OpenAI o1 vs Llama 4 Scout
Performance benchmarks + pricing comparison — updated April 2026
OpenAI o1
OpenAIReasoning model optimized for complex problem-solving. Excels at math, science, and advanced coding.
| Input | $15.00/M |
| Output | $60.00/M |
| Context | 200K tokens |
| Best For | Complex math, advanced coding, scientific reasoning |
| Benchmark | 83/100 |
Llama 4 Scout
MetaMeta's Llama 4 mid-tier multimodal model. Native multimodal with efficient inference.
| Input | $0.200/M |
| Output | $0.800/M |
| Context | 10M tokens |
| Best For | Multimodal applications, image + text tasks |
Cost Comparison by Scenario
Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.
| Scenario | OpenAI o1 | Llama 4 Scout | Savings |
|---|---|---|---|
| Small Script (1K lines) | $2.32 | $0.03 | Llama 4 Scout saves $2.29 (99%) |
| Medium Feature (10K lines) | $17.25 | $0.23 | Llama 4 Scout saves $17.02 (99%) |
| Large Project (50K lines) | $86.25 | $1.15 | Llama 4 Scout saves $85.10 (99%) |
| Code Review (5K lines) | $4.13 | $0.06 | Llama 4 Scout saves $4.07 (99%) |
Verdict
Llama 4 Scout wins on both price and performance — $0.200/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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