Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
Muse Wonder Full is the most capable model in Meta's Muse Wonder series, built for long-running professional agents and ultra-long-horizon software engineering. It shares Muse Wonder's Active Memory and Active Focus capabilities and generally scores higher on Meta's agentic and coding evaluations.
Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.
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.
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.
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.
Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.
86M-parameter (mDeBERTa-base) multilingual classifier that detects prompt injection and jailbreak attempts
22M-parameter (DeBERTa-xsmall) English classifier that detects prompt injection and jailbreak attempts
Multimodal Llama 4-based safety classifier for moderating prompts and responses
Open Llama with long-context vision for efficient multimodal agents
Open multimodal Llama for strong reasoning with efficient everyday serving
Popular open Llama workhorse for multilingual chat, coding, and self-hosting
Compact open Llama base model for lightweight and on-device use
Small open Llama base model for lightweight text generation and self-hosting
Open multimodal Llama model for image understanding, captioning, and visual QA
Compact instruction-tuned Llama model for multilingual dialogue and on-device assistants
Large open multimodal Llama model for image reasoning, document QA, and captioning
Small instruction-tuned Llama model for multilingual dialogue and agentic retrieval
Llama 3.1-based safety classifier for moderating prompts and model responses
Compact open Llama model for lightweight chat, drafting, and self-hosting
Open Llama instruction model for multilingual chat, reasoning, and coding
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...
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...
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...
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...
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...
Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...
Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
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No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
No provider description is available for this model yet.
| Model | Creator | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|
| Muse Spark Openmeta/muse-spark-open | 1.04858M | $1.25 | $4.25 | 2026-10-15 | |||
| Muse Wonder Fullmeta/muse-wonder-full | 1.04858M | — | — | 2026-10-12 | |||
| Muse Wondermeta/muse-wonder-1.0 | 1.04858M | $4 | $20 | 2026-10-12 | |||
| Muse Spark 1.3meta/muse-spark-1.3 | 1.04858M | $1.25 | $4.25 | 2026-09-02 | |||
| Muse Glimmer 30Bmeta/muse-glimmer-30b | 131.072K | $0.2 | $0.8 | 2026-08-10 | |||
| Muse Spark 1.2meta/muse-spark-1.2 | 1.04858M | $1.25 | $4.25 | 2026-08-05 | |||
| Muse Spark 1.1meta/muse-spark-1.1 | 1.04858M | $1.25 | $4.25 | 2026-04-08 | |||
| Llama Prompt Guard 2 86Mmeta/llama-prompt-guard-2-86m | 512 | — | — | 2025-04-29 | |||
| Llama Prompt Guard 2 22Mmeta/llama-prompt-guard-2-22m | 512 | $0.03 | $0.03 | 2025-04-29 | |||
| Llama Guard 4 12Bmeta/llama-guard-4-12b | 163.84K | $0.18 | $0.18 | 2025-04-29 | |||
| Llama 4 Scout 17B Instructmeta/llama-4-scout-17b-instruct | 10M | $0.17 | $0.66 | 2025-04-05 | |||
| Llama 4 Maverick 17B Instructmeta/llama-4-maverick-17b-instruct | 1M | $0.14 | $0.59 | 2025-04-05 | |||
| Llama-3.3-70B-Instructmeta/llama-3.3-70b-instruct | 128K | $0.1 | $0.32 | 2024-12-06 | |||
| Llama-3.2-1Bmeta/llama-3.2-1b | 131.072K | — | — | 2024-09-25 | |||
| Llama-3.2-3Bmeta/llama-3.2-3b | 131.072K | — | — | 2024-09-25 | |||
| Llama-3.2-11B-Vision-Instructmeta/llama-3.2-11b-vision-instruct | 128K | $0.055 | $0.055 | 2024-09-25 | |||
| Llama 3.2 1B Instructmeta/llama-3.2-1b-instruct | 131.072K | $0.01 | $0.01 | 2024-09-25 | |||
| Llama-3.2-90B-Vision-Instructmeta/llama-3.2-90b-vision-instruct | 128K | — | — | 2024-09-25 | |||
| Llama 3.2 3B Instructmeta/llama-3.2-3b-instruct | 131.072K | $0.02 | $0.02 | 2024-09-25 | |||
| Llama-Guard-3-8Bmeta/llama-guard-3-8b | 128K | — | — | 2024-07-23 | |||
| Llama-3.1-8B-Instructmeta/llama-3.1-8b-instruct | 128K | $0.02 | $0.05 | 2024-07-23 | |||
| Llama-3.1-70B-Instructmeta/llama-3.1-70b-instruct | 128K | $0.4 | $0.4 | 2024-07-23 | |||
| Meta: Llama Guard 4 12Bmeta-llama/llama-guard-4-12b | 163.84K | $0.18 | $0.18 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 128K | $0.188 | $0.652 | — | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 327.68K | $0.1 | $0.3 | — | |||
| Meta: Llama 3.3 70B Instruct (free)meta-llama/llama-3.3-70b-instruct:free | 65.536K | Free | Free | — | |||
| Meta: Llama 3.3 70B Instructmeta-llama/llama-3.3-70b-instruct | 131.072K | $0.1 | $0.32 | — | |||
| Meta: Llama 3.2 1B Instructmeta-llama/llama-3.2-1b-instruct | 60K | $0.027 | $0.201 | — | |||
| Meta: Llama 3.2 11B Vision Instructmeta-llama/llama-3.2-11b-vision-instruct | 131.072K | $0.345 | $0.345 | — | |||
| Meta: Llama 3.2 3B Instruct (free)meta-llama/llama-3.2-3b-instruct:free | 131.072K | Free | Free | — | |||
| Meta: Llama 3.2 3B Instructmeta-llama/llama-3.2-3b-instruct | 80K | $0.051 | $0.335 | — | |||
| Meta: Llama 3.1 8B Instructmeta-llama/llama-3.1-8b-instruct | 131.072K | $0.05 | $0.08 | — | |||
| Meta: Llama 3.1 70B Instructmeta-llama/llama-3.1-70b-instruct | 131.072K | $0.4 | $0.4 | — | |||
| meta-llama/Meta-Llama-3-8B-Instructmeta-llama/Meta-Llama-3-8B-Instruct | Not documented | — | — | — | |||
| meta-llama/Meta-Llama-3-70B-Instructmeta-llama/Meta-Llama-3-70B-Instruct | Not documented | — | — | — | |||
| meta-llama/Llama-4-Maverick-17B-128E-Instructmeta-llama/Llama-4-Maverick-17B-128E-Instruct | Not documented | — | — | — | |||
| meta-llama/Llama-4-Scout-17B-16E-Instructmeta-llama/Llama-4-Scout-17B-16E-Instruct | Not documented | — | — | — | |||
| meta-llama/Llama-Guard-4-12Bmeta-llama/Llama-Guard-4-12B | Not documented | — | — | — | |||
| meta-llama/Llama-4-Maverick-17B-128Emeta-llama/Llama-4-Maverick-17B-128E | Not documented | — | — | — | |||
| meta-llama/Llama-4-Scout-17B-16Emeta-llama/Llama-4-Scout-17B-16E | Not documented | — | — | — | |||
| meta-llama/Llama-3.2-90B-Vision-Instructmeta-llama/Llama-3.2-90B-Vision-Instruct | Not documented | — | — | — | |||
| meta-llama/Llama-3.3-70B-Instructmeta-llama/Llama-3.3-70B-Instruct | Not documented | — | — | — | |||
| meta-llama/Llama-3.1-70B-Instructmeta-llama/Llama-3.1-70B-Instruct | Not documented | — | — | — | |||
| meta-llama/Llama-3.2-11B-Vision-Instructmeta-llama/Llama-3.2-11B-Vision-Instruct | Not documented | — | — | — | |||
| meta-llama/Llama-3.2-3B-Instruct-QLORA_INT4_EO8meta-llama/Llama-3.2-3B-Instruct-QLORA_INT4_EO8 | Not documented | — | — | — | |||
| meta-llama/Llama-3.2-3B-Instruct-SpinQuant_INT4_EO8meta-llama/Llama-3.2-3B-Instruct-SpinQuant_INT4_EO8 | Not documented | — | — | — | |||
| meta-llama/Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8meta-llama/Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8 | Not documented | — | — | — | |||
| meta-llama/Llama-3.2-1B-Instruct-QLORA_INT4_EO8meta-llama/Llama-3.2-1B-Instruct-QLORA_INT4_EO8 | Not documented | — | — | — | |||
| meta-llama/Llama-Guard-3-11B-Visionmeta-llama/Llama-Guard-3-11B-Vision | Not documented | — | — | — | |||
| meta-llama/Llama-3.2-1Bmeta-llama/Llama-3.2-1B | Not documented | — | — | — |