Claude Haiku 4.5 vs Llama 3.1 405B
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 Claude Haiku 4.5 and Llama 3.1 405B.
Claude Haiku 4.5
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
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.
Technical Specifications
| Specification | Claude Haiku 4.5 | Llama 3.1 405B |
|---|---|---|
| Provider | Anthropic | Meta |
| Context Window | 200,000 tokens | 131,072 tokens |
| Agent Suitability | 87/100 | 90/100 |
| Time to First Token (TTFT) | 180 ms | 550 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-10-15 | 2024-07-23 |
API Pricing Comparison
Input Price per Million Tokens
Claude Haiku 4.5
$1.00
Llama 3.1 405B
$0.80
Output Price per Million Tokens
Claude Haiku 4.5
$5.00
Llama 3.1 405B
$0.80
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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.
Claude Haiku 4.5 Quirks & Gotchas
- ▸Fastest TTFT in the Claude lineup — ideal for real-time chat
- ▸Tool calling limited compared to Sonnet — best for simple classification and routing
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