When Is the Same Model Not the Same Service? A Measurement Study of Hosted Open-Weight LLM APIs

Fuente: arXiv
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Main Authors: Li, Haorui, He, Zhenghui, Liu, Xuanzi, Xu, Yang, Liu, Dongsheng, Ma, Jiakang, Wu, Lupan, Wu, Yangjie, Tang, Xiongchao, Shi, Tianhui
Format: Preprint
Published: 2026
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_version_ 1866918486718021632
author Li, Haorui
He, Zhenghui
Liu, Xuanzi
Xu, Yang
Liu, Dongsheng
Ma, Jiakang
Wu, Lupan
Wu, Yangjie
Tang, Xiongchao
Shi, Tianhui
author_facet Li, Haorui
He, Zhenghui
Liu, Xuanzi
Xu, Yang
Liu, Dongsheng
Ma, Jiakang
Wu, Lupan
Wu, Yangjie
Tang, Xiongchao
Shi, Tianhui
contents Open-weight large language models (LLMs) are usually named as model artifacts, but production users often consume them as hosted API services. This paper argues that the operational unit is a service object: a provider-specific, time-varying endpoint defined by model variant, protocol behavior, context capacity, listed price, latency and throughput distribution, reliability, and task feasibility. Using sampled request logs, provider metadata, compatibility probes, pricing snapshots, and continuous latency measurements collected by AI Ping during Q4 2025, we study how this service layer changes the meaning of "the same model." Three empirical patterns emerge. First, observed demand is concentrated but persistent across versions: in the displayed family aggregate, the largest family carries 32.0% of relative demand and the top five carry 87.4%, with a Gini coefficient of 0.693, while older variants remain active after newer releases. Second, supply and use separate: provider listing breadth does not imply realized adoption, and listed prices are more anchored than latency, throughput, context length, protocol support, and error semantics. Third, task mix matters: applications induce different token-length regimes, so provider choice is a constrained decision over provider-model-task-time tuples rather than a lookup by model name. In two representative counterfactuals under observed feasibility constraints, routing lowers Qwen3-32B cost by 37.8% and raises DeepSeek-V3.2 average throughput by about 90% relative to direct official access. The results support a measurement view of hosted open-weight LLMs as heterogeneous services, not static catalog entries. We open-source the measurement methodology and reproduction artifacts at https://github.com/haoruilee/llm_api_measurement_study to support result reproduction.
format Preprint
id arxiv_https___arxiv_org_abs_2605_02821
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle When Is the Same Model Not the Same Service? A Measurement Study of Hosted Open-Weight LLM APIs
Li, Haorui
He, Zhenghui
Liu, Xuanzi
Xu, Yang
Liu, Dongsheng
Ma, Jiakang
Wu, Lupan
Wu, Yangjie
Tang, Xiongchao
Shi, Tianhui
Performance
C.4; I.2.7
Open-weight large language models (LLMs) are usually named as model artifacts, but production users often consume them as hosted API services. This paper argues that the operational unit is a service object: a provider-specific, time-varying endpoint defined by model variant, protocol behavior, context capacity, listed price, latency and throughput distribution, reliability, and task feasibility. Using sampled request logs, provider metadata, compatibility probes, pricing snapshots, and continuous latency measurements collected by AI Ping during Q4 2025, we study how this service layer changes the meaning of "the same model." Three empirical patterns emerge. First, observed demand is concentrated but persistent across versions: in the displayed family aggregate, the largest family carries 32.0% of relative demand and the top five carry 87.4%, with a Gini coefficient of 0.693, while older variants remain active after newer releases. Second, supply and use separate: provider listing breadth does not imply realized adoption, and listed prices are more anchored than latency, throughput, context length, protocol support, and error semantics. Third, task mix matters: applications induce different token-length regimes, so provider choice is a constrained decision over provider-model-task-time tuples rather than a lookup by model name. In two representative counterfactuals under observed feasibility constraints, routing lowers Qwen3-32B cost by 37.8% and raises DeepSeek-V3.2 average throughput by about 90% relative to direct official access. The results support a measurement view of hosted open-weight LLMs as heterogeneous services, not static catalog entries. We open-source the measurement methodology and reproduction artifacts at https://github.com/haoruilee/llm_api_measurement_study to support result reproduction.
title When Is the Same Model Not the Same Service? A Measurement Study of Hosted Open-Weight LLM APIs
topic Performance
C.4; I.2.7
url https://arxiv.org/abs/2605.02821