Llama 3.1 405B vs UI-TARS 7B
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Llama 3.1 405B and UI-TARS 7B.
Llama 3.1 405B
Llama 3.1 405B is Meta's largest open-weight language model and one of the most capable openly available models in the world. With 405 billion parameters, it achieves performance competitive with GPT-4 and Claude Opus across benchmarks spanning general knowledge, mathematics, coding, and multilingual tasks. Llama 3.1 405B is released under Meta's custom commercial license, supporting broad use cases including deployment via major cloud providers (AWS, GCP, Azure) and self-hosted inference with multi-GPU configurations.
UI-TARS 7B
UI-TARS-1.5 is a multimodal vision-language agent optimized for GUI-based environments, including desktop interfaces, web browsers, mobile systems, and games. Built by ByteDance, it builds upon the UI-TARS framework with reinforcement...
Technical Specifications
| Specification | Llama 3.1 405B | UI-TARS 7B |
|---|---|---|
| Provider | Meta | ByteDance |
| Context Window | 131,072 tokens | 128,000 tokens |
| Agent Suitability | 90/100 | N/A |
| Time to First Token (TTFT) | 550 ms | N/A |
| Deployment Model | self hostable | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-07-23 | 2025-07-22 |
API Pricing Comparison
Input Price per Million Tokens
Llama 3.1 405B
$0.80
UI-TARS 7B
$0.10
Output Price per Million Tokens
Llama 3.1 405B
$0.80
UI-TARS 7B
$0.20
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Llama 3.1 405B Quirks & Gotchas
- ▸Massive model — requires 8× A100 80GB for FP16 inference
- ▸Available via Together AI, Fireworks, and Bedrock as managed API
UI-TARS 7B Quirks & Gotchas
No developer gotchas reported.