For most Indian startups doing fewer than 50 million tokens per month, a commercial API (GPT-4o mini, Gemini Flash, DeepSeek Flash) is almost certainly cheaper than self-hosting after you account for infrastructure management time. Above roughly 200 million tokens per month, the break-even flips — and if data residency under the DPDP Act matters for your use case, self-hosting on an Indian GPU cloud may be the only compliant option regardless of volume.
The break-even calculation
GPT-4o mini costs $0.15 per million input tokens and $0.60 per million output tokens. At a typical 3:1 input-to-output ratio, blended cost is approximately $0.26/million tokens. An A100 80GB on NeevCloud at ₹126/hr (~$1.31/hr) can serve Llama 3.3 70B at roughly 800–1,200 tokens per second sustained throughput at FP16. Over a month (730 hours), that GPU costs about ₹92,000 ($955) and can process approximately 1.5–2 billion tokens assuming 40% utilization. At $0.26/million blended API cost, 2 billion tokens would cost $520 — cheaper than the GPU. At 80% utilization however, the GPU processes 3–4B tokens for the same ₹92,000, while 4B tokens at $0.26/million would cost $1,040. The break-even is around 150–200M tokens/month at 40% GPU utilization.
What the math misses
Infrastructure cost is not just the GPU bill. You need: engineering time to deploy and tune vLLM or TGI, handle failures, and manage updates (budget 10–20% of a senior engineer's time); storage for model weights (Llama 3.3 70B is 140GB at FP16); network egress if your users are distributed; and a separate smaller GPU or CPU for embedding generation. Add these and the true break-even moves to 300–500M tokens/month for most teams. Below that, APIs win on total cost of ownership even if raw per-token math looks close.
When self-hosting is mandatory regardless of cost
If you are processing Indian personal data — user conversations, health records, financial information — under the DPDP Act 2023, data transfer to foreign servers requires a legal basis. For most B2C Indian applications, routing user data through OpenAI's US servers or DeepSeek's China servers without explicit consent and cross-border transfer agreements creates compliance exposure. Self-hosting Llama 3.3 70B, Mistral, or DeepSeek R1 on E2E Networks or NeevCloud keeps data in India, eliminates the cross-border transfer question, and gives you full audit control over what the model sees. At that point, the build-vs-buy decision is less about cost and more about what your legal team requires.
Recommended approach for Indian teams
Start on a commercial API. Use GPT-4o mini or Gemini Flash or DeepSeek Flash while validating your product. Track your monthly token volume. When you cross 100M tokens/month, run a 30-day parallel test: same workload, same quality benchmarks, one API and one vLLM deployment on a NeevCloud A100. Measure actual throughput, latency, and quality side-by-side. If your DPDP compliance posture requires India-only data processing, start the self-hosting evaluation earlier — the compliance benefit alone can justify the switch before the cost math fully flips.