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Nemotron 3.5 Content Safety vs Nemotron 3 Content Safety

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
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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

NVIDIA 的 Nemotron 3.5 Content Safety 与 NVIDIA 的 Nemotron 3 Content Safety 是当前备受关注的两款主力 AI 模型。Nemotron 3.5 Content Safety 提供 128K Token 上下文窗口，API 定价为每百万 Token 输入 $0.08 / 输出 $0.16；而 Nemotron 3 Content Safety 提供 128K Token 上下文窗口，定价为每百万 Token 输入 $0.05 / 输出 $0.10。以下为两者的基准测试、延迟与成本全面对比。

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NVIDIA

Nemotron 3.5 Content Safety

开源权重基础大模型

NVIDIA 推出的 Nemotron 3.5 Content Safety 是一款支持私有云服务器自托管、微调与完全数据主权的开源权重基础大模型，具备 128K 上下文窗口、160 Token/秒生成速度与 39/100 综合智能指数（每百万 Token $0.08 输入 / $0.16 输出）。

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

开源权重基础大模型

NVIDIA 推出的 Nemotron 3 Content Safety 是一款支持私有云服务器自托管、微调与完全数据主权的开源权重基础大模型，具备 128K 上下文窗口、190 Token/秒生成速度与 37/100 综合智能指数（每百万 Token $0.05 输入 / $0.1 输出）。

Intelligence Index37 / 100
Input Token:

$0.05 / 1M

Output Token:

$0.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

核心差异一览

  • 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

各项指标谁更胜一筹？

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

权威基准测试得分对比

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

延迟与响应速度

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

实时 Token 成本模拟器

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

  • 提供 128K 上下文窗口与最高 2K 输出容量，核心基准表现优异（Arena Elo 1200）
  • 高达 160 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 220 毫秒
  • 开放模型权重 (12B)，支持通过 vLLM、SGLang 或 Ollama 在私有 GPU 集群上本地部署与微调
Considerations & Trade-offs
  • 在本地以满血精度运行需要较高的 GPU 显存 (VRAM) 与运维基础设施
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

Nemotron 3 Content Safety · Strengths & Key Advantages

  • 提供 128K 上下文窗口与最高 2K 输出容量，核心基准表现优异（Arena Elo 1175）
  • 高达 190 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 160 毫秒
  • 开放模型权重 (8B)，支持通过 vLLM、SGLang 或 Ollama 在私有 GPU 集群上本地部署与微调
Considerations & Trade-offs
  • 在本地以满血精度运行需要较高的 GPU 显存 (VRAM) 与运维基础设施
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

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

技术规格参数

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: 常见问题解答 (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.

综合结论

综合来看，Nemotron 3.5 Content Safety（适合：支持私有云服务器自托管、微调与完全数据主权的开源权重基础任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）与 Nemotron 3 Content Safety（适合：支持私有云服务器自托管、微调与完全数据主权的开源权重基础任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）各具优势：Nemotron 3.5 Content Safety 在综合智能与编程基准测试中表现更强，Nemotron 3 Content Safety 拥有更快的 Token 生成速度，而 Nemotron 3 Content Safety 则在规模化 API 部署中具备更高的成本效益。

常见问题 (FAQ)

在编程和深度推理方面，Nemotron 3.5 Content Safety 和 Nemotron 3 Content Safety 哪个更强？+

在综合智能指数与编程基准评测中，Nemotron 3.5 Content Safety 表现占优。建议结合上方的 SWE-bench Verified 与 GPQA Diamond 跑分根据具体场景选择。

Nemotron 3.5 Content Safety 与 Nemotron 3 Content Safety 的 API 价格哪个更便宜？+

Nemotron 3.5 Content Safety 的 API 价格为输入 $0.08 / 输出 $0.16（每百万 Token），Nemotron 3 Content Safety 为输入 $0.05 / 输出 $0.10。综合混合成本来看，Nemotron 3 Content Safety 更具性价比。

哪款模型拥有更大的上下文窗口和更快的响应速度？+

Nemotron 3.5 Content Safety 支持 128K Token 上下文窗口，而 Nemotron 3 Content Safety 支持 128K Token。在流式生成速度方面，Nemotron 3 Content Safety 的吞吐表现更快。

AI Terminology & Guide
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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.

数据来源: NVIDIA 与 NVIDIA 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。