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Explore AI models 85003
Llama-Guard-3-8B
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View details ↗Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM...
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$0.18 / M input tokensOpenRouter · meta-llama/llama-guard-4-12b
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View details ↗LlamaGuard-7b
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View details ↗MetaMath-Mistral-7B
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View details ↗Meta-Llama-3-70B
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View details ↗Meta-Llama-3-8B
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View details ↗Muse-Glimmer-30B-assistant
meta-models**Authors:** Meta Superintelligence Lab **Model Release Date:** August 2026 **License:** Apache 2.0 > [!NOTE] This model card is for the lightweight "drafter" model for Muse Glimmer 30B, based on DFlash. The DFlash block-diffusion model predicts entire blocks of 16 tokens in a single forward pass. The main model then verifies these proposals in parallel, accepting correct tokens and correcting wrong ones. This technique lets Muse Glimmer generate text significantly faster than standard token-by-token generation while producing identical output quality. Muse Glimmer is a 30-billion-parameter causal language model with a dedicated perception encoder, distilled from Muse Spark and purpose-built for autonomous agentic tasks on consumer hardware. The model integrates multi-step reasoning, reliable tool use, multimodal understanding, and failure recovery into a single model that runs locally without requiring cloud infrastructure or network access.
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View details ↗Muse-Glimmer-30B-ExecuTorch-PTE
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View details ↗Muse-Glimmer-30B-GGUF
meta-models**Authors:** Meta Superintelligence Lab **Model Release Date:** August 2026 **License:** Apache 2.0 > [!NOTE] > This repo contains GGUF conversions of `meta-models/Muse-Glimmer-30B` for llama.cpp: two quantized text builds, a perception encoder for image input, and a DFlash drafter for speculative decoding. > Everything you need to install, download and serve them is on this page. No bf16 GGUF is published here — use the base repo if you need full precision. Muse Glimmer is a 30-billion-parameter causal language model with a dedicated perception encoder, distilled from Muse Spark and purpose-built for autonomous agentic tasks on consumer hardware. The model integrates multi-step reasoning, reliable tool use, multimodal understanding, and failure recovery into a single model that runs locally without requiring cloud infrastructure or network access.
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View details ↗Muse-Spark-Open-816B-A42B-NVFP4
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View details ↗Muse Ember
MetaMuse Ember is the smallest and most efficient model from Meta that’s designed for complex reasoning execution and the work agents repeat all day: tool calls, coding agent subtasks, routing,...
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View details ↗Muse Glimmer 30B
MetaMuse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...
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$0.3 / M input tokensOpenRouter · meta/muse-glimmer-30b
View details ↗Muse Spark
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View details ↗Muse Spark 1.1
MetaMuse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, and PDF documents and returns text, with a 1M-token context window....
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$1.25 / M input tokensOpenRouter · meta/muse-spark-1.1
View details ↗Muse Spark 1.2
MetaMuse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, and PDF documents, returns text, and offers a 1M-token context window....
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$1.25 / M input tokensOpenRouter · meta/muse-spark-1.2
View details ↗Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost. It’s meaningfully cheaper than Muse Spark...
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$0.1 / M input tokensOpenRouter · meta/muse-spark-1.2-contributor
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