OpenAI o1-mini vs Databricks Llama 3.1 405B

Performance benchmarks + pricing comparison — updated April 2026

OpenAI o1-mini

OpenAI

Cost-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

Databricks

Meta's 405B model hosted on Databricks. Largest open-weight model available for enterprise use.

Input	$5.00/M
Output	$15.00/M
Context	128K tokens
Best For	Enterprise AI, complex reasoning, custom fine-tuning

Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.

Scenario	OpenAI o1-mini	Databricks Llama 3.1 405B	Savings
Small Script (1K lines)	$0.17	$0.63	OpenAI o1-mini saves $0.45 (73%)
Medium Feature (10K lines)	$1.27	$4.75	OpenAI o1-mini saves $3.48 (73%)
Large Project (50K lines)	$6.33	$23.75	OpenAI o1-mini saves $17.42 (73%)
Code Review (5K lines)	$0.30	$1.25	OpenAI o1-mini saves $0.95 (76%)

OpenAI o1-mini wins on both price and performance — $1.10/M input with a benchmark score of N/A/100.

For most developers, this is the clear choice between these two models.

Anthropic's balanced model for coding and general tasks. Best price-performance ratio in the Claude family.

Anthropic's most powerful model. Best for complex reasoning and challenging coding tasks.

Previous generation Sonnet. Still excellent for coding tasks at the same price point.

Fast, cost-effective model for high-volume tasks. Great for code review and simple queries.

First generation Opus. Highest reasoning capability in the Claude 3 family.

First generation Sonnet. Balanced performance for general tasks.