Llama 3.1 405B vs Qwen3.5 397B A17B
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 Qwen3.5 397B A17B.
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.
Qwen3.5 397B A17B
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
Technical Specifications
| Specification | Llama 3.1 405B | Qwen3.5 397B A17B |
|---|---|---|
| Provider | Meta | Alibaba |
| Context Window | 131,072 tokens | 256,000 tokens |
| Agent Suitability | 90/100 | N/A |
| Time to First Token (TTFT) | 550 ms | N/A |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-07-23 | 2026-02-16 |
API Pricing Comparison
Input Price per Million Tokens
Llama 3.1 405B
$0.80
Qwen3.5 397B A17B
$0.39
Output Price per Million Tokens
Llama 3.1 405B
$0.80
Qwen3.5 397B A17B
$2.45
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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
Qwen3.5 397B A17B Quirks & Gotchas
No developer gotchas reported.