Chameleon Models by AI at Meta
About
The Chameleon family of large language models (LLMs), developed by Meta AI, marks a significant advancement in multimodal AI. These models feature an innovative early-fusion architecture that integrates both images and text seamlessly, allowing simultaneous processing and generation in any sequence. Unlike traditional models that handle modalities separately, Chameleon holistically combines visual and textual data from the beginning, which enhances its understanding of complex inputs. This architecture facilitates tasks like image captioning, visual question answering, and mixed-modal generation. A notable innovation is its vector quantization approach, enabling image tokenization compatible with transformer text processing. The models are accessible in various sizes, including the publicly available 7B and 34B parameter versions, and have outperformed other leading models like Google's Gemini Pro and OpenAI's GPT-4V in specific tasks. Additionally, another version of Chameleon, developed by UCLA and Microsoft, focuses on compositional reasoning with integrated tool usage, achieving state-of-the-art results in benchmarks such as ScienceQA.
Current Variants
Use-when guidance is derived from seed capabilities, context, release, and replacement fields.
Use when the workload needs 4k context and 34B parameters.
Use when the workload needs 4k context and 7B parameters.
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| Chameleon 34B | Use when the workload needs 4k context and 34B parameters. | 2024-06 | 4k context34B parameters | Current |
| Chameleon 7B | Use when the workload needs 4k context and 7B parameters. | 2024-06 | 4k context7B parameters | Current |
Release Timeline
1 release groupSpecifications(2 models)
| Model | Released | Context | Parameters |
|---|---|---|---|
| Chameleon 34B | 2024-06 | 4k | 34B |
| Chameleon 7B | 2024-06 | 4k | 7B |
Frequently Asked Questions
- What is Chameleon used for?
- Chameleon is used for coding. The family description and listed model capabilities point to those workloads as the best fit.
- How does Chameleon compare to Llama Guard?
- Chameleon by AI at Meta is strongest where you need coding, while Llama Guard by AI at Meta is the closest related family to check for safety. Chameleon has 2 listed variants and reaches up to 4k context, while Llama Guard reaches up to 164k context, so compare the specs and pricing tables before choosing a production model.
- Which Chameleon model should I use?
- If price is the main constraint, use the pricing table first because Chameleon does not have complete provider pricing in the local data. For the most capable/latest local choice, evaluate Chameleon 34B with 4k context.
