GPT-4o vs Llama 3.3 70B
Performance benchmarks + pricing comparison — updated April 2026
GPT-4o
OpenAIOpenAI's flagship multimodal model. Strong coding and reasoning at competitive pricing.
| Input | $2.50/M |
| Output | $10.00/M |
| Context | 128K tokens |
| Best For | General coding, multimodal tasks, chatbots |
| Benchmark | 75/100 |
Llama 3.3 70B
MetaMeta's open-weight 70B model. Strong coding and general capability, widely supported across AI platforms.
| Input | $0.250/M |
| Output | $1.00/M |
| Context | 128K tokens |
| Best For | Self-hosted deployments, cost-effective coding, custom fine-tuning |
Cost Comparison by Scenario
Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.
| Scenario | GPT-4o | Llama 3.3 70B | Savings |
|---|---|---|---|
| Small Script (1K lines) | $0.41 | $0.04 | Llama 3.3 70B saves $0.37 (90%) |
| Medium Feature (10K lines) | $3.06 | $0.29 | Llama 3.3 70B saves $2.77 (91%) |
| Large Project (50K lines) | $15.31 | $1.44 | Llama 3.3 70B saves $13.88 (91%) |
| Code Review (5K lines) | $0.78 | $0.07 | Llama 3.3 70B saves $0.71 (91%) |
Verdict
Llama 3.3 70B wins on both price and performance — $0.250/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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