Meta

Muse Spark 1.3

Meta

Muse Spark 1.3 is a proprietary Meta multimodal reasoning model for coding and agentic knowledge work. The 1.3 update improves long instruction adherence, multi-task coordination, self-awareness of task limits, and cooperation with users during extended work. It accepts text, images, video, and audio and produces text; the API specifies a 1,048,576-token context for these versions. Standard and, where offered, Contributor access use the same model capabilities but different data-use terms. Contributor access is a serving tier rather than a separate model. Future open-weight plans are not a weight release.

Muse Glimmer

Meta

Muse Glimmer is Meta’s 30B open-weight multimodal model designed for local, always-on agent workflows. It transfers capabilities from Muse Spark through distillation, followed by longer-context mid-training, supervised tuning, reinforcement learning, and on-policy distillation. The model handles text and images, tool calling, coding, and multi-step plans under configurable reasoning effort. Apache-2.0 weights permit private deployment and adaptation. Consumer hardware viability depends on memory and quantization; local operation does not guarantee reliable autonomous behavior.

Muse Spark 1.2

Meta

Muse Spark 1.2 is a proprietary Meta multimodal reasoning model for coding and agentic knowledge work. The 1.2 update focuses on coding and tool-driven visual work, launching alongside the Muse Code terminal agent with stronger long-task and multimodal capabilities. It accepts text, images, video, and audio and produces text; the API specifies a 1,048,576-token context for these versions. Standard and, where offered, Contributor access use the same model capabilities but different data-use terms. Contributor access is a serving tier rather than a separate model. Future open-weight plans are not a weight release.

Muse Spark 1.1

Meta

Muse Spark 1.1 is a proprietary Meta multimodal reasoning model for coding and agentic knowledge work. The 1.1 update materially improves repository coding, multi-turn agents, and multimodal workflows, and introduces the public Meta Model API preview. It accepts text, images, video, and audio and produces text; the API specifies a 1,048,576-token context for these versions. Standard and, where offered, Contributor access use the same model capabilities but different data-use terms. Contributor access is a serving tier rather than a separate model. Future open-weight plans are not a weight release.

Muse Spark

Meta

Muse Spark is the first model developed by Meta Superintelligence Labs in the Muse family. It is a proprietary multimodal reasoning model with tool use, visual reasoning, and multi-agent orchestration, initially released through Meta AI on the web and in the app. It offers different response and reasoning modes for everyday questions and harder tasks. Its release marked a new training program rather than an open Llama checkpoint. Architecture and parameter count are not publicly disclosed, and planned future open-weight releases do not apply to this model.

Llama 4

Meta

Llama 4 is Meta’s first openly released mixture-of-experts generation with native image and text understanding. The released Scout and Maverick models each activate 17B parameters per token, but differ in expert count, total size, and context capacity. Scout provides a 10M-token context, while Maverick supports 1M. The announced Behemoth teacher was not a released checkpoint and is excluded. These models carry the custom Llama 4 Community License; large-scale use and multimodal geographic conditions require review of its terms.

Llama 3.3

Meta

Llama 3.3 is an open-weight Meta language-model release under its version-specific community license. This 70B instruction model improves multilingual, coding, and reasoning performance through updated post-training, aiming to approach the earlier 405B tier at lower serving cost. Downloadable weights support research and commercial deployment subject to the license and acceptable-use policy. Hosted inference is supplied through deployment partners. The model can produce unsupported claims, and safety or task quality must be evaluated in each application rather than inferred from the size label.

Llama 3.2

Meta

Llama 3.2 is an open-weight Meta language-model release under its version-specific community license. The 1B and 3B models are text-only edge models, while the separately trained 11B and 90B tiers add image understanding. The vision-tier license has additional geographic conditions. Downloadable weights support research and commercial deployment subject to the license and acceptable-use policy. Hosted inference is supplied through deployment partners. The model can produce unsupported claims, and safety or task quality must be evaluated in each application rather than inferred from the size label.

Llama 3.1 (405B)

Meta

Third-generation Llama model, reportedly 405B parameters with 15.6T tokens of training. Introduced a massive context window (128k tokens) and expanded multilingual capability. At release, it was the largest openly available model to date.

Llama 3

Meta

Llama 3 is an open-weight Meta language-model release under its version-specific community license. The initial Llama 3 generation provided 8B and 70B base and instruction models, trained on a new data mix with an expanded tokenizer. Downloadable weights support research and commercial deployment subject to the license and acceptable-use policy. Hosted inference is supplied through deployment partners. The model can produce unsupported claims, and safety or task quality must be evaluated in each application rather than inferred from the size label.

Llama 2 70B

Meta

70B-parameter successor to LLaMA, trained on 2 trillion tokens and fine-tuned for helpful dialogue. Released openly under a custom license allowing commercial use with some restrictions. Strong performance rivaling closed models like ChatGPT on many benchmarks.

LLaMA 65B

Meta

Large Language Model Meta AI, released in sizes up to 65B parameters for research. Achieved strong performance by training on 1.4T tokens; weights were leaked, spurring a wave of fine-tuned variants.

Galactica

Meta

120B-parameter model aimed at scientific text and knowledge integration. Notorious for generating plausible-sounding but incorrect scientific content; public demo was retracted.

OPT 175B

Meta

Open Pretrained Transformer, a reproduction of GPT-3 (175B) made openly available to researchers. Notably released with training logs and a non-commercial license.