Enterprise Plans
AI Application Development
AI Translator API
AI SEO/GEO Service
Web Scraping Service
Log in
Llama 3.1 8B VS ChatGPT-4o mini
In the rapidly evolving landscape of Large Language Models (LLMs), choosing between a powerful open-source model and a high-efficiency proprietary one is a common challenge. This analysis provides a deep dive into the Llama 3.1 8B vs. GPT-4o mini comparison, exploring their technical specifications, standardized benchmarks, and real-world performance.
Core Specifications & Hardware Efficiency
When analyzing lightweight AI models, small differences in base specs can lead to significant shifts in deployment costs and user experience. Based on the original analysis in Benchmarks and specs, here is how they stack up:
| Specification | Llama 3.1 8B | ChatGPT-4o mini |
|---|---|---|
| Context Window | 128K | 128K |
| Max Output Tokens | 4K | 16K |
| Knowledge Cutoff | Dec 2023 | Oct 2023 |
| Speed (Tokens/sec) | ~147 | ~99 |
💡 Key Insight: While GPT-4o mini supports longer generation (16K output), Llama 3.1 8B is significantly faster in processing speed, making it ideal for real-time applications where latency is critical.
Industry Standard Benchmarks
Benchmarks provide a standardized way to measure "intelligence" across reasoning, math, and coding. GPT-4o mini generally maintains a lead in cognitive heavy-lifting.
| Benchmark Category | Llama 3.1 8B | GPT-4o mini |
|---|---|---|
| MMLU (General Knowledge) | 73.0 | 82.0 |
| HumanEval (Coding) | 72.6 | 87.2 |
| MATH (Advanced Math) | 51.9 | 70.2 |
Real-World Performance Testing
Pricing & Cost Efficiency
Cost is often the deciding factor for high-volume applications. While input costs are comparable, Llama 3.1 offers better scalability for long-form generation.
| Model | Input (per 1K tokens) | Output (per 1K tokens) |
|---|---|---|
| Llama 3.1 8B | $0.000234 | $0.000234 |
| GPT-4o mini | $0.000195 | $0.0009 |
Final Verdict: Which Should You Choose?
Choose GPT-4o mini if:
- You need complex reasoning and high coding accuracy.
- You require long output lengths (up to 16K tokens).
- You want a highly versatile model for diverse, "smart" agent tasks.
Choose Llama 3.1 8B if:
- Speed and latency are your top priorities.
- You are focused on cost optimization for output tokens.
- You prefer an open-weights ecosystem with high processing throughput.
Frequently Asked Questions
Q1: Which model is better for coding?
A: GPT-4o mini is significantly more capable at coding, scoring 87.2 on HumanEval compared to Llama 3.1 8B's 72.6.
Q2: Is Llama 3.1 8B faster than GPT-4o mini?
A: Yes, in many benchmark environments, Llama 3.1 8B achieves roughly 147 tokens per second, which is about 48% faster than GPT-4o mini's ~99 tokens per second.
Q3: Can these models handle large documents?
A: Both models feature a 128K context window, making them equally capable of "reading" large files, though GPT-4o mini can "write" longer responses.
Q4: Why is Llama 3.1 8B cheaper for output?
A: Llama 3.1 8B is an open-source architecture designed for efficiency. Many providers offer lower output pricing (up to 4x cheaper) compared to GPT-4o mini.