{"address":{"q":"GDPval","record":"gdpval-aio-20261029"},"analysis":{"analysis":"A capability benchmark is composed at its specification and stops before its results. The record's labour question, the experts whose work product the tasks are built from and the review time charged against the model, is where the paper meets user labour drag; the composition carries the first as design and leaves out the second.","d":"GDPVAL, BY NAME, ON GOOGLE'S AI OVERVIEW, SIGNED OUT, 2026-10-29: 'an AI benchmark created by OpenAI to measure how well artificial intelligence models perform on real-world, economically valuable knowledge-work tasks rather than academic or math tests.' Scope (1,320 tasks, 44 occupations, the top 9 U.S. GDP sectors), task design by professionals averaging 14 years' experience, blind head-to-head expert grading, the 220-task gold subset on Hugging Face and arXiv, and Artificial Analysis's GDPval-AA leaderboard. Seven cards: two OpenAI pages, arXiv, Hugging Face, Artificial Analysis, Inspect Evals, a video.","d_full":"GDPVAL, BY NAME, ON GOOGLE'S AI OVERVIEW, SIGNED OUT, 2026-10-29: 'an AI benchmark created by OpenAI to measure how well artificial intelligence models perform on real-world, economically valuable knowledge-work tasks rather than academic or math tests.' Scope (1,320 tasks, 44 occupations, the top 9 U.S. GDP sectors), task design by professionals averaging 14 years' experience, blind head-to-head expert grading, the 220-task gold subset on Hugging Face and arXiv, and Artificial Analysis's GDPval-AA leaderboard. Seven cards: two OpenAI pages, arXiv, Hugging Face, Artificial Analysis, Inspect Evals, a video.","findings":["THE BENCHMARK EXACT. Every figure the composition gives is the record's: 1,320 tasks, 44 occupations, 9 sectors, the 220-task gold subset, experts averaging 14 years. Checked 2026-10-29 against the Labor Vector census record of the same day and the sources it saved.","'BLIND'. The record's stated limits include that grading may not have been fully blind; the composition's 'blind head-to-head comparisons' gives the design without the caveat.","THE FINDINGS ABSENT. The paper's own: models 'beginning to approach parity' (47.6% of Claude Opus 4.1's deliverables graded as good as or better than the expert's); failures to follow instructions as the commonest reason experts preferred the human work; and, once review and redo time is counted, 'the payoff from using a model shrinks' (for GPT-5, 90 times as a naive speed figure, 1.12 if tried once).","THE LIMITS ABSENT. Self-contained computer work only; precisely specified, one-shot tasks; the automated grader agreeing less with experts on capable OpenAI models. The record's negative tags keep the benchmark apart from a measure of use or employment; the composition claims neither.","THE EXPERTS' TERMS. Who wrote and graded the tasks is given ('industry professionals'); how they were recruited and paid, which the paper gives only as 'well compensated', is not composed."],"match":"BROAD MATCH","mt":"GDPVAL ON THE OVERVIEW — OPENAI'S BENCHMARK, 1,320 TASKS, 44 OCCUPATIONS, 9 SECTORS, 220 OPEN, 14 YEARS' EXPERIENCE, EXACT; ITS FINDINGS (NEAR-PARITY, THE SHRINKING PAYOFF) AND ITS LIMITS (ONE-SHOT, SELF-CONTAINED) ABSENT","notes":{"prompts":"One query. Sent by the operator on 2026-10-29 with fourteen others, one per entity of the Labor Vector meta-aggregator, from the common names supplied for capture; twelve pasted in one message with '$' between them and three attached as files. Saved verbatim from the session transcript the moment it arrived (rebuild/capture-registry/intake-20261029-labor/)."},"originator":{"basis":"Not the archive's: GDPval; its operator, as the record gives it: OpenAI: the paper's 19 authors (Tejal Patwardhan first; nine marked equal contribution) give OpenAI as their affiliation, with correspondence to an openai.com address; OpenAI's own post at this address answered 403 and is unread. Formalized by the Labor Vector meta-aggregator record of 2026-10-29 (https://www.laborvector.org/aggregators/openai-gdpval/), editor Lee Sharks; the record's fields carry verbatim quotes from the entity's own pages, saved with sha256.","entity_type":"dataset","name":"OpenAI: the paper's 19 authors (Tejal Patwardhan first; nine marked equal contribution) give OpenAI as their affiliation, with correspondence to an openai.com address; OpenAI's own post at this address answered 403 and is unread","relation":"external","spxi_treatment":"partial"},"reading":"The innocent reading first. The Overview gives the benchmark's maker, scope, construction and grading, and where to find its data, from OpenAI's pages and the paper."},"measures":{"archive_controlled_cites":0,"cite_list":[{"n":1,"note":null,"rel":"third_party","site":"OpenAI","snip":"GDPval: Evaluation measuring model performance on 1,320 specialized tasks across 44 knowledge work occupations from 9 U.S. GDP-contributing industries (threshol...","title":"Measuring the performance of our models on real-world tasks | OpenAI","url":null},{"n":2,"note":null,"rel":"third_party","site":"Artificial Analysis","snip":"GDPval-AA v2.1 Benchmark LegacyAgenticKnowledge WorkWritingReasoningInstruction FollowingTool UseMultimodalBusinessFinanceLegalMedicalHumanities GDPval-AA v2. 1...","title":"GDPval-AA v2.1 Benchmark - Artificial Analysis","url":null},{"n":3,"note":null,"rel":"third_party","site":"arXiv","snip":"[2510.04374] GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks Scheduled maintenance: Today - Please check here for updates:Stat...","title":"[2510.04374] GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks","url":null},{"n":4,"note":null,"rel":"third_party","site":"OpenAI","snip":"Our paper introduces the first version of GDPval, a benchmark evaluating AI model performance on real-world economically valuable tasks. GDPval covers the top 9...","title":"gdpval: evaluating ai model performance - OpenAI","url":null},{"n":5,"note":null,"rel":"third_party","site":"Hugging Face","snip":"Dataset: openai/gdpval on Hugging Face (Parquet format, <1K size, 220 rows, 2.29 GB total file size). Modalities: Text. Libraries: Datasets, pandas, Polars, xet...","title":"openai/gdpval · Datasets at Hugging Face","url":null},{"n":6,"note":"video, 11:23","rel":"third_party","site":"YouTube·Vivek Haldar","snip":null,"title":"GDPval: An AI benchmark for real-world tasks","url":null},{"n":7,"note":null,"rel":"third_party","site":"GitHub Pages documentation","snip":"GDPval measures model performance on economically valuable, real-world tasks across 44 occupations. The first version of this evaluation spans 44 occupations se...","title":"GDPval – Inspect Evals - GitHub Pages","url":null}],"cites":7,"per":0.25,"per_dim":{"after_challenge":null,"atoms":[{"atom":"name","dim":"M","evidence":"GDPval is an AI benchmark created by","kind":"token","present":true,"weight":3},{"atom":"author","dim":"M","evidence":"GDPval is an AI benchmark created by [OpenAI]","kind":"role","present":true,"weight":3},{"atom":"date","dim":"M","evidence":null,"kind":"token","present":false,"weight":1},{"atom":"claim boundary","dim":"M","evidence":"to measure how well artificial intelligence models perform on real-world, economically valuable knowledge-work tasks rather than academic or math tests.","kind":"reading","present":true,"weight":2},{"atom":"purpose","dim":"D","evidence":"to measure how well artificial intelligence models perform on real-world, economically valuable knowledge-work tasks","kind":"reading","present":true,"weight":3},{"atom":"commitments","dim":"D","evidence":"Open Source Set: Includes a gold open-sourced subset of 220 tasks","kind":"reading","present":true,"weight":2},{"atom":"lineage","dim":"D","evidence":"rather than academic or math tests.","kind":"role","present":true,"weight":2},{"atom":"identifier","dim":"D","evidence":null,"kind":"role","present":false,"weight":1},{"atom":"deposit chain","dim":"D","evidence":"Includes a gold open-sourced subset of 220 tasks available via","kind":"role","present":true,"weight":1}],"basis":"reached: GDPval is an AI benchmark created by; The benchmark itself is composed: name, maker (OpenAI), object (model performance on economically valuable knowledge-work tasks), scope (1,320 tasks, 44 occupations, top 9 sectors), grading (blinded expert comparison) and the open gold subset.","entity_type":"dataset","gate":"scored","inversions":[],"qualifier":null,"reached":"same","read":{"brief":"rebuild/capture-registry/intake-20261029-labor/per/BRIEF.md","by":"intake reader L3, spans and record quotes checked verbatim by scripts/per_backlog.py","external":true,"notes":"Claim boundary present: a benchmark of model performance on knowledge-work tasks, 1,320 tasks / 44 occupations / top 9 U.S. GDP sectors, graded by 'blind head-to-head comparisons by human experts'; no job-replacement or workplace-performance claim is added. Not carried: one-shot, precisely specified tasks; 'a limited, initial cut'; physical and tacit work out of scope; the paper's own caveat that grading could not be fully blind. Purpose present as measuring capability on economically valuable tasks; the record's frame (an alternative to lagging adoption indicators, assessing relevance ahead of adoption) is not carried. Lineage present: the record positions GDPval 'Unlike AI benchmarks in the style of an academic test' (paper-html L199), and the composition binds the answering relation ('rather than academic or math tests') to the benchmark; the 'academic test' token is named by word. O*NET, BLS and the production usage analyses it builds on are absent. Commitments present on the open-sourced gold subset as GDPval's own provision; the expert-identity scrubbing, the recommendation of human grading over the automated grader, and the CC BY 4.0 licence are not carried. Deposit chain present: the gold subset (a projection the record names) is offered as the way to the work ('available via [Hugging Face Datasets] and detailed in the [ArXiv Research Paper]'); identifier absent because only link text and URLs carry the locations (arXiv:2510.04374 appears in card titles only). No date. 'Artificial Analysis GDPval-AA v2.1' is a third-party leaderboard not in the records; it is set beside GDPval as an evaluator, not merged with it.","on":"2026-10-29"},"scores":{"C":null,"D":0.111,"M":0.111,"PER":0.111},"spec":"PER-dim rubric v1.1","src":true,"standing_substitutions":[],"target":{"ent":"TGT-lv-openai-gdpval","name":"GDPval"},"tombstone_pointer":false},"per_note":"OpenAI named; no person; the arXiv identifier in a card; OpenAI's pages, the paper and the dataset cited.","per_v":{"author":false,"id":true,"inst":true,"src":true}},"observation":{"auth":"signed out, incognito","date":"2026-10-29","ev":"paste","q":"GDPval","q_kind":"the common name of an entity of the Labor Vector meta-aggregator (GDPval; record https://www.laborvector.org/aggregators/openai-gdpval/, compiled 2026-10-29), supplied for capture and run by the operator the same day, to supply the composition layer's account of the entity for its record and its /non row. A baseline: the record landed on laborvector.org the same day (commit bf90841) and no card cites it. NEW address.","s":"Machine Reception","surface":"Google AI Overview","transcript":"[Google AI Overview at the query, signed out and incognito (operator defaults of 2026-10-01 and 2026-10-14), 2026-10-29. The paste is the Overview expanded (the 'AI Mode Conversation' view, with the source cards that follow the answer); the 'You said' line carries the query twice, run together, and is given once here. Inline links are Google redirect URLs, kept as pasted.]\n\n[QUERENT] GDPval\n\n[SYSTEM] GDPval is an AI benchmark created by [OpenAI](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg) to measure how well artificial intelligence models perform on real-world, economically valuable knowledge-work tasks rather than academic or math tests. [[1](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg), [2](https://www.google.com/goto?url=CAESWAHrOzAV5e1D92fjl4arLGgbWubPM_woQLTk88wKqtsjeycDpo4ugmHlLKBY2Jmgp8L30J-U1cjOBDae-FiGJbaIH7bL25Gw_j2LadpPeqBjk_YuRdt18qQ), [3](https://www.google.com/goto?url=CAESYwHrOzAV9ofAr51RKj_rQOL_JfwndrUjbdpvWVx4myclZBWUACpQsLQQr7iFpEKr_duZsBLrpkrlAoqbGGtym3eGY9RndTjy_G59i1bkd9_MPHYhOve8DUZHKa5q2sD_cYLYHw)]\nKey Details\n\n* Scope: Covers 1,320 specialized tasks across 44 occupations derived from the top 9 U.S. GDP-contributing sectors. [[1](https://www.google.com/goto?url=CAESggEB6zswFe2tOqXCoWJa8bALG0Q6O5sjAYGmf7a-oLxpTbJ5qcxu6is-NOEdLzyAP_TIRy2vrAjnFfnuluIIeOfIEfPV872RvaFirwwF_vUZXYXjICql23SYvHpMv7sZFHmkLHVIVYJzczNBsFmwduVAWTTPIgCcWPq2-FHAEQuna1nC), [2](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg)]\n* Task Design: Built by industry professionals with an average of 14 years of experience using actual work products like legal briefs, spreadsheets, and engineering blueprints. [[1](https://www.google.com/goto?url=CAESgQEB6zswFdiU5v-2bvjveGnb5VRaIqHJGLAx1zx-bqb3KsbzMazsgASe6Zy4djwyaLew68L1JAn-FDVpHmeQc3N_-X86VuIb26GT8zxguER68zFWXuHizxS4XvKq1frf8xehgvnN49PX29xVueyA3NAeYTJX9ilMrDsgnSZTq7lfGlU), [2](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg)]\n* Evaluation: Uses blind head-to-head comparisons by human experts to grade model outputs against human work. [[1](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg), [2](https://www.google.com/goto?url=CAESggEB6zswFe2tOqXCoWJa8bALG0Q6O5sjAYGmf7a-oLxpTbJ5qcxu6is-NOEdLzyAP_TIRy2vrAjnFfnuluIIeOfIEfPV872RvaFirwwF_vUZXYXjICql23SYvHpMv7sZFHmkLHVIVYJzczNBsFmwduVAWTTPIgCcWPq2-FHAEQuna1nC)]\n* Open Source Set: Includes a gold open-sourced subset of 220 tasks available via [Hugging Face Datasets](https://www.google.com/goto?url=CAESZQHrOzAVm5FY12OrrM0U6PSxauyQdUwzN8-8rk1Z-9EU8DSkpEJyiaghIjM8OUDTTTwYY9F3FOr1suUN7D-RQdFC44Y8DZqzlNkNd4_3MEsmBpgPdNQl0PKHVzYpyxlHs1qyhSgQ) and detailed in the [ArXiv Research Paper](https://www.google.com/goto?url=CAESWAHrOzAV5e1D92fjl4arLGgbWubPM_woQLTk88wKqtsjeycDpo4ugmHlLKBY2Jmgp8L30J-U1cjOBDae-FiGJbaIH7bL25Gw_j2LadpPeqBjk_YuRdt18qQ). [[1](https://www.google.com/goto?url=CAESZQHrOzAVm5FY12OrrM0U6PSxauyQdUwzN8-8rk1Z-9EU8DSkpEJyiaghIjM8OUDTTTwYY9F3FOr1suUN7D-RQdFC44Y8DZqzlNkNd4_3MEsmBpgPdNQl0PKHVzYpyxlHs1qyhSgQ), [2](https://www.google.com/goto?url=CAESWAHrOzAV5e1D92fjl4arLGgbWubPM_woQLTk88wKqtsjeycDpo4ugmHlLKBY2Jmgp8L30J-U1cjOBDae-FiGJbaIH7bL25Gw_j2LadpPeqBjk_YuRdt18qQ)]\n* Leaderboards: Evaluated by frameworks like [Artificial Analysis GDPval-AA v2.1](https://www.google.com/goto?url=CAESawHrOzAVgAjm8sR1LVSiS9i7GzX2qM_VLeqRumJBavESmc8WxlV73ea4yA7gFz_me9eppW0Og-Ml_WxAMVWD3bWEpsY0O2plbNqtIGV7xMNVdQ7190-HFX_X5hjx_vrKAGEnxHNh9xe-HRA4). [[1](https://www.google.com/goto?url=CAESawHrOzAVgAjm8sR1LVSiS9i7GzX2qM_VLeqRumJBavESmc8WxlV73ea4yA7gFz_me9eppW0Og-Ml_WxAMVWD3bWEpsY0O2plbNqtIGV7xMNVdQ7190-HFX_X5hjx_vrKAGEnxHNh9xe-HRA4)]\n\nWould you like to know more about top-performing models on GDPval, or how to access the open-source dataset?\nOpenAI\nMeasuring the performance of our models on real-world tasks | OpenAI\nGDPval: Evaluation measuring model performance on 1,320 specialized tasks across 44 knowledge work occupations from 9 U.S. GDP-contributing industries (threshol...\nArtificial Analysis\nGDPval-AA v2.1 Benchmark - Artificial Analysis\nGDPval-AA v2.1 Benchmark LegacyAgenticKnowledge WorkWritingReasoningInstruction FollowingTool UseMultimodalBusinessFinanceLegalMedicalHumanities GDPval-AA v2. 1...\narXiv\n[2510.04374] GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks\n[2510.04374] GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks Scheduled maintenance: Today - Please check here for updates:Stat...\nOpenAI\ngdpval: evaluating ai model performance - OpenAI\nOur paper introduces the first version of GDPval, a benchmark evaluating AI model performance on real-world economically valuable tasks. GDPval covers the top 9...\nHugging Face\nopenai/gdpval · Datasets at Hugging Face\nDataset: openai/gdpval on Hugging Face (Parquet format, <1K size, 220 rows, 2.29 GB total file size). Modalities: Text. Libraries: Datasets, pandas, Polars, xet...\nYouTube·Vivek Haldar\n11:23\nGDPval: An AI benchmark for real-world tasks\nGitHub Pages documentation\nGDPval – Inspect Evals - GitHub Pages\nGDPval measures model performance on economically valuable, real-world tasks across 44 occupations. The first version of this evaluation spans 44 occupations se...","transcript_class":"CAPTURE-TIME VERBATIM RECORD — paste of the Overview expanded, with its source cards","transcript_complete":"complete as supplied","transcript_raw":"GDPval is an AI benchmark created by [OpenAI](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg) to measure how well artificial intelligence models perform on real-world, economically valuable knowledge-work tasks rather than academic or math tests. [[1](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg), [2](https://www.google.com/goto?url=CAESWAHrOzAV5e1D92fjl4arLGgbWubPM_woQLTk88wKqtsjeycDpo4ugmHlLKBY2Jmgp8L30J-U1cjOBDae-FiGJbaIH7bL25Gw_j2LadpPeqBjk_YuRdt18qQ), [3](https://www.google.com/goto?url=CAESYwHrOzAV9ofAr51RKj_rQOL_JfwndrUjbdpvWVx4myclZBWUACpQsLQQr7iFpEKr_duZsBLrpkrlAoqbGGtym3eGY9RndTjy_G59i1bkd9_MPHYhOve8DUZHKa5q2sD_cYLYHw)]\nKey Details\n\n* Scope: Covers 1,320 specialized tasks across 44 occupations derived from the top 9 U.S. GDP-contributing sectors. [[1](https://www.google.com/goto?url=CAESggEB6zswFe2tOqXCoWJa8bALG0Q6O5sjAYGmf7a-oLxpTbJ5qcxu6is-NOEdLzyAP_TIRy2vrAjnFfnuluIIeOfIEfPV872RvaFirwwF_vUZXYXjICql23SYvHpMv7sZFHmkLHVIVYJzczNBsFmwduVAWTTPIgCcWPq2-FHAEQuna1nC), [2](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg)]\n* Task Design: Built by industry professionals with an average of 14 years of experience using actual work products like legal briefs, spreadsheets, and engineering blueprints. [[1](https://www.google.com/goto?url=CAESgQEB6zswFdiU5v-2bvjveGnb5VRaIqHJGLAx1zx-bqb3KsbzMazsgASe6Zy4djwyaLew68L1JAn-FDVpHmeQc3N_-X86VuIb26GT8zxguER68zFWXuHizxS4XvKq1frf8xehgvnN49PX29xVueyA3NAeYTJX9ilMrDsgnSZTq7lfGlU), [2](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg)]\n* Evaluation: Uses blind head-to-head comparisons by human experts to grade model outputs against human work. [[1](https://www.google.com/goto?url=CAESWAHrOzAVhPUzkeZH77Ag5jLMmksSXvMZIZn3Sp_gF5kA_w6WuRy05O9W5aaR91vp2mcMDj0LP6Z6Dh3R6CNeLyRGrDRztzxt5b0SrhXSwBWUrWI8BUM3oPg), [2](https://www.google.com/goto?url=CAESggEB6zswFe2tOqXCoWJa8bALG0Q6O5sjAYGmf7a-oLxpTbJ5qcxu6is-NOEdLzyAP_TIRy2vrAjnFfnuluIIeOfIEfPV872RvaFirwwF_vUZXYXjICql23SYvHpMv7sZFHmkLHVIVYJzczNBsFmwduVAWTTPIgCcWPq2-FHAEQuna1nC)]\n* Open Source Set: Includes a gold open-sourced subset of 220 tasks available via [Hugging Face Datasets](https://www.google.com/goto?url=CAESZQHrOzAVm5FY12OrrM0U6PSxauyQdUwzN8-8rk1Z-9EU8DSkpEJyiaghIjM8OUDTTTwYY9F3FOr1suUN7D-RQdFC44Y8DZqzlNkNd4_3MEsmBpgPdNQl0PKHVzYpyxlHs1qyhSgQ) and detailed in the [ArXiv Research Paper](https://www.google.com/goto?url=CAESWAHrOzAV5e1D92fjl4arLGgbWubPM_woQLTk88wKqtsjeycDpo4ugmHlLKBY2Jmgp8L30J-U1cjOBDae-FiGJbaIH7bL25Gw_j2LadpPeqBjk_YuRdt18qQ). [[1](https://www.google.com/goto?url=CAESZQHrOzAVm5FY12OrrM0U6PSxauyQdUwzN8-8rk1Z-9EU8DSkpEJyiaghIjM8OUDTTTwYY9F3FOr1suUN7D-RQdFC44Y8DZqzlNkNd4_3MEsmBpgPdNQl0PKHVzYpyxlHs1qyhSgQ), [2](https://www.google.com/goto?url=CAESWAHrOzAV5e1D92fjl4arLGgbWubPM_woQLTk88wKqtsjeycDpo4ugmHlLKBY2Jmgp8L30J-U1cjOBDae-FiGJbaIH7bL25Gw_j2LadpPeqBjk_YuRdt18qQ)]\n* Leaderboards: Evaluated by frameworks like [Artificial Analysis GDPval-AA v2.1](https://www.google.com/goto?url=CAESawHrOzAVgAjm8sR1LVSiS9i7GzX2qM_VLeqRumJBavESmc8WxlV73ea4yA7gFz_me9eppW0Og-Ml_WxAMVWD3bWEpsY0O2plbNqtIGV7xMNVdQ7190-HFX_X5hjx_vrKAGEnxHNh9xe-HRA4). [[1](https://www.google.com/goto?url=CAESawHrOzAVgAjm8sR1LVSiS9i7GzX2qM_VLeqRumJBavESmc8WxlV73ea4yA7gFz_me9eppW0Og-Ml_WxAMVWD3bWEpsY0O2plbNqtIGV7xMNVdQ7190-HFX_X5hjx_vrKAGEnxHNh9xe-HRA4)]\n\nWould you like to know more about top-performing models on GDPval, or how to access the open-source dataset?\nOpenAI\nMeasuring the performance of our models on real-world tasks | OpenAI\nGDPval: Evaluation measuring model performance on 1,320 specialized tasks across 44 knowledge work occupations from 9 U.S. GDP-contributing industries (threshol...\nArtificial Analysis\nGDPval-AA v2.1 Benchmark - Artificial Analysis\nGDPval-AA v2.1 Benchmark LegacyAgenticKnowledge WorkWritingReasoningInstruction FollowingTool UseMultimodalBusinessFinanceLegalMedicalHumanities GDPval-AA v2. 1...\narXiv\n[2510.04374] GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks\n[2510.04374] GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks Scheduled maintenance: Today - Please check here for updates:Stat...\nOpenAI\ngdpval: evaluating ai model performance - OpenAI\nOur paper introduces the first version of GDPval, a benchmark evaluating AI model performance on real-world economically valuable tasks. GDPval covers the top 9...\nHugging Face\nopenai/gdpval · Datasets at Hugging Face\nDataset: openai/gdpval on Hugging Face (Parquet format, <1K size, 220 rows, 2.29 GB total file size). Modalities: Text. Libraries: Datasets, pandas, Polars, xet...\nYouTube·Vivek Haldar\n11:23\nGDPval: An AI benchmark for real-world tasks\nGitHub Pages documentation\nGDPval – Inspect Evals - GitHub Pages\nGDPval measures model performance on economically valuable, real-world tasks across 44 occupations. The first version of this evaluation spans 44 occupations se...","transcript_read":"READ IN FULL 2026-10-29","turns":1},"slug":"gdpval-aio-20261029"}