Nemotron Nano 9B v2 vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Nemotron Nano 9B v2 by NVIDIA against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Nemotron Nano 9B v2
Компактная экономичная модельNemotron Nano 9B v2 от NVIDIA — специализированная ИИ-модель для максимальной экономической эффективности на токен и быстрого продакшен-инференса, обеспечивающая контекстное окно 131K, скорость 140 ток/с и индекс интеллекта 42/100 (по цене
$0.08 / 1M
$0.20 / 1M
131.1K tokens
32.5%
GPT-6 Astra
Модель речи и аудиоGPT-6 Astra от OpenAI — специализированная ИИ-модель для естественного синтеза речи, обработки аудио в реальном времени и транскрибации, обеспечивающая контекстное окно 272K, скорость 100 ток/с и индекс интеллекта 96/100 (по цене $10/$50 за
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Ключевые отличия кратко
- Nemotron Nano 9B v2 is 186.4x cheaper for API usage (input + output tokens combined).
- GPT-6 Astra has a larger context window (272K vs 131K tokens).
- Nemotron Nano 9B v2 is faster at 140 tok/s vs 100 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 32.5%).
| Feature | Nemotron Nano 9B v2 | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 42 | 96 |
Provider | NVIDIA | OpenAI |
Input Price Cost per million input tokens | $0.08 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $0.20 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.05 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 8K | 128K |
Throughput Speed Tokens generated per second | 140 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 32.5% | 82.4% |
GPQA Diamond Graduate-level reasoning | 48% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.02 / 1M | $1.00 / 1M |
Кто лидирует в каждой категории?
At-a-glance decision frameworkРезультаты проверенных бенчмарков
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.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
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.
Задержка и скорость ответа
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Интерактивный калькулятор стоимости токенов
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Nemotron Nano 9B v2 · Strengths & Key Advantages
- Контекстное окно 131K и генерация до 8K выходных токенов за ответ (SWE-bench Verified 32.5% · GPQA Diamond 48%)
- Высокая скорость генерации 140 токенов/сек при задержке до первого токена (TTFT) всего 280 мс
- Открытые веса модели (9B) для локального хостинга и дообучения через vLLM, SGLang или Ollama
Considerations & Trade-offs
- Для локального запуска в полной точности требуются GPU-серверы с достаточным объемом видеопамяти (VRAM)
- В сверхсложных научных доказательствах специализированные тяжелые модели рассуждения могут показывать большую глубину
GPT-6 Astra · Strengths & Key Advantages
- Контекстное окно 272K и генерация до 128K выходных токенов за ответ (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
- Высокая скорость генерации 100 токенов/сек при задержке до первого токена (TTFT) всего 950 мс
- Выгодная тарификация API (по цене $10/$50 за 1M токенов) с поддержкой кэширования промптов и строгих JSON-схем
Considerations & Trade-offs
- Проприетарная облачная модель без возможности скачивания весов для локального запуска в закрытом контуре
- При больших объемах трафика рекомендуется использовать кэширование промптов и Batch API для снижения затрат
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Nemotron Nano 9B v2 | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.06 | $2.15 |
Output Tokens / Task Tokens generated per task | 22K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 8K | 32K |
Технические характеристики
Architecture, release timeline, capabilities, and modalities.
| Feature | Nemotron Nano 9B v2 | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | nemotron-nano-9b-v2 | gpt-6-astra |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-08 | 2026-09 |
| Knowledge Cutoff | June 2025 | June 2026 |
| Architecture | Efficient Dense Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | 9B | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.08/1M in) across full 131K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.02/1M tokens | Automatic prefix caching at $1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 6 GB VRAM (4-bit Quantized) · 19 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Open-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 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision, audio |
| Output Modalities | text | text, audio |
Nemotron Nano 9B v2 vs GPT-6 Astra: Быстрые ответы (FAQ)
Which is more intelligent, Nemotron Nano 9B v2 or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 42 on the composite Intelligence Index.
Which model is faster?
Nemotron Nano 9B v2 is faster, generating 140 tokens per second compared with 100 tokens per second.
Which model is cheaper to run?
Nemotron Nano 9B v2 is cheaper at $0.05 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nemotron Nano 9B v2 has lower latency, with a time to first token of 0.28s compared with 0.95s.
Which model has a larger context window?
GPT-6 Astra has a larger context window, supporting 272K tokens compared with 131.1K tokens.
Вердикт
Choose Nemotron Nano 9B v2 for оптимально для максимальной экономической эффективности на токен и быстрого продакшен-инференса, корпоративных rag-пайплайнов и масштабируемых api-сервисов., or choose GPT-6 Astra for оптимально для естественного синтеза речи, обработки аудио в реальном времени и транскрибации, корпоративных rag-пайплайнов и масштабируемых api-сервисов..
Часто задаваемые вопросы (FAQ)
Which is cheaper: Nemotron Nano 9B v2 or GPT-6 Astra?+
Nemotron Nano 9B v2 costs $0.08/1M input and $0.2/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Nemotron Nano 9B v2 or GPT-6 Astra?+
Nemotron Nano 9B v2 supports 131K tokens whereas GPT-6 Astra supports 272K tokens.
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.
Официальные источники: NVIDIA & OpenAI Official Documentation