Head-to-Head Model Comparison

Nemotron 3 Ultra 550B A55B vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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Compare Nemotron 3 Ultra 550B A55B by NVIDIA against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

徹底比較 (VS)

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NVIDIA

Nemotron 3 Ultra 550B A55B

オープンウェイト基盤モデル

NVIDIA の Nemotron 3 Ultra 550B A55B は、オンプレミス環境でのセルフホスト、ファインチューニング、完全なデータ主権の確保向けに設計されたAIモデルです。1M のコンテキストウィンドウ、毎秒 65 トークンの生成速度、知能指数 60/100(1Mトークンあたり入力$1・出力$3)を実現しています。

Intelligence Index60 / 100
Input Token:

$1.00 / 1M

Output Token:

$3.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

64.5%

OpenAI

GPT-6 Astra

音声・スピーチAIモデル

OpenAI の GPT-6 Astra は、自然な音声合成(TTS)、リアルタイム音声対話、高精度な文字起こし向けに設計されたAIモデルです。272K のコンテキストウィンドウ、毎秒 100 トークンの生成速度、知能指数 96/100(1Mトークンあたり入力$10・出力$50)を実現しています。

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

ひと目でわかる主な違い

  • Nemotron 3 Ultra 550B A55B is 13.4x cheaper for API usage (input + output tokens combined).
  • Nemotron 3 Ultra 550B A55B has a larger context window (1M vs 272K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 65 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 64.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3 Ultra 550B A55BGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
6096
Provider
NVIDIAOpenAI
Input Price
Cost per million input tokens
$1.00 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$3.00 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.68 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
66K128K
Throughput Speed
Tokens generated per second
65 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
64.5%82.4%
GPQA Diamond
Graduate-level reasoning
76%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.25 / 1M$1.00 / 1M

分野別勝者スコアカード

At-a-glance decision framework
Coding
GPT-6 Astra
+17.9% SWE-bench lead
Cost
Nemotron 3 Ultra 550B A55B
13.4x cheaper monthly runtime
Speed
GPT-6 Astra
+54% faster generation
Context
Nemotron 3 Ultra 550B A55B
1M tokens window

検証済みベンチマークスコア比較

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

Nemotron 3 Ultra 550B A55BGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

64.5%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

76%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

87.5%vs89.9%
LMSYS Chatbot Arena Elo

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

1425ptsvs1520pts
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.

53%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.

86%vs93.6%
Long-Context Reasoning

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

89%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

65 tok/s vs100 tok/s

レイテンシ&応答時間

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 Ultra 550B A55B0.62s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3 Ultra 550B A55B8.31s
GPT-6 Astra5.95s

リアルタイムAPIトークン料金シミュレーター

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 Ultra 550B A55B Monthly API Bill
$4.58 / month
$1/1M in · $3/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Nemotron 3 Ultra 550B A55B saves approximately $56.92 / month (93%) under this workload.13.4x Savings

Nemotron 3 Ultra 550B A55B · Strengths & Key Advantages

  • 1M のコンテキストウィンドウと最大 66K トークンの出力容量(SWE-bench Verified 64.5% · GPQA Diamond 76%)
  • 毎秒 65 トークンの高速スループットと、初回トークン到達時間(TTFT)わずか 620ms の低遅延
  • オープンウェイトモデル (550B (55B MoE))として vLLM・SGLang・Ollama を用いた自社GPUでのローカル運用が可能
Considerations & Trade-offs
  • 非量子化のフル精度でローカル推論を行うには十分なGPU VRAM容量が必要です
  • 極めて高度な専門科学の証明問題では、上位の大型推論特化モデルの方がより深い洞察を提供する場合があります

GPT-6 Astra · Strengths & Key Advantages

  • 272K のコンテキストウィンドウと最大 128K トークンの出力容量(SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
  • 毎秒 100 トークンの高速スループットと、初回トークン到達時間(TTFT)わずか 950ms の低遅延
  • 優れたAPI経済性(1Mトークンあたり入力$10・出力$50)に加え、プロンプトキャッシュや構造化JSON出力・関数呼び出しに完全対応
Considerations & Trade-offs
  • クラウド専用のプロプライエタリモデルのため、モデル重みをダウンロードしてオフライン実行することはできません
  • 大量のトークンを処理する本番環境では、プロンプトキャッシュや Batch API の併用によるコスト最適化が推奨されます

Token Use & Task Economics

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

MetricNemotron 3 Ultra 550B A55BGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.85$2.15
Output Tokens / Task
Tokens generated per task
48K58K
Reasoning Tokens / Task
Thinking tokens burned per task
24K32K

技術仕様・スペック

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3 Ultra 550B A55BGPT-6 Astra
Official API Model ID (SDK)nemotron-3-ultra-550b-a55bgpt-6-astra
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2026-062026-09
Knowledge CutoffFebruary 2026June 2026
ArchitectureColossal Sparse MoE (550B Total / 55B Active)Omni-Adaptive Autoregressive with Dynamic CoT
Parameters550B (55B 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 ($1/1M in) across full 1000K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLCached input at $0.25/1M 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) · 341 GB VRAM (4-bit Quantized) · 1183 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 3 Ultra 550B A55B vs GPT-6 Astra: よくある質問 (FAQ)

Which is more intelligent, Nemotron 3 Ultra 550B A55B or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 60 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

Nemotron 3 Ultra 550B A55B is cheaper at $0.68 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron 3 Ultra 550B A55B has lower latency, with a time to first token of 0.62s compared with 0.95s.

Which model has a larger context window?

Nemotron 3 Ultra 550B A55B has a larger context window, supporting 1M tokens compared with 272K tokens.

総合評価

Choose Nemotron 3 Ultra 550B A55B for オンプレミス環境でのセルフホスト、ファインチューニング、完全なデータ主権の確保、エンタープライズrag基盤、スケーラブルな本番api統合に最適。, or choose GPT-6 Astra for 自然な音声合成(tts)、リアルタイム音声対話、高精度な文字起こし、エンタープライズrag基盤、スケーラブルな本番api統合に最適。.

よくある質問 (FAQ)

Which is cheaper: Nemotron 3 Ultra 550B A55B or GPT-6 Astra?+

Nemotron 3 Ultra 550B A55B costs $1/1M input and $3/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: Nemotron 3 Ultra 550B A55B or GPT-6 Astra?+

Nemotron 3 Ultra 550B A55B supports 1M 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.

公的ソース: NVIDIA & OpenAI Official Documentation