Llama 3.1 405B vs Qwen 2.5-Coder 32B
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 Qwen 2.5-Coder 32B.
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.
Qwen 2.5-Coder 32B
Qwen 2.5-Coder 32B is Alibaba's specialized code generation model built on the Qwen 2.5 architecture, fine-tuned on a massive corpus of code repositories, technical documentation, and programming discussions. It achieves competitive results against GPT-4o and Claude Sonnet on coding benchmarks like HumanEval, MBPP, and LiveCodeBench while supporting a broad range of programming languages from Python and JavaScript to Rust and Go. Its 128K context window enables whole-repository analysis and complex multi-file refactoring tasks.
Technical Specifications
| Specification | Llama 3.1 405B | Qwen 2.5-Coder 32B |
|---|---|---|
| Provider | Meta | Alibaba |
| Context Window | 131,072 tokens | 131,072 tokens |
| Agent Suitability | 90/100 | 89/100 |
| Time to First Token (TTFT) | 550 ms | 260 ms |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-07-23 | 2025-11-12 |
API Pricing Comparison
Input Price per Million Tokens
Llama 3.1 405B
$0.80
Qwen 2.5-Coder 32B
$0.35
Output Price per Million Tokens
Llama 3.1 405B
$0.80
Qwen 2.5-Coder 32B
$0.70
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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
Qwen 2.5-Coder 32B Quirks & Gotchas
- ▸Strong code generation across 40+ languages — excellent for multi-language repos
- ▸Available via Alibaba Cloud API or self-hosted