nemotron 3 Content Safety
+19% faster generation
Context
Tied
128K tokens window

Punteggi Benchmark Verificati

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

Nemotron 3.5 Content SafetyNemotron 3 Content Safety
LMSYS Chatbot Arena Elo

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

1200ptsvs1175pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs190 tok/s

Latenza e Tempo di Risposta

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 3.5 Content Safety0.22s
Nemotron 3 Content Safety0.16s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3.5 Content Safety3.35s
Nemotron 3 Content Safety2.79s

Simulatore Interattivo dei Costi Token

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 3.5 Content Safety Monthly API Bill
$0.29 / month
$0.08/1M in · $0.16/1M out
Nemotron 3 Content Safety Monthly API Bill
$0.18 / month
$0.05/1M in · $0.1/1M out
Nemotron 3 Content Safety saves approximately $0.11 / month (39%) under this workload.1.6x Savings

Nemotron 3.5 Content Safety · Strengths & Key Advantages

  • Finestra di contesto da 128K con capacità massima di output fino a 2K token (Arena Elo 1200)
  • Throughput elevato di 160 token/secondo con latenza al primo token (TTFT) di soli 220 ms
  • Pesi aperti (12B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
  • Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Nemotron 3 Content Safety · Strengths & Key Advantages

  • Finestra di contesto da 128K con capacità massima di output fino a 2K token (Arena Elo 1175)
  • Throughput elevato di 190 token/secondo con latenza al primo token (TTFT) di soli 160 ms
  • Pesi aperti (8B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
  • Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

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

MetricNemotron 3.5 Content SafetyNemotron 3 Content Safety
Cost per Task
Estimated USD to finish one task
$0.02$0.01
Output Tokens / Task
Tokens generated per task
2K2K
Reasoning Tokens / Task
Thinking tokens burned per task
1K0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3.5 Content SafetyNemotron 3 Content Safety
Official API Model ID (SDK)nemotron-3-5-content-safetynemotron-3-content-safety
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-062026-04
Knowledge CutoffApril 2026February 2026
ArchitectureMultimodal Safety & Compliance ClassifierEnterprise Safety Classifier Transformer
Parameters12B8B
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 ($0.08/1M in) across full 128K windowFlat rate ($0.05/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.02/1M 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) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 7 GB VRAM (4-bit Quantized) · 26 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 Modalitiestext, visiontext
Output Modalitiestexttext

Nemotron 3.5 Content Safety vs Nemotron 3 Content Safety: Risposte Rapide (FAQ)

Which is more intelligent, Nemotron 3.5 Content Safety or Nemotron 3 Content Safety?

Nemotron 3.5 Content Safety is more intelligent. It scores 39 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 160 tokens per second.

Which model is cheaper to run?

Nemotron 3 Content Safety is cheaper at $0.03 per 1M tokens blended, compared with $0.05 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron 3 Content Safety has lower latency, with a time to first token of 0.16s compared with 0.22s.

Verdetto

Sia Nemotron 3.5 Content Safety (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) sia Nemotron 3 Content Safety (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Nemotron 3.5 Content Safety guida nei benchmark di ragionamento e programmazione, Nemotron 3 Content Safety garantisce una generazione più rapida e Nemotron 3 Content Safety offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Nemotron 3.5 Content Safety o Nemotron 3 Content Safety?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Nemotron 3.5 Content Safety. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Nemotron 3.5 Content Safety e Nemotron 3 Content Safety?+

Nemotron 3.5 Content Safety costa $0.08 / $0.16 per milione di token di input/output, mentre Nemotron 3 Content Safety costa $0.05 / $0.10. Nel costo combinato, Nemotron 3 Content Safety risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Nemotron 3.5 Content Safety supporta 128K token di contesto contro 128K token di Nemotron 3 Content Safety, mentre Nemotron 3 Content Safety offre una velocità di generazione superiore.

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.

Fonti ufficiali: Documentazione API ufficiale di NVIDIA e NVIDIA, schede di sistema e benchmark indipendenti (2026).