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Head-to-Head Model Comparison

Nemotron 3.5 Content Safety vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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NVIDIAAnthropicopen-sourceflagship

Compare Nemotron 3.5 Content Safety by NVIDIA against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

आमने-सामने मॉडल तुलना (VS)

किसी भी मॉडल को बदलें और तुलना करें

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Live comparison: no in-depth editorial review has been published for this pair yet.

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NVIDIA

Nemotron 3.5 Content Safety

ओपन-वेट्स मॉडल

NVIDIA द्वारा विकसित Nemotron 3.5 Content Safety एक उन्नत AI मॉडल है, जिसमें 128K टोकन का कॉन्टेक्स्ट विंडो और $0.08/1M इनपुट तथा $0.16/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index39 / 100
Input Token:

$0.08 / 1M

Output Token:

$0.16 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Anthropic

Claude Opus 5.5

डीप रीजनिंग मॉडल

Anthropic द्वारा विकसित Claude Opus 5.5 एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $4.0/1M इनपुट तथा $20.0/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

एक नज़र में मुख्य अंतर

  • Nemotron 3.5 Content Safety is 83.7x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
  • Nemotron 3.5 Content Safety is faster at 160 tok/s vs 78 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3.5 Content SafetyClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
3994
Provider
NVIDIAAnthropic
Input Price
Cost per million input tokens
$0.08 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$0.16 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.05 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
2K128K
Throughput Speed
Tokens generated per second
160 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
N/A84.6%
GPQA Diamond
Graduate-level reasoning
N/A82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$0.40 / 1M

किस क्षेत्र में कौन आगे है?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Nemotron 3.5 Content Safety
83.7x cheaper monthly runtime
Speed
Nemotron 3.5 Content Safety
+105% faster generation
Context
Claude Opus 5.5
1M tokens window

सत्यापित बेंचमार्क स्कोर तुलना

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

Nemotron 3.5 Content SafetyClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

N/Avs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

N/Avs91.5%
LMSYS Chatbot Arena Elo

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

1200ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs66.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

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

N/Avs95.4%
Long-Context Reasoning

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

N/Avs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs78 tok/s

लेटेंसी और रिस्पॉन्स समय

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
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3.5 Content Safety3.35s
Claude Opus 5.57.81s

रियल-टाइम टोकन लागत सिम्युलेटर

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
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Nemotron 3.5 Content Safety saves approximately $24.31 / month (99%) under this workload.83.7x Savings

Nemotron 3.5 Content Safety · Strengths & Key Advantages

  • NVIDIA की उन्नत Multimodal Safety & Compliance Classifier आर्किटेक्चर और 128K कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($0.08/1M इनपुट, $0.16/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
  • जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
  • बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
  • विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है

Claude Opus 5.5 · Strengths & Key Advantages

  • Anthropic की उन्नत Extended Autonomous Hybrid Reasoning Transformer आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($4.0/1M इनपुट, $20.0/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
  • जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
  • बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
  • विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है

Token Use & Task Economics

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

MetricNemotron 3.5 Content SafetyClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.02$3.85
Output Tokens / Task
Tokens generated per task
2K68K
Reasoning Tokens / Task
Thinking tokens burned per task
1K42K

तकनीकी विशिष्टताएँ (Specs)

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3.5 Content SafetyClaude Opus 5.5
Official API Model ID (SDK)nemotron-3-5-content-safetyclaude-opus-5-5-20260901
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-062026-09
Knowledge CutoffApril 2026June 2026
ArchitectureMultimodal Safety & Compliance ClassifierExtended Autonomous Hybrid Reasoning Transformer
Parameters12BConfidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.08/1M in) across full 128K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.02/1M tokens$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentText-only completion (No GUI action loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingPrompt-based JSON extraction onlyNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
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)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Nemotron 3.5 Content Safety vs Claude Opus 5.5: त्वरित प्रश्नोत्तर (FAQ)

Which is more intelligent, Nemotron 3.5 Content Safety or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 39 on the composite Intelligence Index.

Which model is faster?

Nemotron 3.5 Content Safety is faster, generating 160 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Nemotron 3.5 Content Safety is cheaper at $0.05 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron 3.5 Content Safety has lower latency, with a time to first token of 0.22s compared with 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 128K tokens.

निष्कर्ष

Choose Nemotron 3.5 Content Safety for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और nvidia आधारित प्रोडक्शन सिस्टम, or choose Claude Opus 5.5 for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और anthropic आधारित प्रोडक्शन सिस्टम.

अक्सर पूछे जाने वाले प्रश्न (FAQ)

Which is cheaper: Nemotron 3.5 Content Safety or Claude Opus 5.5?+

Nemotron 3.5 Content Safety costs $0.08/1M input and $0.16/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Nemotron 3.5 Content Safety or Claude Opus 5.5?+

Nemotron 3.5 Content Safety supports 128K tokens whereas Claude Opus 5.5 supports 1M tokens.

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.

स्रोत: NVIDIA & Anthropic Official Documentation