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GitHub Copilot charges per developer per month. Self-hosted CodeLlama on GigaGPU dedicated servers serves your entire engineering team for a single fixed monthly cost — no per-seat pricing. For teams of 5 or more developers, self-hosting is almost always cheaper. This guide shows exactly where the crossover happens.
CodeLlama (and its successors like DeepSeek Coder, StarCoder 2, and Qwen2.5-Coder) provide code completion, generation, and explanation capabilities that rival Copilot for most use cases. With open-source hosting, you also gain full control over your codebase data.
GitHub Copilot vs Self-Hosted CodeLlama Pricing
GitHub Copilot Individual costs $10/month. Copilot Business costs $19/month per user. Copilot Enterprise costs $39/month per user. These prices multiply linearly — a 50-person team on Business pays $950/month. Self-hosted CodeLlama 34B on a single RTX 6000 Pro 96 GB or 2x RTX 5090 serves the entire team simultaneously for a fixed monthly server cost.
For the general economics of GPU vs API pricing, see our cost per 1M tokens: GPU vs OpenAI analysis.
Cost Comparison by Team Size
| Team Size | Copilot Business ($19/user) | Copilot Enterprise ($39/user) | Self-Hosted CodeLlama 34B (1x RTX 6000 Pro 96 GB) |
|---|---|---|---|
| 5 devs | $95/mo | $195/mo | ~$699/mo (fixed) |
| 10 devs | $190/mo | $390/mo | ~$699/mo (fixed) |
| 20 devs | $380/mo | $780/mo | ~$699/mo (fixed) |
| 37 devs | $703/mo | $1,443/mo | ~$699/mo (fixed) |
| 50 devs | $950/mo | $1,950/mo | ~$699/mo (fixed) |
| 100 devs | $1,900/mo | $3,900/mo | ~$699/mo (fixed) |
| 200 devs | $3,800/mo | $7,800/mo | ~$1,398/mo (2 servers) |
Against Copilot Business, break-even is at roughly 37 developers. Against Copilot Enterprise, break-even drops to approximately 18 developers. For organisations with compliance requirements that mandate Enterprise, self-hosting is cheaper for virtually any team size above 20.
Break-Even Analysis
The break-even depends on which Copilot tier you compare against. For Business ($19/user), a $699/month RTX 6000 Pro server breaks even at 37 developers. For Enterprise ($39/user), break-even drops to 18 developers. If you use the smaller CodeLlama 7B or 13B variants on cheaper hardware (RTX 5090 at ~$199/month), break-even drops to 11 developers against Business or 6 developers against Enterprise.
See our GPU vs API break-even guide for the full methodology.
Annual Savings for Development Teams
| Team Size | Copilot Business Cost | Self-Hosted Cost | Monthly Savings | Annual Savings |
|---|---|---|---|---|
| 50 devs | $950 | $699 | $251 (26%) | $3,012 |
| 100 devs | $1,900 | $699 | $1,201 (63%) | $14,412 |
| 200 devs | $3,800 | $1,398 | $2,402 (63%) | $28,824 |
| 500 devs | $9,500 | $2,097 | $7,403 (78%) | $88,836 |
For a 200-person engineering org on Copilot Enterprise ($7,800/month), switching to self-hosted saves over $76,000 annually. At 500 developers, savings exceed $88,000 per year against Business pricing. For ROI analysis at enterprise scale, see our enterprise AI ROI calculator.
Capability Comparison
GitHub Copilot benefits from deep IDE integration and GitHub context awareness. Self-hosted CodeLlama (and alternatives like DeepSeek Coder V2 or StarCoder 2) provide comparable code completion quality and support integration through the open-source Continue.dev IDE extension, Tabby, or custom LSP servers.
The key advantage of self-hosting: your code never leaves your infrastructure. For regulated industries (finance, healthcare, defence), this is often a hard requirement, not a preference. Explore the options at GigaGPU code model hosting, and see our cheapest GPU for inference guide for hardware choices.
When to Self-Host Code AI
For small teams (under 15 developers) without strict data privacy requirements, Copilot Business is convenient. For mid-size to large engineering teams, especially those with compliance constraints, self-hosted code models on GigaGPU dedicated servers deliver comparable quality at lower cost with full data sovereignty.
Compare the options with our GPU vs API cost comparison tool, or explore the best OpenAI alternatives for code generation workloads.
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