←新闻详情

MarkTechPost更新于 10月13日 05:56

Architect 推出 Liquid Inference,为 LLM 推理做实时竞价拍卖

Architect Launches Liquid Inference, a Real-Time Auction for LLM Inference - MarkTechPost

AI 导读

Architect Financial Technologies 推出 Liquid Inference,这是一个对每次 LLM 推理请求进行实时拍卖的路由器,提供方为指定模型报价,买方按最低且符合自身规则的报价成交。买方可在生成前锁定最高价格,并设置单任务成本上限、首 token 时延、最低吞吐、区域、零数据保留和提供方或模型白名单等规则,计费仅按实际用量。该服务兼容 OpenAI 与 Anthropic 客户端,官方称支持 Claude Code、Codex、OpenCode、Cursor、Pi 和 Cline,前 500 名用户可获 20 美元免费推理额度,推荐可获被推荐方费用的 20%。

推荐理由

AI 评分 60

交易公司把交易所式竞价机制搬到 LLM 推理路由上,读者可据此了解按请求实时竞价这一新计费形态。

主题

标签

正文

当前显示原文,中文全文译文尚未就绪。

Architect Financial Technologies has launched Liquid Inference, an LLM router that runs a live auction for every request. Liquid Inference is an LLM inference marketplace from Architect where providers bid to serve each prompt. The buyer pays the lowest offer that meets its rules. For developers, it is quite simple message: swap a base URL, keep your code, and let providers compete on price.

What is Liquid Inference?

Liquid Inference is an exchange-style router for LLM inference. According to Architect, providers post offers to serve specific models. Each request is auctioned across every provider quoting the named model. The lowest-priced offer that meets the buyer’s rules wins.

The product comes from a trading firm, not an AI lab. Architect runs the AX perpetual futures exchange. In May 2026 it acquired a US Designated Contract Market to list GPU compute futures, pending regulatory review. The team used its experience building financial exchanges to create two-sided price discovery for inference.

How does the inference auction work?

The flow has 4 steps:

Request: A client sends a standard OpenAI or Anthropic API call; Rules: The buyer’s constraints filter eligible offers; Auction: Providers quoting that model compete. The lowest qualifying offer wins; Receipt: The max price is locked before generation. Billing covers metered usage only

Buyers can set per-job cost caps, time to first token limits and minimum throughput. They can also require approved regions, zero data retention and provider or model allow lists. An Auto mode can pick the model for a given unit of work. Harrison’s LinkedIn post adds routing rule presets and full multi-modal support.

Account holders can view live order books, per-provider and per-model quotes, and cleared transactions. That level of market data is unusual for an LLM API.

What do buyers get?

Drop-in compatibility with agentic coding tools. The post lists Claude Code, Codex, OpenCode, Cursor, Pi and Cline; Free email signup. The first 500 users get $20 of free inference, per Harrison; A referral program: 20% of referred fees as free inference, plus 10% on second-level referrals

What do inference providers get?

Providers onboard through the Liquid Inference app. Harrison says new providers are verified “in minutes, not weeks.” All prompts use the OpenAI API standard. A REST and WebSocket API registers models and quotes.

Providers can update quotes based on their own costs. That lets them sell spare GPU capacity only when they want. Payouts run through Stripe, with itemized records of every job.

How does Liquid Inference compare with OpenRouter and Hugging Face?

Key Takeaways

Liquid Inference auctions every LLM request across competing providers; Max price is locked before the first token, with a per-job receipt; Works with OpenAI and Anthropic clients, including Claude Code and Cursor; First 500 users get $20 free; referrals earn 20% of fees; Fees, provider list and latency data are not yet public

Michal Sutter

Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.

Michal SutterNVIDIA PivotOPD Teaches Multi-Turn AI Agents to Recover From Pivotal Mistakes; Michal SutterAnthropic Releases Claude Haiku 5.5: A Small Model With 1M Context Priced at $0.10 per Million Input Tokens; Michal SutterReka Releases Rho-1: A 19B Omni-Reasoning Model That Understands, Generates Video and Outputs Robot Actions in One; Michal SutterCan an Open Model Do Security Research? Cantina’s apex-flash-1 Solves 40 of 60 Held-Out Bug Tasks

来源

MarkTechPost