provider stringclasses 54
values | name stringclasses 186
values | size stringclasses 120
values | variant stringclasses 110
values | version stringclasses 110
values | sector stringclasses 4
values | openness stringclasses 2
values | region stringclasses 5
values | country stringclasses 13
values | source_id stringclasses 434
values | is_first_party bool 2
classes | category int64 1 7 | year int64 2.02k 2.03k | metadata stringclasses 433
values | score float64 0 3 | is_model_release bool 2
classes |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
OpenAI | gpt-3.5 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
Google | palm-2 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
Google | gemma-1 | 2B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
Microsoft | llava-1.5 | 13B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | true | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
Meta | llama-2 | 70B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
Google | gemma-1 | 7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 3 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 3 | false |
Microsoft | llava-1.5 | 13B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | true | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Google | gemma-1 | 7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
OpenAI | gpt-3.5 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Meta | llama-2 | 70B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Meta | llama-2 | 13B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Google | gemini-1.0 | null | pro | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Google | palm-2 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Google | gemma-1 | 2B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Mistral | mistral | null | null | v1.0 | Industry | open | Europe | France | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
Meta | llama-2 | 7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_40 | false | 2 | 2,024 | {'title': 'Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks', 'url': 'https://aclanthology.org/2024.naacl-long.143.pdf', 'release_date': '2024-04-02'} | 2 | false |
OpenAI | gpt-4 | null | turbo | 2024-04-09 | Industry | closed | North America | United States | first-party-or-cooperative-evals_41 | false | 2 | 2,024 | {'title': 'EUREKA: Evaluating and Understanding Large Foundation Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/09/Eureka-Evaluating-and-Understanding-Large-Foundation-Models-Sept-13.pdf'} | 3 | false |
Anthropic | claude-3.5 | null | sonnet | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_41 | false | 2 | 2,024 | {'title': 'EUREKA: Evaluating and Understanding Large Foundation Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/09/Eureka-Evaluating-and-Understanding-Large-Foundation-Models-Sept-13.pdf'} | 3 | false |
Anthropic | claude-3 | null | opus | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_41 | false | 2 | 2,024 | {'title': 'EUREKA: Evaluating and Understanding Large Foundation Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/09/Eureka-Evaluating-and-Understanding-Large-Foundation-Models-Sept-13.pdf'} | 3 | false |
OpenAI | gpt-4 | null | null | 2024-05-13 | Industry | closed | North America | United States | first-party-or-cooperative-evals_41 | false | 2 | 2,024 | {'title': 'EUREKA: Evaluating and Understanding Large Foundation Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/09/Eureka-Evaluating-and-Understanding-Large-Foundation-Models-Sept-13.pdf'} | 3 | false |
Google | gemini-1.5 | null | pro | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_41 | false | 2 | 2,024 | {'title': 'EUREKA: Evaluating and Understanding Large Foundation Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/09/Eureka-Evaluating-and-Understanding-Large-Foundation-Models-Sept-13.pdf'} | 3 | false |
OpenAI | gpt-4 | null | preview | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_41 | false | 2 | 2,024 | {'title': 'EUREKA: Evaluating and Understanding Large Foundation Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/09/Eureka-Evaluating-and-Understanding-Large-Foundation-Models-Sept-13.pdf'} | 3 | false |
Mistral | mistral | 7B | null | null | Industry | open | Europe | France | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Meta | llama-2 | 7B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
OpenAI | gpt-4.1 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Meta | llama-2 | 13B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Alibaba | qwen-3 | 8B | null | null | Industry | open | East Asia | China | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Alibaba | qwen-3 | 32B | null | null | Industry | open | East Asia | China | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Meta | llama-2 | 70B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Microsoft | phi-4 | null | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Alibaba | qwen-2 | 72B | null | null | Industry | open | East Asia | China | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Meta | llama-3 | 8B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Alibaba | qwen-2 | 7B | null | null | Industry | open | East Asia | China | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
Meta | llama-3 | 70B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
OpenAI | gpt-3.5 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_42 | false | 2 | 2,025 | {'title': 'SocialCC: Interactive Evaluation for Cultural Competence in Language Agents', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2025/07/SocialCC-Interactive-Evaluation-for-Cultural-Competence-in-Language-Agents.pdf'} | 3 | false |
OpenAI | gpt-3.5 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Mistral | mistral | 7B | instruct | v0.2 | Industry | open | Europe | France | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Google | gemini-1.0 | null | pro | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Meta | llama-3 | 70B | instruct | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Meta | llama-3 | 8B | instruct | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Meta | llama-2 | 7B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
OpenAI | gpt-4 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Google | gemma-1 | 7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 3 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
OpenAI | gpt-4 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Mistral | mistral | 7B | instruct | v0.2 | Industry | open | Europe | France | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Google | gemini-1.0 | null | pro | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
OpenAI | gpt-3.5 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Meta | llama-3 | 70B | instruct | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Meta | llama-2 | 7B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Google | gemma-1 | 7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
Meta | llama-3 | 8B | instruct | null | Industry | open | North America | United States | first-party-or-cooperative-evals_43 | false | 2 | 2,024 | {'title': 'PARIKSHA: A Scalable, Democratic, Transparent Evaluation Platform for Assessing Indic Large Language Models', 'url': 'https://www.microsoft.com/en-us/research/wp-content/uploads/2024/05/Pariksha_Tech_Report_v1-663980ea39a84.pdf'} | 3 | false |
BigScience | bloom | 176B | null | null | Academia | open | Europe | France | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Meta | opt | 125M | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Meta | llama-1 | 13B | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Meta | llama-3 | 8B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Mistral | mixtral | 7B | null | null | Industry | open | Europe | France | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Google | gemma-2 | 27B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Meta | llama-1 | 70B | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Google | gemma-2 | 2B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Mistral | mistral | null | null | null | Industry | open | Europe | France | first-party-or-cooperative-evals_44 | false | 4 | 2,025 | {'title': 'EcoServe: Designing Carbon-Aware AI Inference Systems', 'url': 'https://www.arxiv.org/pdf/2502.05043'} | 3 | false |
Salesforce | instructblip | null | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_45 | false | 3 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
Microsoft | llava-1.5 | 7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_45 | false | 3 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
OpenAI | clip | null | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_45 | false | 3 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_45 | false | 3 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
Google | gemini-1.5 | null | flash | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_45 | false | 3 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_45 | false | 2 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
Google | gemini-1.5 | null | flash | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_45 | false | 2 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
OpenAI | clip | null | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_45 | false | 2 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
Microsoft | llava-1.5 | 7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_45 | false | 2 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
Salesforce | instructblip | null | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_45 | false | 2 | 2,024 | {'title': 'CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark', 'url': 'https://arxiv.org/pdf/2406.05967'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_46 | false | 6 | 2,024 | {'title': 'From Medprompt to o1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyond', 'url': 'https://arxiv.org/pdf/2411.03590'} | 1 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_46 | false | 6 | 2,024 | {'title': 'From Medprompt to o1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyond', 'url': 'https://arxiv.org/pdf/2411.03590'} | 1 | false |
OpenAI | o1 | null | preview | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_46 | false | 6 | 2,024 | {'title': 'From Medprompt to o1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyond', 'url': 'https://arxiv.org/pdf/2411.03590'} | 1 | false |
Microsoft | phi-3 | 3.82B | mini, 4k, instruct | null | Industry | open | North America | United States | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Alibaba | qwen-3 | 235B | 235B-A22B | null | Industry | open | East Asia | China | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Cohere | command-r | 104B | plus | 08-2024 | Industry | open | North America | Canada | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Alibaba | qwen-3 | 32B | null | null | Industry | open | East Asia | China | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Alibaba | qwen-2.5 | 72B | Instruct | null | Industry | open | East Asia | China | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Meta | llama-3.3 | 70B | Instruct | null | Industry | open | North America | United States | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Meta | llama-3.1 | 8B | Instruct | null | Industry | open | North America | United States | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Microsoft | phi-4 | 14.7B | null | null | Industry | open | North America | United States | first-party-or-cooperative-evals_5 | false | 4 | 2,025 | {'title': ""Bigger isn't always better: how to choose the most efficient model for context-specific tasks"", 'url': 'https://huggingface.co/blog/sasha/energy-efficiency-bigger-better'} | 2 | false |
Mistral | mistral-medium | null | null | null | Industry | closed | Europe | France | first-party-or-cooperative-evals_47 | false | 2 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
Mistral | mistral | 7B | instruct | null | Industry | open | Europe | France | first-party-or-cooperative-evals_47 | false | 2 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
Google | gemini-1.0 | null | pro | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_47 | false | 2 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_47 | false | 2 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
Meta | llama-2 | 70B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_47 | false | 2 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
OpenAI | gpt-3.5 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_47 | false | 2 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
Meta | llama-2 | 7B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_47 | false | 2 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
Mistral | mistral | 7B | instruct | null | Industry | open | Europe | France | first-party-or-cooperative-evals_47 | false | 1 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
Mistral | mistral-medium | null | null | null | Industry | closed | Europe | France | first-party-or-cooperative-evals_47 | false | 1 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
OpenAI | gpt-3.5 | null | null | turbo | Industry | closed | North America | United States | first-party-or-cooperative-evals_47 | false | 1 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
OpenAI | gpt-4 | null | null | null | Industry | closed | North America | United States | first-party-or-cooperative-evals_47 | false | 1 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
Meta | llama-2 | 70B | chat | null | Industry | open | North America | United States | first-party-or-cooperative-evals_47 | false | 1 | 2,025 | {'title': 'Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing', 'url': 'https://arxiv.org/pdf/2406.14230'} | 3 | false |
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