Head-to-Head Model Comparison

Nemotron Cascade 2 30B A3B vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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Compare Nemotron Cascade 2 30B A3B by NVIDIA against GPT-6 Astra by OpenAI 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 Cascade 2 30B A3B

오픈 웨이트 추론 모델

NVIDIA의 Nemotron Cascade 2 30B A3B 모델은 강화학습 기반의 고효율 오픈 웨이트 사고 사슬(Chain-of-Thought) 추론에 최적화된 AI 모델로, 256K 컨텍스트 윈도우, 초당 155 토큰의 생성 속도, 종합 지능 지수 46/100점(1M 토큰당 입력 $0.1 / 출력 $0.25)을 제공합니다.

Intelligence Index46 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.25 / 1M

Context Window:

256K tokens

SWE-bench Verified:

39.5%

OpenAI

GPT-6 Astra

네이티브 음성 및 오디오 모델

OpenAI의 GPT-6 Astra 모델은 자연스러운 음성 합성(TTS), 실시간 오디오 처리 및 고정밀 음성 인식에 최적화된 AI 모델로, 272K 컨텍스트 윈도우, 초당 100 토큰의 생성 속도, 종합 지능 지수 96/100점(1M 토큰당 입력 $10 / 출력 $50)을 제공합니다.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

한눈에 보는 핵심 차이점

  • Nemotron Cascade 2 30B A3B is 151.9x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 256K tokens).
  • Nemotron Cascade 2 30B A3B is faster at 155 tok/s vs 100 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 39.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron Cascade 2 30B A3BGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
4696
Provider
NVIDIAOpenAI
Input Price
Cost per million input tokens
$0.10 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$0.25 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.06 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
155 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
39.5%82.4%
GPQA Diamond
Graduate-level reasoning
55.2%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$1.00 / 1M

부문별 우위 모델

At-a-glance decision framework
Coding
GPT-6 Astra
+42.9% SWE-bench lead
Cost
Nemotron Cascade 2 30B A3B
151.9x cheaper monthly runtime
Speed
Nemotron Cascade 2 30B A3B
+55% faster generation
Context
GPT-6 Astra
272K tokens window

검증된 벤치마크 점수 비교

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

Nemotron Cascade 2 30B A3BGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

39.5%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

55.2%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

76%vs89.9%
LMSYS Chatbot Arena Elo

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

1295ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

35%vs63.8%
SciCode (Scientific Computing)

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

N/Avs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.8%
AIME (Advanced Math Competition)

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

65%vs93.6%
Long-Context Reasoning

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

77%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

155 tok/s vs100 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 Cascade 2 30B A3B0.27s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron Cascade 2 30B A3B3.50s
GPT-6 Astra5.95s

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 Cascade 2 30B A3B Monthly API Bill
$0.41 / month
$0.1/1M in · $0.25/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Nemotron Cascade 2 30B A3B saves approximately $61.09 / month (99%) under this workload.151.9x Savings

Nemotron Cascade 2 30B A3B · Strengths & Key Advantages

  • 256K 컨텍스트 윈도우 및 최대 16K 출력 토큰 생성 지원 (SWE-bench Verified 39.5% · GPQA Diamond 55.2%)
  • 초당 155 토큰의 빠른 처리 속도와 270ms에 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

GPT-6 Astra · Strengths & Key Advantages

  • 272K 컨텍스트 윈도우 및 최대 128K 출력 토큰 생성 지원 (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
  • 초당 100 토큰의 빠른 처리 속도와 950ms에 불과한 첫 토큰 지연 시간(TTFT)
  • 합리적인 API 요금 체계(1M 토큰당 입력 $10 / 출력 $50)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 Cascade 2 30B A3BGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.11$2.15
Output Tokens / Task
Tokens generated per task
28K58K
Reasoning Tokens / Task
Thinking tokens burned per task
11K32K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron Cascade 2 30B A3BGPT-6 Astra
Official API Model ID (SDK)nemotron-cascade-2-30b-a3bgpt-6-astra
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2026-032026-09
Knowledge CutoffJanuary 2026June 2026
ArchitectureCascaded Speculative MoE (30B Total / 3B Active)Omni-Adaptive Autoregressive with Dynamic CoT
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 Cloud10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.1/1M in) across full 256K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLCached input at $0.02/1M tokensAutomatic prefix caching at $1/1M (no extra cache-write fee)
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 tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
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)OpenAI Preparedness Framework Audited & System Card Published
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 Modalitiestexttext, vision, audio
Output Modalitiestexttext, audio

Nemotron Cascade 2 30B A3B vs GPT-6 Astra: 핵심 요약 문답 (FAQ)

Which is more intelligent, Nemotron Cascade 2 30B A3B or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 46 on the composite Intelligence Index.

Which model is faster?

Nemotron Cascade 2 30B A3B is faster, generating 155 tokens per second compared with 100 tokens per second.

Which model is cheaper to run?

Nemotron Cascade 2 30B A3B is cheaper at $0.06 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron Cascade 2 30B A3B has lower latency, with a time to first token of 0.27s compared with 0.95s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K tokens compared with 256K tokens.

종합 평가

Choose Nemotron Cascade 2 30B A3B for 강화학습 기반의 고효율 오픈 웨이트 사고 사슬(chain-of-thought) 추론, 엔터프라이즈 rag 지식베이스 및 대규모 프로덕션 api 연동에 최적., or choose GPT-6 Astra for 자연스러운 음성 합성(tts), 실시간 오디오 처리 및 고정밀 음성 인식, 엔터프라이즈 rag 지식베이스 및 대규모 프로덕션 api 연동에 최적..

자주 묻는 질문 (FAQ)

Which is cheaper: Nemotron Cascade 2 30B A3B or GPT-6 Astra?+

Nemotron Cascade 2 30B A3B costs $0.1/1M input and $0.25/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: Nemotron Cascade 2 30B A3B or GPT-6 Astra?+

Nemotron Cascade 2 30B A3B supports 256K tokens whereas GPT-6 Astra supports 272K 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 & OpenAI Official Documentation