Head-to-Head Model Comparison

Nemotron 3 Nano Omni 30B A3B Reasoning vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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NVIDIAAnthropicopen-sourceflagship

Compare Nemotron 3 Nano Omni 30B A3B Reasoning by NVIDIA against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

1:1 모델 맞대결 비교 (VS)

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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 Nano Omni 30B A3B Reasoning

네이티브 멀티모달 AI

NVIDIA의 Nemotron 3 Nano Omni 30B A3B Reasoning 모델은 텍스트와 이미지의 네이티브 멀티모달 이해 및 복합 문서·차트 분석에 최적화된 AI 모델로, 256K 컨텍스트 윈도우, 초당 105 토큰의 생성 속도, 종합 지능 지수 48/100점(1M 토큰당 입력 $0.2 / 출력 $0.6)을 제공합니다.

Intelligence Index48 / 100
Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

256K tokens

SWE-bench Verified:

42%

Anthropic

Claude Opus 5.5

플래그십 프론티어 모델

Anthropic의 Claude Opus 5.5 모델은 최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드에 최적화된 AI 모델로, 1M 컨텍스트 윈도우, 초당 78 토큰의 생성 속도, 종합 지능 지수 94/100점(1M 토큰당 입력 $4 / 출력 $20)을 제공합니다.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

한눈에 보는 핵심 차이점

  • Nemotron 3 Nano Omni 30B A3B Reasoning is 26.9x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 256K tokens).
  • Nemotron 3 Nano Omni 30B A3B Reasoning is faster at 105 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 42.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3 Nano Omni 30B A3B ReasoningClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
4894
Provider
NVIDIAAnthropic
Input Price
Cost per million input tokens
$0.20 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$0.60 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.14 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
105 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
42%84.6%
GPQA Diamond
Graduate-level reasoning
56.5%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.40 / 1M

부문별 우위 모델

At-a-glance decision framework
Coding
Claude Opus 5.5
+42.6% SWE-bench lead
Cost
Nemotron 3 Nano Omni 30B A3B Reasoning
26.9x cheaper monthly runtime
Speed
Nemotron 3 Nano Omni 30B A3B Reasoning
+35% faster generation
Context
Claude Opus 5.5
1M tokens window

검증된 벤치마크 점수 비교

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

Nemotron 3 Nano Omni 30B A3B ReasoningClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

42%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

56.5%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

77.2%vs91.5%
LMSYS Chatbot Arena Elo

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

1310ptsvs1507pts
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.

36.5%vs66.4%
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.

66%vs95.4%
Long-Context Reasoning

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

78%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs78 tok/s

지연 시간(Latency) 및 응답 속도

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 Nano Omni 30B A3B Reasoning0.38s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3 Nano Omni 30B A3B Reasoning5.14s
Claude Opus 5.57.81s

실시간 API 토큰 비용 시뮬레이터

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 Nano Omni 30B A3B Reasoning Monthly API Bill
$0.92 / month
$0.2/1M in · $0.6/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Nemotron 3 Nano Omni 30B A3B Reasoning saves approximately $23.69 / month (96%) under this workload.26.9x Savings

Nemotron 3 Nano Omni 30B A3B Reasoning · Strengths & Key Advantages

  • 256K 컨텍스트 윈도우 및 최대 16K 출력 토큰 생성 지원 (SWE-bench Verified 42% · GPQA Diamond 56.5%)
  • 초당 105 토큰의 빠른 처리 속도와 380ms에 불과한 첫 토큰 지연 시간(TTFT)
  • 오픈 웨이트 아키텍처 (30B (3B MoE))를 통해 vLLM, SGLang, Ollama 기반 자체 GPU 서버 구축 및 파인튜닝 가능
Considerations & Trade-offs
  • 비양자화 전체 정밀도로 로컬 서버에서 구동하려면 충분한 GPU VRAM 용량이 필요합니다
  • 초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Claude Opus 5.5 · Strengths & Key Advantages

  • 1M 컨텍스트 윈도우 및 최대 128K 출력 토큰 생성 지원 (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
  • 초당 78 토큰의 빠른 처리 속도와 1400ms에 불과한 첫 토큰 지연 시간(TTFT)
  • 합리적인 API 요금 체계(1M 토큰당 입력 $4 / 출력 $20)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원
Considerations & Trade-offs
  • 독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
  • 대규모 프로덕션 호출 환경에서는 비용 절감을 위해 프롬프트 캐싱과 배치 API(Batch API) 활용이 권장됩니다

Token Use & Task Economics

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

MetricNemotron 3 Nano Omni 30B A3B ReasoningClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.22$3.85
Output Tokens / Task
Tokens generated per task
28K68K
Reasoning Tokens / Task
Thinking tokens burned per task
12K42K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3 Nano Omni 30B A3B ReasoningClaude Opus 5.5
Official API Model ID (SDK)nemotron-3-nano-omni-30b-a3bclaude-opus-5-5-20260901
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-042026-09
Knowledge CutoffFebruary 2026June 2026
ArchitectureOmnimodal Sparse MoE (30B Total / 3B Active)Extended Autonomous Hybrid Reasoning Transformer
Parameters30B (3B active MoE)Confidential
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 ($0.2/1M in) across full 256K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.05/1M tokens$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative 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) · Audio (~25–32 tokens/sec)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) · 19 GB VRAM (4-bit Quantized) · 65 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, vision, audiotext, vision
Output Modalitiestexttext

Nemotron 3 Nano Omni 30B A3B Reasoning vs Claude Opus 5.5: 핵심 요약 문답 (FAQ)

Which is more intelligent, Nemotron 3 Nano Omni 30B A3B Reasoning or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 48 on the composite Intelligence Index.

Which model is faster?

Nemotron 3 Nano Omni 30B A3B Reasoning is faster, generating 105 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Nemotron 3 Nano Omni 30B A3B Reasoning is cheaper at $0.14 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron 3 Nano Omni 30B A3B Reasoning has lower latency, with a time to first token of 0.38s 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 256K tokens.

종합 평가

Choose Nemotron 3 Nano Omni 30B A3B Reasoning for 텍스트와 이미지의 네이티브 멀티모달 이해 및 복합 문서·차트 분석, 엔터프라이즈 rag 지식베이스 및 대규모 프로덕션 api 연동에 최적., or choose Claude Opus 5.5 for 최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드, 엔터프라이즈 rag 지식베이스 및 대규모 프로덕션 api 연동에 최적..

자주 묻는 질문 (FAQ)

Which is cheaper: Nemotron 3 Nano Omni 30B A3B Reasoning or Claude Opus 5.5?+

Nemotron 3 Nano Omni 30B A3B Reasoning costs $0.2/1M input and $0.6/1M 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 Nano Omni 30B A3B Reasoning or Claude Opus 5.5?+

Nemotron 3 Nano Omni 30B A3B Reasoning supports 256K 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.

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.

공식 출처: NVIDIA & Anthropic Official Documentation