Reasoning Tools JSON

Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.

meta/muse-spark-1.3 2026-09-02 1.04858M context $1.25/M input $4.25/M output
9 providers
Reasoning Tools JSON Open weights

Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.

meta/muse-glimmer-30b 2026-08-10 131.072K context $0.2/M input $0.8/M output
9 providers
Reasoning Tools JSON

Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.

meta/muse-spark-1.2 2026-08-05 1.04858M context $1.25/M input $4.25/M output
14 providers
Reasoning

Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.

meta/muse-spark-1.1 2026-04-08 1.04858M context $1.25/M input $4.25/M output
12 providers
Open weights

Open Llama with long-context vision for efficient multimodal agents

meta/llama-4-scout-17b-instruct 2025-04-05 3.5M context $0.17/M input $0.66/M output
2 providers
Tools Open weights

Open multimodal Llama for strong reasoning with efficient everyday serving

meta/llama-4-maverick-17b-instruct 2025-04-05 1M context $0.14/M input $0.59/M output
6 providers
Tools JSON Open weights

Open multimodal Llama model for image understanding, captioning, and visual QA

meta/llama-3.2-11b-vision-instruct 2024-09-25 128K context $0.055/M input $0.055/M output
3 providers

Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and...

meta-llama/llama-3.2-11b-vision-instruct 131.072K context $0.345/M input $0.345/M output

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...

meta-llama/llama-guard-4-12b 163.84K context $0.18/M input $0.18/M output

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

meta-llama/llama-4-scout 327.68K context $0.1/M input $0.3/M output

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...

meta/muse-spark-1.2-contributor 1.04858M context $0.1/M input $0.2/M output

Muse 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...

meta/muse-glimmer-30b:batch 131.072K context $0.175/M input $0.75/M output

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...

meta-llama/llama-4-maverick 128K context $0.2/M input $0.696/M output

Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...

meta/muse-spark-1.3-contributor 1.04858M context $0.1/M input $0.2/M output