# Datasets, Page 93 of 132 Source: https://savrn.com/datasets/page/93 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- SAVRN Model Hub # AI Training Datasets Each dataset with its card, its structure (every split, row count and column type), its files, its license, and the models that disclose training on it. 11,122Models 3,164Datasets 285Papers 6,792Publishers 11,852Sourced relationships Updated 2026-10-18 · [How the library is built](https://savrn.com/model-hub/methodology) ## Filter Datasets Task - [Text generation127](https://savrn.com/datasets?task=Text+generation) - [Robotics106](https://savrn.com/datasets?task=Robotics) - [Other48](https://savrn.com/datasets?task=Other) - [Text classification47](https://savrn.com/datasets?task=Text+classification) - [Text retrieval44](https://savrn.com/datasets?task=Text+retrieval) - [Question answering36](https://savrn.com/datasets?task=Question+answering) - [Speech recognition33](https://savrn.com/datasets?task=Speech+recognition) - [Tabular classification21](https://savrn.com/datasets?task=Tabular+classification) - [Time series forecasting21](https://savrn.com/datasets?task=Time+series+forecasting) - [Image to text17](https://savrn.com/datasets?task=Image+to+text) - [Image classification16](https://savrn.com/datasets?task=Image+classification) - [Object detection14](https://savrn.com/datasets?task=Object+detection) - [Text to speech14](https://savrn.com/datasets?task=Text+to+speech) - [Visual question answering14](https://savrn.com/datasets?task=Visual+question+answering) - [Image to image11](https://savrn.com/datasets?task=Image+to+image) - [Image segmentation9](https://savrn.com/datasets?task=Image+segmentation) - [Image to 3d9](https://savrn.com/datasets?task=Image+to+3d) - [Translation9](https://savrn.com/datasets?task=Translation) - [Video classification9](https://savrn.com/datasets?task=Video+classification) - [Audio classification7](https://savrn.com/datasets?task=Audio+classification) - [Feature extraction7](https://savrn.com/datasets?task=Feature+extraction) - [Reinforcement learning7](https://savrn.com/datasets?task=Reinforcement+learning) - [Text to image7](https://savrn.com/datasets?task=Text+to+image) - [Text to video7](https://savrn.com/datasets?task=Text+to+video) License - [other250](https://savrn.com/datasets?license=other) - [apache-2.0236](https://savrn.com/datasets?license=apache-2.0) - [mit232](https://savrn.com/datasets?license=mit) - [cc-by-4.0224](https://savrn.com/datasets?license=cc-by-4.0) - [cc-by-nc-4.077](https://savrn.com/datasets?license=cc-by-nc-4.0) - [cc0-1.030](https://savrn.com/datasets?license=cc0-1.0) - [cc-by-sa-4.029](https://savrn.com/datasets?license=cc-by-sa-4.0) - [odc-by24](https://savrn.com/datasets?license=odc-by) - [cc-by-nc-sa-4.020](https://savrn.com/datasets?license=cc-by-nc-sa-4.0) - [unknown14](https://savrn.com/datasets?license=unknown) - [cc-by-sa-3.06](https://savrn.com/datasets?license=cc-by-sa-3.0) - [odbl6](https://savrn.com/datasets?license=odbl) - [gpl-3.05](https://savrn.com/datasets?license=gpl-3.0) - [cc-by-3.04](https://savrn.com/datasets?license=cc-by-3.0) - [cc3](https://savrn.com/datasets?license=cc) - [cc-by-nc-nd-4.03](https://savrn.com/datasets?license=cc-by-nc-nd-4.0) - [gpl3](https://savrn.com/datasets?license=gpl) - [cc-by-2.02](https://savrn.com/datasets?license=cc-by-2.0) - [cc-by-nd-4.02](https://savrn.com/datasets?license=cc-by-nd-4.0) - [cdla-sharing-1.02](https://savrn.com/datasets?license=cdla-sharing-1.0) - [agpl-3.01](https://savrn.com/datasets?license=agpl-3.0) - [bsl-1.01](https://savrn.com/datasets?license=bsl-1.0) - [c-uda1](https://savrn.com/datasets?license=c-uda) - [cc-by-nc-3.01](https://savrn.com/datasets?license=cc-by-nc-3.0) Access - [Publicly accessible2,933](https://savrn.com/datasets?access=open_access) - [Access requested at publisher231](https://savrn.com/datasets?access=gated) Publisher - [Benjamin J Barber35](https://savrn.com/datasets?publisher=endomorphosis) - [Chang Yu24](https://savrn.com/datasets?publisher=g1n0st) - [Ji Xie23](https://savrn.com/datasets?publisher=sanaka87) - [Justicedao18](https://savrn.com/datasets?publisher=justicedao) - [LeDuy13](https://savrn.com/datasets?publisher=duyle2408) - [Nguyen13](https://savrn.com/datasets?publisher=icdn11) - [Nguyen13](https://savrn.com/datasets?publisher=icdn12) - [Nguyen13](https://savrn.com/datasets?publisher=icdn13) - [National Engineering Research Center for Big Data Software13](https://savrn.com/datasets?publisher=thulab) - [Nguyen12](https://savrn.com/datasets?publisher=icdn10) - [Nguyen12](https://savrn.com/datasets?publisher=icdn14) - [Byte I12](https://savrn.com/datasets?publisher=icdn15) - [Rebrowser.net12](https://savrn.com/datasets?publisher=rebrowser) - [Shufan Jiang12](https://savrn.com/datasets?publisher=tsumugii) - [Ai210](https://savrn.com/datasets?publisher=allenai) - [Ps Yo10](https://savrn.com/datasets?publisher=atokforps) - [Dougall DeepMind10](https://savrn.com/datasets?publisher=dougalldeepmind) - [Deesced9](https://savrn.com/datasets?publisher=ameluce) - [Jiahao Zhang9](https://savrn.com/datasets?publisher=hi-todayis-jh) - [Julia Dollis9](https://savrn.com/datasets?publisher=juliadollis) - [Massive Text Embedding Benchmark9](https://savrn.com/datasets?publisher=mteb) - [Pranab Pattanaik9](https://savrn.com/datasets?publisher=p2samapa) - [Sota9](https://savrn.com/datasets?publisher=sotaagi2030) - [Sunsetcanyon9](https://savrn.com/datasets?publisher=sunsetcanyon) Size - [10K1T16](https://savrn.com/datasets?size=n%3E1T) - [1B1M1](https://savrn.com/datasets?size=n%3E1M) Domain - [LeRobot31](https://savrn.com/datasets?domain=LeRobot) - [legal, law, graphrag12](https://savrn.com/datasets?domain=legal%2C+law%2C+graphrag) - [tsfile, timeseries, time-series12](https://savrn.com/datasets?domain=tsfile%2C+timeseries%2C+time-series) - [open-data, data-science, web-scraping9](https://savrn.com/datasets?domain=open-data%2C+data-science%2C+web-scraping) - [seo-cluster, web-nodes9](https://savrn.com/datasets?domain=seo-cluster%2C+web-nodes) - [dpo, rlhf, ultrafeedback8](https://savrn.com/datasets?domain=dpo%2C+rlhf%2C+ultrafeedback) - [mteb, text, image7](https://savrn.com/datasets?domain=mteb%2C+text%2C+image) - [nepali, instruction-tuning, agriculture7](https://savrn.com/datasets?domain=nepali%2C+instruction-tuning%2C+agriculture) - [science, stackexchange, provenance5](https://savrn.com/datasets?domain=science%2C+stackexchange%2C+provenance) - [LeRobot, robotics, lerobot4](https://savrn.com/datasets?domain=LeRobot%2C+robotics%2C+lerobot) - [ml-intern4](https://savrn.com/datasets?domain=ml-intern) - [AMASS, Retarget, Robotics3](https://savrn.com/datasets?domain=AMASS%2C+Retarget%2C+Robotics) - [benchmark, agents, terminal3](https://savrn.com/datasets?domain=benchmark%2C+agents%2C+terminal) - [climate3](https://savrn.com/datasets?domain=climate) - [code3](https://savrn.com/datasets?domain=code) - [crypto, cryptocurrency, finance3](https://savrn.com/datasets?domain=crypto%2C+cryptocurrency%2C+finance) - [data-attribution, influence-functions, interpretability3](https://savrn.com/datasets?domain=data-attribution%2C+influence-functions%2C+interpretability) - [fireviewer, fire, smoke3](https://savrn.com/datasets?domain=fireviewer%2C+fire%2C+smoke) - [video3](https://savrn.com/datasets?domain=video) - [LeRobot, lerobot, grabette2](https://savrn.com/datasets?domain=LeRobot%2C+lerobot%2C+grabette) - [LeRobot, ur7e, robotiq2](https://savrn.com/datasets?domain=LeRobot%2C+ur7e%2C+robotiq) - [agentenv, rl-environment, agents2](https://savrn.com/datasets?domain=agentenv%2C+rl-environment%2C+agents) - [ai-governance, measurement2](https://savrn.com/datasets?domain=ai-governance%2C+measurement) - [autonomous, agents, evolution2](https://savrn.com/datasets?domain=autonomous%2C+agents%2C+evolution) [Most downloaded](https://savrn.com/datasets?sort=downloads)[Most liked](https://savrn.com/datasets?sort=likes)[Recently updated](https://savrn.com/datasets?sort=updated)[Name](https://savrn.com/datasets?sort=name) 3,164 datasets, sorted by most downloaded. Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw) [SADSA](https://savrn.com/model-publishers/asd2sac21d) Annoy: This should be a the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: { "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-10) [DSAD](https://savrn.com/model-publishers/zxqwd12sad) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-10) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-11) [QSAD2](https://savrn.com/model-publishers/asd1dszd) We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version. Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-11) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-12) [55458](https://savrn.com/model-publishers/liufea154) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-12) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-13) [Dadsd](https://savrn.com/model-publishers/fwfasafd) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-13) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-14) [Saaffs454](https://savrn.com/model-publishers/saaffs454) We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version. Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-14) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-15) [WSDSAD](https://savrn.com/model-publishers/dsad2csa2zc) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-15) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-16) [QEQWDWQ](https://savrn.com/model-publishers/ascxz12sae1dw) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-16) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-17) [333](https://savrn.com/model-publishers/dfdgdg333) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-17) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-18) [ASD12D](https://savrn.com/model-publishers/assadasd1) We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version. Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-18) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-19) [DAS](https://savrn.com/model-publishers/asnjggdfsa) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-19) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-2) [444](https://savrn.com/model-publishers/ewrwerwerer44) Annoy: This should be a the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: { "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-2) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-20) [Fdaa](https://savrn.com/model-publishers/sddsasd) We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version. Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-20) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-21) [AS12ED](https://savrn.com/model-publishers/asd12ed31231) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-21) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-22) [21](https://savrn.com/model-publishers/sad1cz12dsa) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-22) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-23) [TatumAuden](https://savrn.com/model-publishers/tatumauden) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-23) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-24) [Afaf](https://savrn.com/model-publishers/asfdaaa) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-24) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-25) [Sdadsa](https://savrn.com/model-publishers/asdsa132dsa) We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version. Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-25) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-26) [SADADSA](https://savrn.com/model-publishers/dxbhafasf) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-26) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-27) [3535](https://savrn.com/model-publishers/safaf3e23) We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version. Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-27) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-28) [212](https://savrn.com/model-publishers/asd121sad) We release the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: Some of the ios are empty. The reason is that when executing the code, the input/output sizes are too large and exceed our required constraints. Thus, they are not stored or used later. Note: Due to imperfect LLM-based transformations, some problem descriptions do not contain enough information to describe the code. We leave this as future work to further enhance our data and update it to a better version. Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-28) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-29) [13321](https://savrn.com/model-publishers/sd324dcsa) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-29) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-3) [ASD](https://savrn.com/model-publishers/khfuiqwdwq) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-3) Dataset ### [Annoy-PyEdu-Rs-Raw](https://savrn.com/datasets/annoy-pyedu-rs-raw-30) [ASDQDC](https://savrn.com/model-publishers/sadnmcvc) the raw data for our processed PythonEdu-Rs dataset, adopted from the original dataset from HuggingFaceTB team. The data format for each line in the 0368500filteredv2ds25.sced.jsonl is as follows: "problemdescription" Publicly accessible [View dataset](https://savrn.com/datasets/annoy-pyedu-rs-raw-30) ## Model Collections Hand-picked starting points, each with the reason it exists. Collection · 4 entries ### [Embedding models for retrieval](https://savrn.com/collections/embedding-models-for-retrieval) Sentence and document embedding models used to build retrieval systems. Dimension and sequence length matter more than size here, and both come from the publisher. [View collection](https://savrn.com/collections/embedding-models-for-retrieval) Collection · 4 entries ### [Models that fit on one accelerator](https://savrn.com/collections/models-that-run-on-one-accelerator) Models whose publisher-reported parameter count puts them within reach of a single accelerator at common precisions. Memory needed depends on precision and serving configuration, so treat the parameter count as the starting point, not the answer. [View collection](https://savrn.com/collections/models-that-run-on-one-accelerator) Collection · 6 entries ### [Open-weight text models worth knowing](https://savrn.com/collections/open-weight-text-models-worth-knowing) Widely used open-weight language models, chosen because each one is a distinct family rather than a variant of the one above it. Selection, not a ranking. [View collection](https://savrn.com/collections/open-weight-text-models-worth-knowing) Collection · 3 entries ### [Speech and audio models](https://savrn.com/collections/speech-and-audio) Recognition and synthesis models, grouped so the two directions are easy to compare. [View collection](https://savrn.com/collections/speech-and-audio) ## Related SAVRN Research The hub sits beside SAVRN's market data and infrastructure research: what models cost to run, and what it takes to run them. SAVRN Index ### [What open models cost to run](https://savrn.com/ai-index/pricing/open-models) The same open-weight model priced by every host that serves it, per million tokens. Research Hub ### [Data center trackers and maps](https://savrn.com/data-center-research) Moratoriums, permits, power, water and capital behind the facilities that run these models. Method ### [How the Model Hub is built](https://savrn.com/model-hub/methodology) Sources, evidence labels, refresh behaviour, and the limits of every comparison here.