Llama 3.1 405BvsLlama 3.2 90B Vision
Meta AI vs Meta AI — Side-by-side model comparison
Head-to-Head Comparison
| Metric | Llama 3.1 405B | Llama 3.2 90B Vision |
|---|---|---|
| Provider | Meta AI | Meta AI |
| Arena Rank | #9 | #11 |
| Context Window | 128K | 128K |
| Input Pricing | Free (open)/1M tokens | Free (open)/1M tokens |
| Output Pricing | Free (open)/1M tokens | Free (open)/1M tokens |
| Parameters | 405B | 90B |
| Open Source | Yes | Yes |
| Best For | Complex reasoning, coding, multilingual tasks | Image understanding, visual QA, multimodal tasks |
| Release Date | Jul 23, 2024 | Sep 25, 2024 |
Llama 3.1 405B
Llama 3.1 405B, developed by Meta AI, is the largest open-source language model with 405 billion parameters and a 128K token context window. The model rivaled GPT-4-class performance on many benchmarks at the time of its release, representing one of the most ambitious open-source AI projects in history. Training required massive computational resources, but Meta open-sourced all weights, enabling the global research community to study, fine-tune, and deploy it freely. Llama 3.1 405B requires multiple high-end GPUs for inference, limiting deployment to organizations with substantial compute infrastructure. It supports multilingual tasks, advanced reasoning, and tool use. Llama 3.1 405B ranks #9 on the Chatbot Arena leaderboard, confirming that open-source models can compete at the frontier of AI capability when sufficient resources are invested in training.
Llama 3.2 90B Vision
Llama 3.2 90B Vision, developed by Meta AI, is a multimodal open-source model with 90 billion parameters and a 128K token context window. The model processes both text and images, enabling visual question answering, document understanding, chart analysis, and image-grounded reasoning tasks. It represents Meta's first open-source model with vision capabilities, extending the Llama family beyond text-only processing. The vision encoder integrates seamlessly with the language model, producing coherent responses that reference visual elements accurately. Free and open-source, it can be deployed on enterprise GPU infrastructure for privacy-sensitive visual AI applications. Llama 3.2 90B Vision ranks #11 on the Chatbot Arena leaderboard, making it one of the highest-ranked open-source multimodal models available and a strong alternative to proprietary vision-language systems.
Key Differences: Llama 3.1 405B vs Llama 3.2 90B Vision
Llama 3.1 405B ranks higher in arena benchmarks (#9) indicating stronger overall performance.
Llama 3.1 405B has 405B parameters vs Llama 3.2 90B Vision's 90B, which affects inference speed and capability.
When to use Llama 3.1 405B
- +You need the highest quality output based on arena rankings
- +Your use case involves complex reasoning, coding, multilingual tasks
When to use Llama 3.2 90B Vision
- +Your use case involves image understanding, visual qa, multimodal tasks
The Verdict
Llama 3.1 405B wins our head-to-head comparison with 2 out of 5 category wins. It's the stronger choice for complex reasoning, coding, multilingual tasks, though Llama 3.2 90B Vision holds an edge in image understanding, visual qa, multimodal tasks.
Last compared: April 2026 · Data sourced from public benchmarks and official pricing pages