Nex AGI의 Nex-N2-Mini 모델은 심층 논리 추론, 고급 수학 문제 해결 및 다단계 과학적 분석에 최적화된 AI 모델로, 262K 컨텍스트 윈도우, 초당 155 토큰의 생성 속도, 종합 지능 지수 75/100점(1M 토큰당 입력 $0.08 / 출력 $0.32)을 제공합니다.
Technical Specifications
- Provider
- Nex AGI
- Category
- lightweight
- Release Date
- 2026-06
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- API Pay-as-you-go
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- nex-n2-mini
- Supported SDK & API Protocol
- Nex AGI REST API (OpenAI-Compatible)
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2028+)
- Production Rate Limits (RPM & TPM)
- 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($0.08/1M in) across full 262K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.008/1M tokens
- Computer Use & Browser GUI Agent
- 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
- Web Search Grounding & Code Sandbox
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- API Prompt Engineering & RAG Distillation
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed Nex AGI Cloud API
- System Card & Safety Framework
- Nex AGI Production Safety & Alignment Verified
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Nex-N2-Mini Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $12.56/mo vs $20 flat plan).
Break-even point: ~1,344 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Nex-N2-Mini:
Benchmark Scores & 6-Axis Capability Radar
- MMLU-Pro
- 72%
- HumanEval
- 82%
- Chatbot Arena Elo
- 1260pts
Strengths
- 262K 컨텍스트 윈도우 및 최대 8K 출력 토큰 생성 지원 (MMLU-Pro 72% · Arena Elo 1260)
- 초당 155 토큰의 빠른 처리 속도와 270ms에 불과한 첫 토큰 지연 시간(TTFT)
- 합리적인 API 요금 체계(1M 토큰당 입력 $0.08 / 출력 $0.32)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원
Limitations & Trade-offs
- 독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
- 초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다
Editorial Assessment
지능 지수 75/100점, 262K 컨텍스트, 초당 155 토큰의 속도를 갖춘 Nex-N2-Mini 모델은 Nex AGI 생태계에서 성능과 경제성을 모두 만족시키는 검증된 선택입니다.
Best for: 심층 논리 추론, 고급 수학 문제 해결 및 다단계 과학적 분석, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.
Compare Nex-N2-Mini
Frequently Asked Questions about Nex-N2-Mini
How much does the Nex-N2-Mini API cost per 1M tokens?+
Nex-N2-Mini by Nex AGI is priced at $0.08 per 1M input tokens and $0.32 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.008 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Nex-N2-Mini pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Nex-N2-Mini's context window?+
Nex-N2-Mini features a 262K tokens context window, which equals approximately 196,608 English words or ~524 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.
Can I run Nex-N2-Mini locally on my own GPU (Open Weights)?+
No, Nex-N2-Mini is a proprietary closed-weights model hosted by Nex AGI. It cannot be downloaded for local GPU execution and must be accessed via Nex AGI's official API or cloud platform.
Does Nex AGI train on data sent to the Nex-N2-Mini API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Nex AGI Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Nex AGI Cloud API & Enterprise Endpoints.
How does Nex-N2-Mini perform on coding and reasoning benchmarks?+
Nex-N2-Mini achieves a composite Intelligence Index of 75/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 72% on MMLU-Pro, and 1260 pts on Chatbot Arena Elo.
What is Nex-N2-Mini best used for?+
Nex-N2-Mini is best suited for: 심층 논리 추론, 고급 수학 문제 해결 및 다단계 과학적 분석, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.. Assessment: 지능 지수 75/100점, 262K 컨텍스트, 초당 155 토큰의 속도를 갖춘 Nex-N2-Mini 모델은 Nex AGI 생태계에서 성능과 경제성을 모두 만족시키는 검증된 선택입니다.
Nex AGI Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to Nex AGI's flagship reasoning tier:
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Nex-N2-Mini:
The basic unit of text that a language model processes, typically representing about 3 to 4 English characters or roughly 0.75 words. For example, the sentence "Artificial intelligence is fast" breaks down into about 5 tokens.
A standardized evaluation suite used to objectively measure and rank an AI model's capabilities across specific tasks — such as SWE-bench Verified for software engineering, AIME for competitive math, or MMLU for general knowledge.
The maximum number of tokens a model can consider at once — both the input it reads and the output it writes. A 1,000,000-token context window can hold roughly 750,000 English words in a single request.
An AI model trained via reinforcement learning to spend dynamic compute thinking through complex logic, math, and architectural problems before outputting a solution. Examples include OpenAI o1, o3, and DeepSeek R1.
A step-by-step reasoning technique where an AI model generates intermediate problem-solving thoughts before arriving at a final answer. Native reasoning models like OpenAI o3 and DeepSeek R1 use CoT to solve complex math and coding challenges.
The ability of a language model to recognize when an external capability is needed and output structured JSON arguments to invoke external APIs, databases, or terminal commands. The runtime executes the tool and passes results back to the model.
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: Nex AGI Pricing Docs↗