Provider, United States # Meta models > Meta's highest-ranked model is Muse Spark 1.3, #27 on the Noometry Index as of October 2026. Noometry tracks 27 Meta models, 20 with open weights. Benchmarks, prices and context windows for every Meta model. - Canonical page: https://noometry.com/providers/meta - Last updated: 2026-10-10 - Title: Meta AI Models Ranked (October 2026) | Noometry Meta's highest-ranked model is Muse Spark 1.3, #27 on the Noometry Index as of October 2026. Noometry tracks 27 Meta models, 20 with open weights. Last verified October 10, 2026 [ai.meta.com](https://ai.meta.com) 27 models Meta models | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 27 | ![](/logos/meta.svg) Meta [Muse Spark 1.3](https://noometry.com/models/muse-spark-1-3) | [Meta](https://noometry.com/providers/meta) | Proprietary | 1.05M | 54.8 | $1.25 | $4.25 | 27.4 | — | | 46 | ![](/logos/meta.svg) Meta [Muse Spark](https://noometry.com/models/muse-spark) | [Meta](https://noometry.com/providers/meta) | Proprietary | — | 50.6 | — | — | — | — | | 48 | ![](/logos/meta.svg) Meta [Muse Spark 1.2](https://noometry.com/models/muse-spark-1-2) | [Meta](https://noometry.com/providers/meta) | Proprietary | 1.05M | 50.3 | $1.25 | $4.25 | 25.2 | — | | 51 | ![](/logos/meta.svg) Meta [Muse Spark 1.1](https://noometry.com/models/muse-spark-1-1) | [Meta](https://noometry.com/providers/meta) | Proprietary | 1.05M | 49.9 | $1.25 | $4.25 | 25 | — | | 131 | ![](/logos/meta.svg) Meta [Muse Glimmer](https://noometry.com/models/muse-glimmer) | [Meta](https://noometry.com/providers/meta) | Open | — | 41.7 | — | — | — | — | | 237 | ![](/logos/meta.svg) Meta [Codellama 70b Instruct](https://noometry.com/models/codellama-70b-instruct) | [Meta](https://noometry.com/providers/meta) | Open | — | 33.7 | — | — | — | — | | 282 | ![](/logos/meta.svg) Meta [Llama 4 Maverick](https://noometry.com/models/llama-4-maverick) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 30.9 | $0.19 | $0.65 | 102 | 456 | | 287 | ![](/logos/meta.svg) Meta [Codellama 34b Instruct](https://noometry.com/models/codellama-34b-instruct) | [Meta](https://noometry.com/providers/meta) | Open | — | 30.8 | — | — | — | — | | 288 | ![](/logos/meta.svg) Meta [Llama 3.1-405B](https://noometry.com/models/llama-3-1-405b) | [Meta](https://noometry.com/providers/meta) | Open | — | 30.7 | — | — | — | 78 | | 291 | ![](/logos/meta.svg) Meta [Llama-3.3-70B-Instruct](https://noometry.com/models/llama-3-3-70b-instruct) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 30.6 | $0.10 | $0.32 | 197 | — | | 308 | ![](/logos/meta.svg) Meta [Llama 3.1-70B](https://noometry.com/models/llama-3-1-70b) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 29.6 | $0.40 | $0.40 | 74.1 | — | | 309 | ![](/logos/meta.svg) Meta [Llama 2-13B](https://noometry.com/models/llama-2-13b) | [Meta](https://noometry.com/providers/meta) | Open | — | 29.6 | — | — | — | — | | 317 | ![](/logos/meta.svg) Meta [Llama 2-7B](https://noometry.com/models/llama-2-7b) | [Meta](https://noometry.com/providers/meta) | Open | — | 29.1 | — | — | — | — | | 321 | ![](/logos/meta.svg) Meta [Llama 3.2 3B](https://noometry.com/models/llama-3-2-3b) | [Meta](https://noometry.com/providers/meta) | Open | 131K | 28.9 | $0.05 | $0.33 | 241 | — | | 323 | ![](/logos/meta.svg) Meta [Llama 3-70B](https://noometry.com/models/llama-3-70b) | [Meta](https://noometry.com/providers/meta) | Open | — | 28.8 | — | — | — | 104 | | 330 | ![](/logos/meta.svg) Meta [Llama 4 Scout](https://noometry.com/models/llama-4-scout) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 27.7 | $0.10 | $0.30 | 184 | 272 | | 331 | ![](/logos/meta.svg) Meta [Llama 3.2 90B](https://noometry.com/models/llama-3-2-90b) | [Meta](https://noometry.com/providers/meta) | Open | — | 27.5 | — | — | — | — | | 344 | ![](/logos/meta.svg) Meta [Llama 3-8B](https://noometry.com/models/llama-3-8b) | [Meta](https://noometry.com/providers/meta) | Open | — | 25.5 | — | — | — | — | | 348 | ![](/logos/meta.svg) Meta [Llama 13b](https://noometry.com/models/llama-13b) | [Meta](https://noometry.com/providers/meta) | Open | — | 24.4 | — | — | — | — | | 349 | ![](/logos/meta.svg) Meta [Llama 2-70B](https://noometry.com/models/llama-2-70b) | [Meta](https://noometry.com/providers/meta) | Open | — | 24.4 | — | — | — | — | | 352 | ![](/logos/meta.svg) Meta [Llama 3.1-8B](https://noometry.com/models/llama-3-1-8b) | [Meta](https://noometry.com/providers/meta) | Open | 128K | 23.0 | $0.05 | $0.08 | 400 | — | | 354 | ![](/logos/meta.svg) Meta [Llama 3.2 1B](https://noometry.com/models/llama-3-2-1b) | [Meta](https://noometry.com/providers/meta) | Open | 60K | 20.1 | $0.027 | $0.20 | 286 | — | | | ![](/logos/meta.svg) Meta [Llama 2-34B](https://noometry.com/models/llama-2-34b) | [Meta](https://noometry.com/providers/meta) | Proprietary | — | Not ranked | — | — | — | — | | | ![](/logos/meta.svg) Meta [Llama 3.2 11B](https://noometry.com/models/llama-3-2-11b) | [Meta](https://noometry.com/providers/meta) | Open | — | Not ranked | — | — | — | — | | | ![](/logos/meta.svg) Meta [Muse Glimmer 30B](https://noometry.com/models/muse-glimmer-30b) | [Meta](https://noometry.com/providers/meta) | Open | 131K | Not ranked | $0.30 | $1.20 | — | — | | | ![](/logos/meta.svg) Meta [Muse Spark 1.2 Contributor](https://noometry.com/models/muse-spark-1-2-contributor) | [Meta](https://noometry.com/providers/meta) | Proprietary | 1.05M | Not ranked | $0.10 | $0.20 | — | — | | | ![](/logos/meta.svg) Meta [Muse Spark 1.3 Contributor](https://noometry.com/models/muse-spark-1-3-contributor) | [Meta](https://noometry.com/providers/meta) | Proprietary | 1.05M | Not ranked | $0.10 | $0.20 | — | — | ## Meta's best vs other flagships - [Muse Spark 1.3 vs Qwen3.8 Max](https://noometry.com/compare/muse-spark-1-3-vs-qwen3-8-max) - [Muse Spark 1.3 vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-muse-spark-1-3) - [Muse Spark 1.3 vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-muse-spark-1-3) - [Muse Spark 1.3 vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-muse-spark-1-3) - [Muse Spark 1.3 vs Mistral Large 4](https://noometry.com/compare/mistral-large-4-vs-muse-spark-1-3) - [Muse Spark 1.3 vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-muse-spark-1-3) ## Frequently asked questions ### What is the best Meta model? Meta's highest-ranked model is Muse Spark 1.3, #27 on the Noometry Index as of October 2026. Noometry tracks 27 Meta models, 20 with open weights. ### What is the cheapest Meta model? Llama 3.2 1B has the lowest input price among Meta models we track: $0.027 per million input tokens and $0.20 per million output tokens.