GPT-4o mini vs Llama 3.1 8B
Performance benchmarks + pricing comparison — updated April 2026
GPT-4o mini
OpenAIAffordable small model. Fast and cost-effective for high-volume coding tasks.
| Input | $0.150/M |
| Output | $0.600/M |
| Context | 128K tokens |
| Best For | High-volume tasks, simple coding, cost-sensitive projects |
| Benchmark | 58/100 |
Llama 3.1 8B
MetaMeta's smallest Llama 3.1 model. Open weights, deploy anywhere. Great for self-hosted applications.
| Input | $0.050/M |
| Output | $0.100/M |
| Context | 128K tokens |
| Best For | Self-hosted AI, fine-tuning, budget applications |
Cost Comparison by Scenario
Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.
| Scenario | GPT-4o mini | Llama 3.1 8B | Savings |
|---|---|---|---|
| Small Script (1K lines) | $0.02 | <$0.01 | Llama 3.1 8B saves $0.02 (81%) |
| Medium Feature (10K lines) | $0.18 | $0.04 | Llama 3.1 8B saves $0.15 (80%) |
| Large Project (50K lines) | $0.92 | $0.19 | Llama 3.1 8B saves $0.73 (80%) |
| Code Review (5K lines) | $0.05 | $0.01 | Llama 3.1 8B saves $0.04 (76%) |
Verdict
Llama 3.1 8B wins on both price and performance — $0.050/M input with a benchmark score of N/A/100.
For most developers, this is the clear choice between these two models.
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