Compare Claude 3.5 Haiku and LLaMA 3 8B. Find out which model is better for your specific use case and requirements.
| Feature | Claude 3.5 Haiku | LLaMA 3 8B |
|---|---|---|
| Provider | Anthropic | Meta |
| Model Type | text | text |
| Context Window | 200,000 tokens | 8,192 tokens |
| Input Cost | $0.80/ 1M tokens | N/A |
| Output Cost | $4.00/ 1M tokens | N/A |
1. Intelligence & Benchmark Performance
2. Coding Strength
Scores 40.6% on SWE-bench Verified, outperforming:
Excellent for engineering assistants, agent coding tasks, and bug fixing.
3. Speed & Latency
4. Tool Use & Instruction Following
5. Best Use Cases
LLaMA 3 8B is a highly efficient, small-scale open-source model perfect for simpler tasks and edge devices. It's great for applications like chatbots, text classification, and sentiment analysis where resource constraints are a concern. Its speed and small footprint make it easy to deploy.
Discover AI prompts that work great with these models. Use them to build powerful AI tools on Appaca.
Build a video marketing strategy that uses storytelling to show how your USP transforms persona challenges into outcomes.
Create professional LinkedIn posts that establish thought leadership, drive engagement, and grow your network.
Craft a case study outline that proves your USP by showing how a customer like your persona overcame their challenges.
Generate three distinct objection-handling scripts for real estate cold calls: empathetic, data-driven, and direct—plus follow-up questions and next steps.
Design a website quiz that helps your persona self-diagnose challenges and recommends next steps aligned to your USP.
Create a website content hub that centralizes resources related to persona challenges and positions your USP as the solution.
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