Nemotron Cascade 2 30B A3B vs Nemotron 3 Nano 30B A3B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Nemotron Cascade 2 30B A3B by NVIDIA and Nemotron 3 Nano 30B A3B by NVIDIA represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, both models offer identical input token rates. On output generation, costs are matched. In data-heavy architectures requiring extensive repository or document analysis, Nemotron 3 Nano 30B A3B provides an expanded memory horizon with 262K tokens. In latency-sensitive production environments, Nemotron Cascade 2 30B A3B leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
원하는 AI 모델 선택 및 실시간 비교
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Nemotron Cascade 2 30B A3B
오픈 웨이트 모델NVIDIA의 Nemotron Cascade 2 30B A3B 모델은 256K 토큰 컨텍스트 윈도우와 입력 $0.1/1M 토큰, 출력 $0.25/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$0.10 / 1M
$0.25 / 1M
256K tokens
39.5%
Nemotron 3 Nano 30B A3B
오픈 웨이트 모델NVIDIA의 Nemotron 3 Nano 30B A3B 모델은 262K 토큰 컨텍스트 윈도우와 입력 $0.1/1M 토큰, 출력 $0.25/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$0.10 / 1M
$0.25 / 1M
262.1K tokens
38%
한눈에 보는 핵심 차이점
- Both models cost the same under this workload — choose on capability, not price.
- Nemotron 3 Nano 30B A3B has a larger context window (262K vs 256K tokens).
- Nemotron Cascade 2 30B A3B is faster at 155 tok/s vs 130 tok/s.
- Nemotron Cascade 2 30B A3B leads on SWE-bench coding (39.5% vs 38.0%).
| Feature | Nemotron Cascade 2 30B A3B | Nemotron 3 Nano 30B A3B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 46 | 45 |
Provider | NVIDIA | NVIDIA |
Input Price Cost per million input tokens | $0.10 / 1M | $0.10 / 1M |
Output Price Cost per million output tokens | $0.25 / 1M | $0.25 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.06 / 1M | $0.06 / 1M |
Context Window Maximum input + output tokens | 256K tokens~384 A4 pages of text | 262.1K tokens~393 A4 pages of text |
Max Output Tokens Per single request | 16K | 16K |
Throughput Speed Tokens generated per second | 155 tok/s | 130 tok/s |
SWE-bench Verified Real-world software engineering | 39.5% | 38% |
GPQA Diamond Graduate-level reasoning | 55.2% | 54% |
Cached Input Price Prompt caching discount per 1M tokens | $0.02 / 1M | $0.02 / 1M |
부문별 우위 모델
At-a-glance decision framework검증된 벤치마크 점수 비교
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
지연 시간(Latency) 및 응답 속도
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
실시간 API 토큰 비용 시뮬레이터
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Nemotron Cascade 2 30B A3B · Strengths & Key Advantages
- NVIDIA의 첨단 Cascaded Speculative MoE (30B Total / 3B Active) 아키텍처와 최대 256K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $0.1/1M, 출력 $0.25/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Nemotron 3 Nano 30B A3B · Strengths & Key Advantages
- NVIDIA의 첨단 Sparse Mixture-of-Experts (30B Total / 3B Active) 아키텍처와 최대 262K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $0.1/1M, 출력 $0.25/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Nemotron Cascade 2 30B A3B | Nemotron 3 Nano 30B A3B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.11 | $0.12 |
Output Tokens / Task Tokens generated per task | 28K | 28K |
Reasoning Tokens / Task Thinking tokens burned per task | 11K | 10K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | Nemotron Cascade 2 30B A3B | Nemotron 3 Nano 30B A3B |
|---|---|---|
| Official API Model ID (SDK) | nemotron-cascade-2-30b-a3b | nemotron-3-nano-30b-a3b |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-03 | 2025-12 |
| Knowledge Cutoff | January 2026 | October 2025 |
| Architecture | Cascaded Speculative MoE (30B Total / 3B Active) | Sparse Mixture-of-Experts (30B Total / 3B Active) |
| Parameters | 30B (3B active MoE) | 30B (3B active MoE) |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.1/1M in) across full 256K window | Flat rate ($0.1/1M in) across full 262K window |
| Prompt Cache Policy & TTL | Cached input at $0.02/1M tokens | Cached input at $0.02/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full 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 Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Open-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 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text | text |
| Output Modalities | text | text |
Nemotron Cascade 2 30B A3B vs Nemotron 3 Nano 30B A3B: 핵심 요약 문답 (FAQ)
Which is more intelligent, Nemotron Cascade 2 30B A3B or Nemotron 3 Nano 30B A3B?
Nemotron Cascade 2 30B A3B is more intelligent. It scores 46 compared with 45 on the composite Intelligence Index.
Which model is faster?
Nemotron Cascade 2 30B A3B is faster, generating 155 tokens per second compared with 130 tokens per second.
Which model has lower latency?
Nemotron Cascade 2 30B A3B has lower latency, with a time to first token of 0.27s compared with 0.32s.
Which model has a larger context window?
Nemotron 3 Nano 30B A3B has a larger context window, supporting 262.1K tokens compared with 256K tokens.
종합 평가
Verdict & Model Selection Recommendation: Choose Nemotron Cascade 2 30B A3B if your priority is Real-time conversational agents, instant coding autocomplete, and low-latency API services. Its performance in demanding tasks justifies its operational token cost. Choose Nemotron 3 Nano 30B A3B if your workflow prioritizes Local developer workstations, high-concurrency enterprise chatbots, and budget RAG pipelines. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
자주 묻는 질문 (FAQ)
How does Nemotron Cascade 2 30B A3B compare to Nemotron 3 Nano 30B A3B in API token pricing and cost per token?+
Both Nemotron Cascade 2 30B A3B and Nemotron 3 Nano 30B A3B share matched API token pricing at $0.10 per 1M input tokens and $0.25 per 1M output tokens. Because their token economics are identical, your selection should be guided by benchmark latency, memory horizon, and reasoning capabilities rather than operational token fees. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Nemotron Cascade 2 30B A3B or Nemotron 3 Nano 30B A3B?+
Nemotron Cascade 2 30B A3B supports a context window of 256K tokens (~192k words), while Nemotron 3 Nano 30B A3B supports 262K tokens (~197k words). Therefore, Nemotron 3 Nano 30B A3B can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Nemotron Cascade 2 30B A3B or Nemotron 3 Nano 30B A3B?+
Nemotron Cascade 2 30B A3B scores 39.5% on SWE-bench Verified while Nemotron 3 Nano 30B A3B scores 38%. For autonomous software engineering and multi-file debugging, Nemotron Cascade 2 30B A3B holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Nemotron Cascade 2 30B A3B and Nemotron 3 Nano 30B A3B?+
Nemotron Cascade 2 30B A3B features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Nemotron 3 Nano 30B A3B provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Nemotron Cascade 2 30B A3B and Nemotron 3 Nano 30B A3B?+
Nemotron Cascade 2 30B A3B generates approximately 155 tokens per second, while Nemotron 3 Nano 30B A3B delivers 130 tokens per second. In latency-sensitive production environments, Nemotron Cascade 2 30B A3B provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Nemotron Cascade 2 30B A3B and Nemotron 3 Nano 30B A3B to optimize costs?+
Yes! Tiered multi-model routing can optimize for latency and accuracy: you can route high-frequency conversational turns and latency-sensitive queries to Nemotron Cascade 2 30B A3B, and route deep architectural or complex reasoning queries to Nemotron Cascade 2 30B A3B. This balanced routing strategy maximizes system throughput and answer quality.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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: GetInfoUs Independent AI Benchmarks & Official API Specs