Vision

Larger vision-language Llama variant, competitive with the proprietary multimodal frontier on standard image-understanding benchmarks. Drops in as a vision upgrade where 11B isn't sharp enough. Requires substantial GPU memory in fp16; most teams will run it quantized or on multi-GPU. A natural pairing with retrieval pipelines that fetch image-rich chunks alongside text.

Context

128K

License

llama-3

VRAM Q4

54 GB

Vision-language variant of Yi 34B. Image-text reasoning via an MLP adapter on a CLIP encoder. Useful for bilingual EN/中 multimodal workloads where the major Western vision-language models underperform on Chinese text in images.

Context

4K

License

apache-2-0

VRAM Q4

20.4 GB

Meta's April 2025 mixture-of-experts release. 17B active parameters across 16 experts (109B total). Natively multimodal with an unprecedented 10M-token context window — a leap far beyond Llama 3's 128K. Scout was designed to run on a single GPU at Q4 while beating Llama 3.3 70B on reasoning and multilingual benchmarks. The Llama 4 licence tightened acceptable-use provisions vs Llama 3.

Context

10.0M

License

llama-4

VRAM Q4

10.2 GB

Larger Llama 4 sibling of Scout — 17B active across 128 experts (400B total). 1M-token native context. Positioned as GPT-4o-class on chat and reasoning while remaining tractable on a single high-end host at fp8. Multimodal from the ground up; instruction-tuned by Meta with a heavier synthetic-data pipeline than Llama 3.

Context

1.0M

License

llama-4

VRAM Q4

10.2 GB

Llama 3's first vision-language model. Image understanding via a separately-trained ViT adapter bolted onto Llama 3 weights. Useful for OCR-adjacent workloads, document understanding, and image captioning at a permissive licence. The 11B size makes it cheap to host. Combined with the 128K text context, it handles long PDF-with-images workflows comfortably on a single 4090.

Context

128K

License

llama-3

VRAM Q4

6.6 GB