GitHub Copilot is more accessible for small teams or basic needs, starting at $10 per seat. Tabnine’s entry-level plan matches GitHub Copilot’s mid-tier pricing at $39 per seat, but it requires an annual commitment and provides specific infrastructure flexibility.
For enterprise buyers, the choice depends on deployment preferences. Tabnine supports using your own LLM on-premises or via cloud endpoints for both its Code Assistant and Agentic Platform tiers. GitHub Copilot scales based on model complexity and the volume of agent workflows, reaching $100 per seat for its highest tier.
Break-even value per seat
| Plan |
Price / seat / month |
Hours to break even at $50/h |
Hours to break even at $75/h |
Hours to break even at $100/h |
| GitHub Copilot — Pro |
$10 |
0.2 h |
0.1 h |
0.1 h |
| Tabnine Code Assistant — Code Assistant |
$39 |
0.8 h |
0.5 h |
0.4 h |
| GitHub Copilot — Pro+ |
$39 |
0.8 h |
0.5 h |
0.4 h |
| Tabnine Agentic Platform — Agentic Platform |
$59 |
1.2 h |
0.8 h |
0.6 h |
| GitHub Copilot — Max |
$100 |
2.0 h |
1.3 h |
1.0 h |
Break-even hours = seat price ÷ loaded hourly cost. Each seat pays for itself once it saves that much verified time per month.
How do the infrastructure options compare?
Tabnine's $39 and $59 plans are built for organizations requiring high levels of control, offering unlimited usage when integrated with your own LLM on-prem or via a cloud endpoint. Both Tabnine tiers also include IP indemnity as a standard feature. GitHub Copilot focuses on a tiered approach to model access, moving from everyday coding at the $10 level to premium models at the $39 level.
What are the break-even requirements?
The financial hurdle for these tools is low relative to developer compensation. At a loaded cost of $100 per hour, a seat of GitHub Copilot Pro pays for itself in just 6 minutes of saved time per month. Even the most expensive option, GitHub Copilot Max at $100 per month, requires only one hour of saved time to reach a 1:1 return on investment.
To validate this spend, leadership must transition from sentiment-based feedback to time-on-task metrics. By comparing current output against a pre-adoption baseline, you can determine if the 0.1 to 2.0 hours required for break-even are actually being recovered. NetLift provides the framework to measure these efficiencies, ensuring that the move to agentic workflows at higher price points translates into measurable cost-avoidance or increased velocity.
Sources
All pricing on this page comes from official vendor pages: