{"id":"https://openalex.org/W4417530727","doi":"https://doi.org/10.48550/arxiv.2512.16531","title":"Scaling Laws for Energy Efficiency of Local LLMs","display_name":"Scaling Laws for Energy Efficiency of Local LLMs","publication_year":2025,"publication_date":"2025-12-18","ids":{"openalex":"https://openalex.org/W4417530727","doi":"https://doi.org/10.48550/arxiv.2512.16531"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.16531","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16531","pdf_url":"https://arxiv.org/pdf/2512.16531","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.16531","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Alvarez, Ander","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alvarez, Ander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Genuardi, Alessandro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Genuardi, Alessandro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Sinha, Nilotpal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sinha, Nilotpal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Tiene, Antonio","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tiene, Antonio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Okyay, Mikail","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Okyay, Mikail","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ryskulov, Bakbergen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ryskulov, Bakbergen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Montero, David","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Montero, David","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Mugel, Samuel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mugel, Samuel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Or\u00fas, Rom\u00e1n","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Or\u00fas, Rom\u00e1n","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4668000042438507,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4668000042438507,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.15620000660419464,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.05820000171661377,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5162000060081482},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5123999714851379},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5070000290870667},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5031999945640564},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4700999855995178},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.44440001249313354},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4345000088214874},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.4284999966621399},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.3928000032901764}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7289999723434448},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5162000060081482},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5123999714851379},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5070000290870667},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5031999945640564},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4700999855995178},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.44440001249313354},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4345000088214874},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3986999988555908},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.3928000032901764},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3919999897480011},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3718000054359436},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3407999873161316},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C34778210","wikidata":"https://www.wikidata.org/wiki/Q376791","display_name":"Production\u2013possibility frontier","level":3,"score":0.3107999861240387},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3012000024318695},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C520301825","wikidata":"https://www.wikidata.org/wiki/Q380170","display_name":"Energy conservation","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C4822641","wikidata":"https://www.wikidata.org/wiki/Q846651","display_name":"Multiprocessing","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.2563999891281128}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.16531","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16531","pdf_url":"https://arxiv.org/pdf/2512.16531","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.16531","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.16531","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.16531","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16531","pdf_url":"https://arxiv.org/pdf/2512.16531","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deploying":[0],"local":[1,50,74,213],"large":[2,61],"language":[3,51,62,122,214],"models":[4,7,65,123,152],"and":[5,17,34,52,63,84,104,124,149,167,182,189,215,218,223],"vision-language":[6,53,64,129,151,216],"on":[8,37,66,99],"edge":[9,232],"devices":[10],"requires":[11],"balancing":[12],"accuracy":[13],"with":[14,108,117,125,146],"constrained":[15],"computational":[16,44,114,138],"energy":[18,190],"budgets.":[19],"Although":[20],"graphics":[21],"processors":[22],"dominate":[23],"modern":[24],"artificial-intelligence":[25],"deployment,":[26,83],"most":[27],"consumer":[28],"hardware--including":[29],"laptops,":[30],"desktops,":[31],"industrial":[32],"controllers,":[33],"embedded":[35,92],"systems--relies":[36],"central":[38],"processing":[39],"units.":[40],"Despite":[41],"this,":[42],"the":[43],"laws":[45],"governing":[46],"central-processing-unit-only":[47,210],"inference":[48,142],"for":[49,73,121,128,140,212,230],"workloads":[54],"remain":[55],"largely":[56],"unexplored.":[57],"We":[58,131],"systematically":[59],"benchmark":[60],"two":[67,133],"representative":[68],"central-processing-unit":[69],"tiers":[70],"widely":[71],"used":[72],"inference:":[75],"a":[76,85,95,154,205],"MacBook":[77],"Pro":[78],"M2,":[79],"reflecting":[80],"mainstream":[81],"laptop-class":[82],"Raspberry":[86],"Pi":[87],"5,":[88],"representing":[89],"constrained,":[90],"low-power":[91],"settings.":[93],"Using":[94],"unified":[96],"methodology":[97],"based":[98],"continuous":[100],"sampling":[101],"of":[102,208],"processor":[103,181],"memory":[105,183],"usage":[106,184],"together":[107],"area-under-curve":[109],"integration,":[110],"we":[111,175],"characterize":[112],"how":[113],"load":[115],"scales":[116,143],"input":[118],"text":[119],"length":[120],"image":[126],"resolution":[127,165],"models.":[130],"uncover":[132],"empirical":[134],"scaling":[135,211],"laws:":[136],"(1)":[137],"cost":[139],"language-model":[141],"approximately":[144],"linearly":[145],"token":[147],"length;":[148],"(2)":[150],"exhibit":[153],"preprocessing-driven":[155],"\"resolution":[156],"knee\",":[157],"where":[158],"compute":[159],"remains":[160],"constant":[161],"above":[162],"an":[163],"internal":[164],"clamp":[166],"decreases":[168],"sharply":[169],"below":[170],"it.":[171],"Beyond":[172],"these":[173],"laws,":[174],"show":[176],"that":[177],"quantum-inspired":[178],"compression":[179,222],"reduces":[180],"by":[185,192],"up":[186,193],"to":[187,194],"71.9%":[188],"consumption":[191],"62%,":[195],"while":[196],"preserving":[197],"or":[198],"improving":[199],"semantic":[200],"accuracy.":[201],"These":[202],"results":[203],"provide":[204],"systematic":[206],"quantification":[207],"multimodal":[209],"workloads,":[217],"they":[219],"identify":[220],"model":[221],"input-resolution":[224],"preprocessing":[225],"as":[226],"effective,":[227],"low-cost":[228],"levers":[229],"sustainable":[231],"inference.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-12-21T00:00:00"}
