2026 全球主流 AI 大模型 LLM API 聚合服务商平台

Core Insights - The article evaluates the best LLM API aggregation service providers based on four dimensions: latency, pricing, model coverage, and compliance, aiming to guide users in selecting reliable partners for AI infrastructure in 2026 [1][2]. Evaluation Criteria - The evaluation focuses on key indicators of LLM API services, including stability, model richness, compliance, and cost-effectiveness [2][4]. - Stability (SLA) is crucial for determining whether LLM APIs can handle high concurrency without timeouts, impacting AI application deployment [4]. - Model richness assesses the coverage of major models like GPT-4o, Claude 3.5, and Gemini 1.5, as well as domestic models [4]. - Compliance and payment options are essential for domestic enterprises, particularly regarding public-to-public transactions and invoicing [4]. - Cost-effectiveness examines hidden costs such as exchange rate discrepancies and unexpected pricing [4]. Top-Tier Providers - n1n.ai: Emerged as a strong contender in 2025, designed for enterprise-level Model-as-a-Service (MaaS) with a unique 1:1 exchange rate, saving 85% on AI model costs [3][5]. - Azure OpenAI: Microsoft's enterprise-level AI service, recognized for its reliability [6]. - OpenRouter: A well-known overseas LLM API aggregator favored by AI enthusiasts [8]. - SiliconFlow: A domestic platform known for open-source AI model inference [9]. Second and Third Tiers - The second tier caters to developers seeking new and fast solutions, with rapid model deployment but unstable connections for domestic users [7][11]. - The third tier includes platforms like OneAPI, primarily community-operated and focused on proxy services for LLM APIs [10]. Performance Comparison - A performance test during peak hours showed: - n1n.ai: 320ms latency, 99.9% success rate, and a price of ¥7.5 per 1M tokens at a 1:1 exchange rate. - OpenRouter: 850ms latency, 92% success rate, and a price of ¥55 (requires currency exchange). - Azure: 280ms latency, 99.9% success rate, and a price of ¥72 (official API price) [11]. Pitfalls to Avoid - Pricing Trap: Some platforms advertise low prices but have unfavorable exchange rates, leading to high actual costs [12][13]. - Model "Shell" Trap: Smaller platforms may misrepresent models, selling GPT-3.5 as GPT-4, which can severely impact application performance [14]. - Compliance and Invoicing: Lack of invoicing options can hinder project progress for domestic enterprises, making it essential to choose compliant service providers [15]. Conclusion - The evaluation concludes that selecting the right LLM API aggregation provider is critical for successful AI application development, with n1n.ai being the top choice for enterprises due to its competitive pricing and infrastructure [16][18].