Llama 3.1 405B vs Yi-Lightning
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 Yi-Lightning.
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.
Yi-Lightning
Yi-Lightning is 01.AI's (ιΆδΈδΈη©) fastest and most cost-efficient model, purpose-built for high-throughput production workloads. It delivers competitive performance against GPT-4o-mini and Claude Haiku at a fraction of the cost, with exceptional bilingual Chinese-English capabilities. Yi-Lightning excels at classification, entity extraction, summarization, and high-frequency API tasks where latency and cost-per-call are critical constraints.
Technical Specifications
| Specification | Llama 3.1 405B | Yi-Lightning |
|---|---|---|
| Provider | Meta | 01.AI |
| Context Window | 131,072 tokens | 131,072 tokens |
| Agent Suitability | 90/100 | 82/100 |
| Time to First Token (TTFT) | 550 ms | 120 ms |
| Deployment Model | self hostable | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-07-23 | 2025-10-01 |
API Pricing Comparison
Input Price per Million Tokens
Llama 3.1 405B
$0.80
Yi-Lightning
$0.15
Output Price per Million Tokens
Llama 3.1 405B
$0.80
Yi-Lightning
$0.30
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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
- βΈMassive model β requires 8Γ A100 80GB for FP16 inference
- βΈAvailable via Together AI, Fireworks, and Bedrock as managed API
Yi-Lightning Quirks & Gotchas
- βΈBest cost-efficiency for high-volume bilingual applications
- βΈSelf-hostable via Ollama β excellent open-weight option for Asian-language pipelines