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=37 | 11026 | 11026 | 11026 | 11026 |
| restricted-weights n=13 | 1300 | 1300 | 1300 | 0130 |
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 | |
|---|---|---|---|---|---|---|---|---|
| LFM2.5-350MOpen weightsLiquid AI | Other | 354.5M | — | 31 Mar 2026 | — | 0 | ✓ fits0.7 GB4bit✓ fits0.9 GB8bit | |
| LFM2.5-350M-BaseOpen weightsLiquid AI | —unclassified | — | — | — | — | 0 | —— | |
| LFM2.5-8B-A1B-BaseOpen weightsLiquid AI | —unclassified | — | — | — | — | 0 | —— | |
| LFM2.5-8B-A1B-DSparkOpen weightsLiquid AI | —unclassified | — | — | — | — | 0 | —— | |
| LFM2.5-Audio-1.5BOpen weightsLiquid AI | —unclassified | — | — | — | — | 0 | —— | |
| LFM2.5-VL-3BOpen weightsLiquid AI | Other | 3.12B | — | 11 Aug 2026 | — | 0 | ✓ fits2.3 GB4bit✓ fits4.1 GB8bit | |
| LFM2.5-VL-450MOpen weightsLiquid AI | Other | 448.7M | — | 8 Apr 2026 | — | 0 | ✓ fits0.8 GB4bit✓ fits1.0 GB8bit | |
| Laguna S 2.1Open weightsPoolside · text | —unclassified | — | 1.05M | 21 Jul 2026 | — | 1from $0.18 out | —— | |
| Laguna XS 2.1Open weightsPoolside · text | —unclassified | — | 262.1K | 2 Jul 2026 | — | 1from $0.12 out | —— | |
| Leanstral 1.5Open weightsMistral AI | Apache-2.0 | — | 256K | — | — | 1 | —— | |
| Llama 3 8B LunarisOpen weightsSao10K · text | —unclassified | — | 8.19K | 13 Aug 2024 | — | 1from $0.05 out | —— | |
| Llama 3.1 70B Instructrestricted-weightsMeta AI · text | Llama-3.1-Community | 70.5B | 131.1K | 23 Jul 2024 | — | 1from $0.72 out | ✓ fits41.1 GB4bit✓ fits81.6 GB8bit | |
| Llama 3.1 8B Instructrestricted-weightsMeta AI · text | Llama-3.1-Community | 8.03B | 131.1K | 23 Jul 2024 | — | 1from $0.08 out | ✓ fits5.1 GB4bit✓ fits9.7 GB8bit | |
| Llama 3.1 Euryale 70B v2.2Open weightsSao10K · text | —unclassified | — | 131.1K | 28 Aug 2024 | — | 1from $0.85 out | —— | |
| Llama 3.2 1B Instructrestricted-weightsMeta AI · text | Llama-3.2-Community | 1.24B | 60K | 18 Sept 2024 | — | 1from $0.201 out | ✓ fits1.2 GB4bit✓ fits1.9 GB8bit | |
| Llama 3.2 3B Instructrestricted-weightsMeta AI · text | Llama-3.2-Community | 3.21B | 131.1K | 18 Sept 2024 | — | 1from $0.33 out | ✓ fits2.4 GB4bit✓ fits4.2 GB8bit | |
| Llama 3.3 70B Instructrestricted-weightsMeta AI · text | Llama-3.3-Community | 70.5B | 131.1K | 26 Nov 2024 | — | 1from $0.32 out | ✓ fits41.1 GB4bit✓ fits81.6 GB8bit | |
| Llama 3.3 Euryale 70BOpen weightsSao10K · text | —unclassified | — | 131.1K | 18 Dec 2024 | — | 1from $0.75 out | —— | |
| Llama Guard 4 12BOpen weightsMeta AI · image, text | —unclassified | — | 163.8K | 30 Apr 2025 | — | 1from $0.18 out | —— | |
| Llama-2-13b-chat-hfrestricted-weightsMeta AI | Llama-2-Community | 13B | — | 13 Jul 2023 | — | 0 | ✓ fits8.0 GB4bit✓ fits15.5 GB8bit | |
| Llama-2-7b-chat-hfrestricted-weightsMeta AI | Llama-2-Community | 6.74B | — | 13 Jul 2023 | — | 0 | ✓ fits4.4 GB4bit✓ fits8.3 GB8bit | |
| Llama-2-7b-hfrestricted-weightsMeta AI | Llama-2-Community | 6.74B | — | 13 Jul 2023 | — | 0 | ✓ fits4.4 GB4bit✓ fits8.3 GB8bit | |
| Llama-3.2-11B-Vision-Instructrestricted-weightsMeta AI | Llama-3.2-Community | 10.7B | — | 18 Sept 2024 | — | 0 | ✓ fits6.6 GB4bit✓ fits12.8 GB8bit | |
| Llama-3.2-90B-Vision-Instructrestricted-weightsMeta AI | Llama-3.2-Community | 88.6B | — | 19 Sept 2024 | — | 0 | ✓ fits51.4 GB4bit✓ fits102.4 GB8bit | |
| Llama-4-Scout-17B-16EOpen weightsMeta AI | —unclassified | — | — | — | — | 0 | —— | |
| M1-3BOpen weightsTogether AI | MIT | 3.45B | — | 2 May 2025 | — | 0 | ✓ fits2.5 GB4bit✓ fits4.5 GB8bit | |
| Meta-Llama-3-70Brestricted-weightsMeta AI | Llama-3-Community | 70.5B | — | 17 Apr 2024 | — | 0 | ✓ fits41.1 GB4bit✓ fits81.6 GB8bit | |
| Meta-Llama-3-8Brestricted-weightsMeta AI | Llama-3-Community | 8.03B | — | 17 Apr 2024 | — | 0 | ✓ fits5.1 GB4bit✓ fits9.7 GB8bit | |
| Meta-Llama-3-8B-Instructrestricted-weightsMeta AI | Llama-3-Community | 8.03B | — | 17 Apr 2024 | — | 0 | ✓ fits5.1 GB4bit✓ fits9.7 GB8bit | |
| Meta-Llama-3.1-70BOpen weightsMeta AI | —unclassified | — | — | — | — | 0 | —— | |
| Meta-Llama-3.1-8BOpen weightsMeta AI | —unclassified | — | — | — | — | 0 | —— | |
| Meta-Llama-3.2-3BOpen weightsMeta AI | —unclassified | — | — | — | — | 0 | —— | |
| MiniMax-01Open weightsMiniMax · image, text | —unclassified | 456.1B | 1M | 12 Jan 2025 | — | 1from $1.1 out | ✗ too large262.8 GB4bit✗ too large525.0 GB8bit | |
| MiniMax-H3Open weightsMiniMax | Other | 33.1B | — | 28 Jul 2026 | — | 0 | ✓ fits19.5 GB4bit✓ fits38.6 GB8bit | |
| MiniMax-M1-40k-hfOpen weightsMiniMax | Apache-2.0 | 456.1B | — | 1 Jul 2025 | — | 0 | ✗ too large262.8 GB4bit✗ too large525.0 GB8bit | |
| MiniMax-M1-80k-hfOpen weightsMiniMax | Apache-2.0 | 456.1B | — | 1 Jul 2025 | — | 0 | ✗ too large262.8 GB4bit✗ too large525.0 GB8bit | |
| MiniMax-Music3Open weightsMiniMax | —unclassified | 2.43B | — | 7 Aug 2026 | — | 0 | ✓ fits1.9 GB4bit✓ fits3.3 GB8bit | |
| MiniMax-Text-01-hfOpen weightsMiniMax | Other | 456.1B | — | 3 Jun 2025 | — | 0 | ✗ too large262.8 GB4bit✗ too large525.0 GB8bit | |
| MiniMax-VL-01Open weightsMiniMax | —unclassified | 456.4B | — | 12 Jan 2025 | — | 0 | ✗ too large262.9 GB4bit✗ too large525.4 GB8bit | |
| Ministral 3 14B 2512Open weightsMistral AI · image, text | Apache-2.0 | 13.9B | 262.1K | 31 Oct 2025 | — | 1from $0.20 out | ✓ fits8.5 GB4bit✓ fits16.5 GB8bit | |
| Ministral 3 3B 2512Open weightsMistral AI · image, text | Apache-2.0 | 3.85B | 131.1K | 31 Oct 2025 | — | 1from $0.10 out | ✓ fits2.7 GB4bit✓ fits4.9 GB8bit | |
| Ministral 3 8B 2512Open weightsMistral AI · image, text | —unclassified | — | 262.1K | 2 Dec 2025 | — | 1from $0.075 out | —— | |
| Ministral-3-14B-Base-2512Open weightsMistral AI | —unclassified | — | — | — | — | 0 | —— | |
| Ministral-3-14B-Reasoning-2512Open weightsMistral AI | Apache-2.0 | 13.9B | — | 31 Oct 2025 | — | 0 | ✓ fits8.5 GB4bit✓ fits16.5 GB8bit | |
| Ministral-3-3B-Base-2512Open weightsMistral AI | —unclassified | — | — | — | — | 0 | —— | |
| Ministral-3-3B-Reasoning-2512Open weightsMistral AI | Apache-2.0 | 4.25B | — | 31 Oct 2025 | — | 0 | ✓ fits3.0 GB4bit✓ fits5.4 GB8bit | |
| Ministral-8B-Instruct-2410Open weightsMistral AI | Other | 8.02B | — | 15 Oct 2024 | — | 0 | ✓ fits5.1 GB4bit✓ fits9.7 GB8bit | |
| Mistral NemoOpen weightsMistral AI · text | Apache-2.0 | 12.3B | 131.1K | 17 Jul 2024 | — | 1from $0.03 out | ✓ fits7.5 GB4bit✓ fits14.6 GB8bit | |
| Mistral Small 3.1 24BOpen weightsMistral AI · image, text | Apache-2.0 | 24B | 128K | 11 Mar 2025 | — | 1from $0.555 out | ✓ fits14.3 GB4bit✓ fits28.1 GB8bit | |
| Mistral Small 3.2 24BOpen weightsMistral AI · image, text | Apache-2.0 | 24B | 256K | 19 Jun 2025 | — | 1from $0.20 out | ✓ fits14.3 GB4bit✓ fits28.1 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