Best for
- Developers
- Enterprises
- Fine-tuners
L4
Open-weight LLMs
Overview - Llama 4
Meta's open-weight multimodal MoE family (Scout, Maverick) with very long context.
Llama 4 moved Meta's family to mixture-of-experts with native image input and million-token-class context on Scout. Widely supported by every local runner and cloud host; the Llama licence allows commercial use with some limits.
Difficulty: IntermediatePlatform: LocalPricing: FreeReleased: 2025-04
Open WeightMultimodalMeta
What this tool is used for
Llama 4 is best used as a practical helper for multimodal assistants, long-document qa, fine-tuned domain models. It is useful when you want to move from rough ideas to high-quality drafts quickly, then refine with human review before publishing or sharing.
Use this when
- You want the broadest ecosystem support
- You need image + text locally
- You fine-tune for your domain
Not ideal for
- Very small devices
Example tasks
- Multimodal assistants
- Long-document QA
- Fine-tuned domain models
Limitations / things to watch
- MoE sizes need lots of RAM
- Licence has usage thresholds
How this compares to similar tools
Llama 4 sits in the same category as Qwen 3 and DeepSeek R1 / V3. Use Llama 4 when its output style and workflow fit your team, but compare pricing limits, integrations, and review requirements before standardizing.