Llama 3.2 90B 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.
- Parameters
- 90B
- Context length
- 128K
- Modality
- text, vision
- Released
- 2024-09-25
Memory & hardware
- VRAM (fp16)
- 180 GB
- VRAM (Q4)
- 54 GB
- Recommended
- 2× A100 80GB or 1× H200
- Quantizations
- fp16, q8_0, q5_k_m, q4_k_m
License: Llama 3 Community License
- SPDX
- —
- Commercial use
- Yes
- Modification
- Yes
- Redistribution
- Yes
Benchmarks
Hosted inference pricing
USD per million tokens.
| Provider | Input | Output | |
|---|---|---|---|
| groqCheapest | $0.90 | $0.90 |
Run it yourself
Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.
ollama run llama3.2:90b
vllm serve meta-llama/Llama-3.2-90B-Vision-Instruct
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-90B-Vision-Instruct")
model = AutoModelForCausalLM.from_pretrained(
"meta-llama/Llama-3.2-90B-Vision-Instruct", device_map="auto", torch_dtype="auto"
)meta-llama/Llama-3.2-90B-Vision-Instruct Related models
Same family or similar size — useful when shopping around.
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- License
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