Open models
Every canonical model whose weights can be downloaded, described by measurable properties — licence permissions, parameters, context, release, benchmark ranks, providers, estimated local fit. Openness is a set of observed dimensions here, never a score.
950 downloadable models
Openness explorer
Categories and licence permissions
Left: the downloadable universe by openness category. Right: what the licences on this page allow, counted per category — allowed · restricted · unknown.
- Open source1 0%
- Open weights869 91%
- Restricted weights80 8%
Top licences: Apache License 2.0 (275) · Other (unclassified licence) (115) · MIT License (92) · Creative Commons Attribution-NonCommercial 4.0 (22) · Apple Sample Code / ML Research License (15) · Llama 3.2 Community License (12)
| Category · this page | Commercial use | Redistribution | Derivatives | Hosting |
|---|---|---|---|---|
| Open source n=0 | — | — | — | — |
| Open weights n=39 | 19020 | 19020 | 19020 | 19020 |
| restricted-weights n=11 | 650 | 1100 | 1100 | 1100 |
Counts read: allowed · restricted · unknown / unclassified — over the 50 models on this page, from each licence's stated terms (ontology).
Downloadable models
950 models · sorted by best benchmark rank
Permissions, in order:commercial use· redistribution· derivatives· hosting allowed restricted unknown
| Model | Licence · permissions | Params | Context | Release | Best results | Providers | Fit 64 GB @4bit · 128 GB @8bit Estimated | |
|---|---|---|---|---|---|---|---|---|
| qwen-chat-72bOpen weightsAlibaba Group | —unclassified | — | 33.8K | — | artificial-analysis-intelligence-index#422 | 0 | —— | |
| deepseek-llm-67b-chatOpen weightsDeepSeek | —unclassified | — | 4.1K | — | artificial-analysis-intelligence-index#430 | 0 | —— | |
| llama-65bOpen weightsMeta AI | —unclassified | — | 2.05K | — | artificial-analysis-intelligence-index#452 | 0 | —— | |
| qwen-chat-14bOpen weightsAlibaba Group | —unclassified | — | 8.19K | — | artificial-analysis-intelligence-index#452 | 0 | —— | |
| 3b-de-ft-research_releaseOpen weightsCanopy Labs | Apache-2.0 | 3.3B | — | 2 Apr 2025 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.3 GB8bit | |
| 3b-de-pretrain-research_releaserestricted-weightsCanopy Labs | Llama-3.2-Community | 3.78B | — | 23 Mar 2025 | — | 0 | ✓ fits2.7 GB4bit✓ fits4.8 GB8bit | |
| 3b-es_it-ft-research_releaseOpen weightsCanopy Labs | Apache-2.0 | 3.3B | — | 4 Apr 2025 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.3 GB8bit | |
| 3b-es_it-pretrain-research_releaserestricted-weightsCanopy Labs | Llama-3.2-Community | 3.78B | — | 27 Mar 2025 | — | 0 | ✓ fits2.7 GB4bit✓ fits4.8 GB8bit | |
| 3b-fr-ft-research_releaseOpen weightsCanopy Labs | Apache-2.0 | 3.3B | — | 3 Apr 2025 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.3 GB8bit | |
| 3b-fr-pretrain-research_releaserestricted-weightsCanopy Labs | Llama-3.2-Community | 3.78B | — | 2 Apr 2025 | — | 0 | ✓ fits2.7 GB4bit✓ fits4.8 GB8bit | |
| 3b-hi-ft-research_releaseOpen weightsCanopy Labs | Apache-2.0 | 3.3B | — | 8 Apr 2025 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.3 GB8bit | |
| 3b-hi-pretrain-research_releaserestricted-weightsCanopy Labs | Llama-3.2-Community | 3.78B | — | 8 Apr 2025 | — | 0 | ✓ fits2.7 GB4bit✓ fits4.8 GB8bit | |
| 3b-ko-ft-research_releaseOpen weightsCanopy Labs | Apache-2.0 | 3.3B | — | 6 Apr 2025 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.3 GB8bit | |
| 3b-ko-pretrain-research_releaseOpen weightsCanopy Labs | Apache-2.0 | 3.78B | — | 2 Apr 2025 | — | 0 | ✓ fits2.7 GB4bit✓ fits4.8 GB8bit | |
| 3b-zh-ft-research_releaseOpen weightsCanopy Labs | Apache-2.0 | 3.3B | — | 6 Apr 2025 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.3 GB8bit | |
| 3b-zh-pretrain-research_releaserestricted-weightsCanopy Labs | Llama-3.2-Community | 3.78B | — | 3 Apr 2025 | — | 0 | ✓ fits2.7 GB4bit✓ fits4.8 GB8bit | |
| AI21-Jamba-Large-1.5Open weightsAI21 Labs | Other | 398.6B | — | 19 Aug 2024 | — | 0 | ✗ too large229.7 GB4bit✗ too large458.8 GB8bit | |
| AI21-Jamba-Large-1.6Open weightsAI21 Labs | Other | 398.6B | — | 27 Feb 2025 | — | 0 | ✗ too large229.7 GB4bit✗ too large458.8 GB8bit | |
| AI21-Jamba-Large-1.7Open weightsAI21 Labs | Other | 398.6B | — | 2 Jul 2025 | — | 0 | ✗ too large229.7 GB4bit✗ too large458.8 GB8bit | |
| AI21-Jamba-Mini-1.5Open weightsAI21 Labs | Other | 51.6B | — | 19 Aug 2024 | — | 0 | ✓ fits30.2 GB4bit✓ fits59.8 GB8bit | |
| AI21-Jamba-Mini-1.6Open weightsAI21 Labs | Other | 51.6B | — | 27 Feb 2025 | — | 0 | ✓ fits30.2 GB4bit✓ fits59.8 GB8bit | |
| AI21-Jamba-Mini-1.7Open weightsAI21 Labs | Other | 51.6B | — | 1 Jul 2025 | — | 0 | ✓ fits30.2 GB4bit✓ fits59.8 GB8bit | |
| AI21-Jamba-Reasoning-3BOpen weightsAI21 Labs | Apache-2.0 | 3.2B | — | 5 Oct 2025 | — | 0 | ✓ fits2.3 GB4bit✓ fits4.2 GB8bit | |
| AI21-Jamba2-3BOpen weightsAI21 Labs | Apache-2.0 | 3.03B | — | 6 Jan 2026 | — | 0 | ✓ fits2.2 GB4bit✓ fits4.0 GB8bit | |
| AI21-Jamba2-MiniOpen weightsAI21 Labs | Apache-2.0 | 51.6B | — | 6 Jan 2026 | — | 0 | ✓ fits30.2 GB4bit✓ fits59.8 GB8bit | |
| AREX-TurboOpen weightsBAAI | —unclassified | — | — | — | — | 0 | —— | |
| Aurora-Spec-Minimax-M2.5Open weightsTogether AI | Apache-2.0 | 857.9M | — | 19 Feb 2026 | — | 0 | ✓ fits1.0 GB4bit✓ fits1.5 GB8bit | |
| BAGEL-7B-MoTOpen weightsByteDance | Apache-2.0 | 14.7B | — | 19 May 2025 | — | 0 | ✓ fits8.9 GB4bit✓ fits17.4 GB8bit | |
| BFS-Prover-V2-7BOpen weightsByteDance | Apache-2.0 | 7.62B | — | 6 Oct 2025 | — | 0 | ✓ fits4.9 GB4bit✓ fits9.3 GB8bit | |
| BigBang-v1Open weightsendless-frontier | —unclassified | — | — | — | — | 0 | —— | |
| BioMedLMrestricted-weightsStanford CRFM | BigScience-BLOOM-RAIL-1.0 | — | — | 14 Dec 2022 | — | 0 | —— | |
| BiomedNLP-BiomedBERT-base-uncased-abstractOpen weightsMicrosoft | MIT | — | — | 2 Mar 2022 | — | 0 | —— | |
| Cohere-embed-english-v3.0Open weightsCohere | —unclassified | — | — | 2 Nov 2023 | — | 0 | —— | |
| Cohere-embed-multilingual-v3.0Open weightsCohere | —unclassified | — | — | 2 Nov 2023 | — | 0 | —— | |
| Cosmos-Reason2-2BOpen weightsNVIDIA | Other | 2.44B | — | 12 Dec 2025 | — | 0 | ✓ fits1.9 GB4bit✓ fits3.3 GB8bit | |
| Cosmos3-EdgeOpen weightsNVIDIA | Other | 3.86B | — | 1 Jul 2026 | — | 0 | ✓ fits2.7 GB4bit✓ fits4.9 GB8bit | |
| Cydonia 24B V4.1Open weightsTheDrummer · text | —unclassified | — | 131.1K | 27 Sept 2025 | — | 1from $0.50 out | —— | |
| DFN2B-CLIP-ViT-B-16restricted-weightsApple | Apple-AMLR | — | — | 31 Oct 2023 | — | 0 | —— | |
| DFN2B-CLIP-ViT-L-14restricted-weightsApple | Apple-AMLR | — | — | 30 Oct 2023 | — | 0 | —— | |
| DFN2B-CLIP-ViT-L-14-39Brestricted-weightsApple | Apple-AMLR | 39B | — | 8 Jul 2024 | — | 0 | ✓ fits22.9 GB4bit✓ fits45.4 GB8bit | |
| DFN5B-CLIP-ViT-H-14restricted-weightsApple | Apple-AMLR | — | — | 30 Oct 2023 | — | 0 | —— | |
| DFN5B-CLIP-ViT-H-14-378restricted-weightsApple | Apple-AMLR | — | — | 30 Oct 2023 | — | 0 | —— | |
| DeepSeek V4 Flash 0423Open weightsDeepSeek · text | MIT | 290.9B | 1.05M | 22 Apr 2026 | — | 1from $0.134 out | ✗ too large167.8 GB4bit✗ too large335.1 GB8bit | |
| DeepSeek V4 Pro 0423Open weightsDeepSeek · text | MIT | 1.6T | 1.05M | 22 Apr 2026 | — | 1from $1.64 out | ✗ too large919.8 GB4bit✗ too large1839.2 GB8bit | |
| DeepSeek-Coder-V2-Lite-InstructOpen weightsDeepSeek | Other | 15.7B | — | 14 Jun 2024 | — | 0 | ✓ fits9.5 GB4bit✓ fits18.6 GB8bit | |
| DeepSeek-OCROpen weightsDeepSeek | MIT | 3.34B | — | 17 Oct 2025 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.3 GB8bit | |
| DeepSeek-OCR-2Open weightsDeepSeek | Apache-2.0 | 3.39B | — | 27 Jan 2026 | — | 0 | ✓ fits2.4 GB4bit✓ fits4.4 GB8bit | |
| DeepSeek-R1-0528Open weightsDeepSeek | —unclassified | — | — | — | — | 0 | —— | |
| DeepSeek-R1-Distill-Qwen-7BOpen weightsDeepSeek | MIT | 7.62B | — | 20 Jan 2025 | — | 0 | ✓ fits4.9 GB4bit✓ fits9.3 GB8bit | |
| DeepSeek-V2-LiteOpen weightsDeepSeek | Other | 15.7B | — | 15 May 2024 | — | 0 | ✓ fits9.5 GB4bit✓ fits18.6 GB8bit |
Best results = rank inside each benchmark's primary comparability group; several dimensions are shown side by side and never combined. Fit columns are estimates (64 GB device at 4-bit, 128 GB at 8-bit, 8K context) — method on /methodology. unclassified = the raw licence label is not yet mapped in the ontology.
MethodUniverse = canonical models whose weights can be downloaded (open-weights, open-source, restricted-weights). hardware_fit values are ESTIMATES (see /methodology); best_results are ranks inside each benchmark's primary comparability group — no composite score. /methodology