[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fNx7SFQPqJYdbBmVDtm8ZWJElxbALtoJ4Yg9Npvzsq9o":3},{"tool":4,"categoryPool":49},{"id":5,"name":6,"slug":7,"description":8,"url":9,"githubUrl":10,"logoUrl":11,"openSource":12,"categories":13,"createdAt":18,"repo":19,"company":29,"articles":36,"related":48},"entity_01m0tg48sxe00bcr85j9pjvw09","Pipette","pipette","Compare foundation models on real devices across accuracy, throughput, latency, memory, quantization, runtime, and hardware.","https:\u002F\u002Fpipette.liquid.ai\u002F","https:\u002F\u002Fgithub.com\u002FLiquid4All\u002Fpipette-clients","https:\u002F\u002Fr2.minima.ltd\u002Forg_01jakhtww5fk6b0jmxj0qfp9rf\u002Ficon-d7c3eb30.png",true,[14],{"name":15,"slug":16,"count":17},"Evals","evals",0,1787595727,{"fullName":20,"url":10,"stars":21,"forks":17,"openIssues":22,"language":23,"license":24,"topics":25,"pushedAt":26,"archived":27,"licenseSpdx":24,"licenseOsi":12,"licenseVerifiedAt":28},"Liquid4All\u002Fpipette-clients",5,1,"Rust","Apache-2.0",[],"2026-08-20T16:56:27Z",false,"2026-08-24T18:22:12.704Z",{"id":30,"name":31,"slug":32,"url":33,"bio":34,"githubOrg":35},"entity_01kz6syj0vfk0v7j0pn2gds1v2","Liquid AI","liquid-ai","https:\u002F\u002Fwww.liquid.ai","Liquid AI is an efficiency-first foundation model company. We build highly capable, compute-optimized models that bring intelligence to any device and medium of choice.","Liquid4All",[37],{"id":38,"name":39,"slug":40,"summary":41,"url":42,"kind":43,"platform":44,"author":31,"publisher":31,"publishedAt":45,"about":46,"writtenBy":47},"entity_01m0tg5y3me03ss1qp21s69tzp","Introducing Pipette: A benchmarking suite for on-device intelligence","introducing-pipette-a-benchmarking-suite-for-on-device-intelligence","Meet Pipette, an open-source platform for reproducible on-device AI benchmarks across models, quantization, runtimes and hardware.","https:\u002F\u002Fwww.liquid.ai\u002Fblog\u002Fpipette-on-device-ai-benchmarking-by-liquid-ai","announcement","web","2026-08-24",[],[],[],[50,81,104,137],{"id":51,"name":52,"slug":53,"description":54,"url":55,"githubUrl":55,"logoUrl":56,"openSource":12,"categories":57,"createdAt":59,"repo":60,"company":73,"articles":79,"related":80},"entity_01kzhe2n9gfagsad1ydt1e7gkn","AACR-Bench","aacr-bench","An Alibaba open-source multi-language benchmark for evaluating LLMs in repository-level automatic code review, featuring an AI-assisted and expert-verified dataset.","https:\u002F\u002Fgithub.com\u002Falibaba\u002Faacr-bench","https:\u002F\u002Fr2.minima.ltd\u002Forg_01jakhtww5fk6b0jmxj0qfp9rf\u002Falibaba-0f6c077a.png",[58],{"name":15,"slug":16,"count":17},1786217846,{"fullName":61,"url":55,"stars":62,"forks":63,"openIssues":21,"language":64,"license":24,"topics":65,"pushedAt":71,"archived":27,"licenseSpdx":24,"licenseOsi":12,"licenseVerifiedAt":72},"alibaba\u002Faacr-bench",211,20,"Python",[66,67,68,69,70],"benchmark","code-review","multi-language","repository-level-context","software-engineering","2026-08-24T08:20:46Z","2026-08-09",{"id":74,"name":75,"slug":76,"url":77,"bio":78,"githubOrg":76},"entity_01kzmeveq2f22bbn6jcepyspwk","Alibaba","alibaba","https:\u002F\u002Fwww.alibabagroup.com","Alibaba Open Source",[],[],{"id":82,"name":83,"slug":84,"description":85,"url":86,"githubUrl":87,"logoUrl":88,"openSource":12,"categories":89,"createdAt":91,"repo":92,"articles":102,"related":103},"entity_01kzpjy8r7fvn8q0rcmcw8xg56","BenchLocal","benchlocal","Test LLMs on real tasks. Compare models side-by-side.","https:\u002F\u002Fbenchlocal.com\u002F","https:\u002F\u002Fgithub.com\u002Fstevibe\u002FBenchLocal","https:\u002F\u002Fr2.minima.ltd\u002Forg_01jakhtww5fk6b0jmxj0qfp9rf\u002Fstevibe-cd02357b.png",[90],{"name":15,"slug":16,"count":17},1786390717,{"fullName":93,"url":87,"stars":94,"forks":95,"openIssues":96,"language":97,"license":98,"topics":99,"pushedAt":100,"archived":27,"licenseSpdx":98,"licenseOsi":12,"licenseVerifiedAt":101},"stevibe\u002FBenchLocal",414,46,14,"TypeScript","MIT",[],"2026-08-10T15:10:36Z","2026-08-10",[],[],{"id":105,"name":106,"slug":107,"description":108,"url":109,"logoUrl":110,"openSource":27,"categories":111,"createdAt":116,"company":117,"articles":121,"related":136},"entity_01kyb2mdndeshatkngff89rdmc","Braintrust","braintrust","Ship quality agents at scale. Braintrust is the AI observability platform for tracing production, running evals, and catching regressions before they reach users.","https:\u002F\u002Fwww.braintrust.dev\u002F","https:\u002F\u002Fr2.minima.ltd\u002Forg_01jakhtww5fk6b0jmxj0qfp9rf\u002Ficon180-ef918139.png",[112,113],{"name":15,"slug":16,"count":17},{"name":114,"slug":115,"count":17},"Observability","observability",1784930776,{"id":118,"name":106,"slug":107,"url":119,"bio":108,"githubOrg":120},"entity_01kzmevhdaf22bbn7meq79a9a8","https:\u002F\u002Fbraintrust.dev\u002F","braintrustdata",[122],{"id":123,"name":124,"slug":125,"summary":126,"url":127,"kind":128,"platform":129,"author":130,"authorHandle":131,"publisher":132,"publishedAt":133,"about":134,"writtenBy":135},"entity_01kyb1ndrmf6esz3naek99dvk8","The context gold rush: Why everyone is building the same thing.","the-context-gold-rush-why-everyone-is-building-the-same-thing","You either die building product or live long enough to do context management.","https:\u002F\u002Fx.com\u002Fsamzliu\u002Fstatus\u002F2080210797465379147","blog","x","Sam Z Liu","samzliu","X","2026-07-23",[],[],[],{"id":138,"name":139,"slug":140,"description":141,"url":142,"logoUrl":143,"openSource":27,"categories":144,"createdAt":146,"company":147,"articles":154,"related":166},"entity_01kzyfk0nweh5b7faygzq2rgzz","DataBench","databench","DataBench scores frontier AI on the analytics work that matters — reasoning, reporting, and investigation on realistic, messy warehouse data.","https:\u002F\u002Fhex.tech\u002Fdatabench\u002F","https:\u002F\u002Fr2.minima.ltd\u002Forg_01jakhtww5fk6b0jmxj0qfp9rf\u002Ffavicon-32ee2db0.svg",[145],{"name":15,"slug":16,"count":17},1786655638,{"id":148,"name":149,"slug":150,"url":151,"bio":152,"githubOrg":153},"entity_01kzyfhc52eh5b7fac540s653f","Hex","hex","https:\u002F\u002Fhex.tech","Finally — anyone can get data insights grounded in the facts of their business. Hex has a flexible approach to context that earns trust without slowing you down.","hex-inc",[155],{"id":156,"name":157,"slug":158,"summary":159,"url":160,"kind":161,"platform":129,"author":149,"authorHandle":162,"publisher":132,"publishedAt":163,"about":164,"writtenBy":165},"entity_01kzye6311esg9ae93nr6enft3","Introducing DataBench","introducing-databench","DataBench v1: 100 realistic analytical tasks across Q&A and open-ended prompts, run in a synthetic Hex workspace — built because existing analytics benchmarks test \"overspecified pub trivia\" rather than the vague, directional questions people actually ask.","https:\u002F\u002Fx.com\u002F_hex_tech\u002Fstatus\u002F2087946398390206512","article","_hex_tech","2026-08-13",[],[],[]]