{"id":"https://openalex.org/W7224454142","doi":"https://doi.org/10.20944/preprints202610.2733.v1","title":"Evaluating Quantized Language Model Inference a Critical Review of Quality Memory and Workload Tradeoffs","display_name":"Evaluating Quantized Language Model Inference a Critical Review of Quality Memory and Workload Tradeoffs","publication_year":2026,"publication_date":"2026-10-28","ids":{"openalex":"https://openalex.org/W7224454142","doi":"https://doi.org/10.20944/preprints202610.2733.v1"},"language":"en","primary_location":{"id":"doi:10.20944/preprints202610.2733.v1","doi":"https://doi.org/10.20944/preprints202610.2733.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202610.2733.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"volume":null,"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.20944/preprints202610.2733.v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5158826818","display_name":"Bankatesh Choudhary","orcid":"https://orcid.org/0009-0004-6516-3828","observed_orcids":["https://orcid.org/0009-0004-6516-3828"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bankatesh Choudhary","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0004-6516-3828","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5159767022","display_name":"Meenakshi Sharma","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meenakshi Sharma","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":0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9437999725341797,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9437999725341797,"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/T10363","display_name":"Low-power high-performance VLSI design","score":0.012400000356137753,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11697","display_name":"Numerical Methods and Algorithms","score":0.006500000134110451,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/large-language-models","display_name":"large language models","score":0.9810000061988831},{"id":"https://openalex.org/keywords/mixed-precision","display_name":"mixed precision","score":0.6290000081062317},{"id":"https://openalex.org/keywords/post-training-quantization","display_name":"post-training quantization","score":0.8550000190734863},{"id":"https://openalex.org/keywords/inference-latency","display_name":"inference latency","score":0.492000013589859},{"id":"https://openalex.org/keywords/memory-models","display_name":"memory models","score":0.48399999737739563},{"id":"https://openalex.org/keywords/inference-optimization","display_name":"inference optimization","score":0.3449999988079071},{"id":"https://openalex.org/keywords/quantization-error","display_name":"quantization error","score":0.4410000145435333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483999729156494},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5695000290870667},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.551800012588501},{"id":"https://openalex.org/C43364308","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Byte","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.49470001459121704},{"id":"https://openalex.org/C193702766","wikidata":"https://www.wikidata.org/wiki/Q1414548","display_name":"Concurrency","level":2,"score":0.48660001158714294},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.48559999465942383},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.48030000925064087},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.4715999960899353},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4424999952316284},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35989999771118164},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.3596999943256378},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2791999876499176},{"id":"https://openalex.org/C2779110517","wikidata":"https://www.wikidata.org/wiki/Q1240788","display_name":"Supervisor","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C115874739","wikidata":"https://www.wikidata.org/wiki/Q825377","display_name":"Critical path method","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.27079999446868896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2606000006198883},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.20944/preprints202610.2733.v1","doi":"https://doi.org/10.20944/preprints202610.2733.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202610.2733.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.20944/preprints202610.2733.v1","doi":"https://doi.org/10.20944/preprints202610.2733.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202610.2733.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7162868745","https://openalex.org/W6929265277","https://openalex.org/W7155005633","https://openalex.org/W4402683730","https://openalex.org/W7104034764","https://openalex.org/W7166868033","https://openalex.org/W7221031885","https://openalex.org/W4409362928","https://openalex.org/W7214472452","https://openalex.org/W7131136884"],"abstract_inverted_index":{"Quantization":[0],"reduces":[1],"the":[2,20,68,71,75,78,82],"numerical":[3,23],"precision":[4],"of":[5],"large":[6],"language":[7],"model":[8,91,174],"weights,":[9],"activations,":[10],"or":[11,177],"key-value":[12],"caches,":[13,98],"but":[14],"its":[15],"practical":[16],"value":[17],"depends":[18],"on":[19],"interaction":[21],"among":[22],"error,":[24],"workload,":[25],"and":[26,57,81,99,106,141,149,165,199],"execution":[27],"hardware.":[28],"This":[29],"review":[30,69],"compares":[31],"representative":[32],"methods":[33],"through":[34],"those":[35],"three":[36],"dimensions.":[37],"A":[38,102],"purposive":[39],"literature":[40],"synthesis":[41],"covers":[42],"integer":[43],"inference":[44,163],"foundations,":[45],"outlier-aware":[46],"mixed":[47],"precision,":[48,80],"second-order":[49],"weight":[50,117],"reconstruction,":[51],"activation-aware":[52],"scaling,":[53],"rotations,":[54],"cache":[55],"quantization,":[56],"training":[58,168],"with":[59,196],"low-bit":[60,167],"representations.":[61],"Rather":[62],"than":[63,203],"pool":[64],"incompatible":[65],"benchmark":[66],"results,":[67],"distinguishes":[70,159],"object":[72],"being":[73],"quantized,":[74],"required":[76],"preparation,":[77],"retained":[79],"implementation":[83],"needed":[84],"for":[85],"a":[86,112,122,132,154],"benefit.":[87],"An":[88],"analytical":[89],"memory":[90],"separates":[92,137],"compressed":[93],"weights":[94],"from":[95,139,162,169],"quantization":[96,187],"metadata,":[97],"runtime":[100],"workspace.":[101],"recomputable":[103],"worked":[104],"example":[105],"concurrency":[107],"sensitivity":[108],"analysis":[109],"show":[110],"why":[111],"fourfold":[113,123],"reduction":[114,124],"in":[115,125],"nominal":[116],"bytes":[118],"does":[119],"not":[120],"imply":[121],"total":[126],"serving":[127],"memory.":[128],"The":[129,182],"paper":[130],"proposes":[131],"reproducible":[133],"comparison":[134],"protocol":[135],"that":[136,186],"prefill":[138],"decoding":[140],"evaluates":[142],"quality,":[143],"latency":[144],"distributions,":[145],"throughput,":[146],"peak":[147],"memory,":[148],"amortized":[150],"preparation":[151],"cost":[152],"under":[153],"common":[155],"workload.":[156],"It":[157],"also":[158],"quantized":[160],"fine-tuning":[161],"optimization":[164],"native":[166],"post-training":[170],"conversion.":[171],"No":[172],"new":[173],"benchmark,":[175],"speedup,":[176],"accuracy":[178],"result":[179],"is":[180,185],"reported.":[181],"central":[183],"conclusion":[184],"should":[188],"be":[189],"selected":[190],"against":[191],"an":[192],"application-specific":[193],"operating":[194],"envelope,":[195],"quality":[197],"constraints":[198],"hardware":[200],"measurements,":[201],"rather":[202],"ranked":[204],"by":[205],"bit":[206],"width":[207],"alone.":[208]},"counts_by_year":[],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2026-10-30T00:00:00"}
