OpenAI o1-mini vs Groq Llama 3.3 70B
Performance benchmarks + pricing comparison — updated April 2026
OpenAI o1-mini
OpenAICost-effective reasoning model. Good for coding tasks that require logical reasoning.
| Input | $1.10/M |
| Output | $4.40/M |
| Context | 128K tokens |
| Best For | Coding logic, debugging, algorithm design |
| Benchmark | 70/100 |
Groq Llama 3.3 70B
GroqLlama 3.3 70B running on Groq's ultra-fast LPU inference. Sub-100ms responses for 70B model.
| Input | $0.590/M |
| Output | $0.790/M |
| Context | 128K tokens |
| Best For | Real-time applications, fast chat, low-latency coding |
Cost Comparison by Scenario
Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.
| Scenario | OpenAI o1-mini | Groq Llama 3.3 70B | Savings |
|---|---|---|---|
| Small Script (1K lines) | $0.17 | $0.04 | Groq Llama 3.3 70B saves $0.13 (74%) |
| Medium Feature (10K lines) | $1.27 | $0.36 | Groq Llama 3.3 70B saves $0.90 (71%) |
| Large Project (50K lines) | $6.33 | $1.82 | Groq Llama 3.3 70B saves $4.50 (71%) |
| Code Review (5K lines) | $0.30 | $0.12 | Groq Llama 3.3 70B saves $0.18 (59%) |
Verdict
Groq Llama 3.3 70B wins on both price and performance — $0.590/M input with a benchmark score of N/A/100.
For most developers, this is the clear choice between these two models.
Compare with Other Models
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