Google Colab Pro is the cheap entry point for notebook-based AI work. For production serving, the trade-offs become expensive. A dedicated RTX 5060 Ti 16GB from our UK dedicated hosting is the next-step platform when Colab starts to bite.
Contents
- Colab Pro plans
- Colab limits vs dedicated
- GPU variance and compute units
- Cost comparison at real usage
- When to transition
Colab Pro plans
Colab Pro sits around $10-12/month and Pro+ at roughly £42/month (~$50). Both sell “compute units” that ration GPU time against a pool. Enterprise comes in considerably higher but still shares the same preemptible architecture.
Colab limits vs dedicated
| Dimension | Colab Pro+ (~£42/mo) | 5060 Ti dedicated (~£300/mo) |
|---|---|---|
| GPU type | T4 / L4 / A100 assigned at random | Fixed RTX 5060 Ti 16GB Blackwell |
| Session timeout | ~24h max, often shorter | None – always on |
| Idle disconnect | ~90 min inactivity | N/A |
| Compute unit throttling | Yes – hard quota | No throttling |
| Persistent public endpoint | No – ephemeral URLs | Yes – dedicated IP |
| Root / systemd | No | Yes |
| Persistent storage | Google Drive mount only | Full NVMe local |
| UK data residency | No | Yes |
| Concurrent requests | Single-user notebook | 32+ concurrent batched |
GPU variance and compute units
Colab Pro+ gives ~500 compute units/month. A single A100 session burns ~13 units/hour; L4 sessions around 5. That caps you at roughly 38 hours of A100 time or 100 hours of L4 – less than half a month of continuous use. The assigned GPU also varies by availability – your code may run 3x slower overnight simply because Colab handed you a T4 instead of an L4.
- Your benchmarks are not reproducible between sessions.
- You cannot run a 24/7 API endpoint without hacky keep-alive tricks.
- Models must be reloaded on every session start (often 2-5 minutes of cold start).
Cost comparison at real usage
| Workload | Colab Pro+ | 5060 Ti dedicated | Verdict |
|---|---|---|---|
| 1 developer, ~40h/month | £42 + frustration | £300 | Colab wins on pure cost |
| 3 developers, ~120h/month | 3× £42 = £126 + runs out | £300 | Dedicated competitive |
| Production 24/7 inference API | Impossible reliably | £300 | Dedicated only option |
| Nightly batch 200M tokens | Out of units day 5 | £300 | Dedicated only |
When to transition
Transition from Colab to dedicated when any of the following is true: you need an always-on API endpoint, you are running nightly batch jobs that exceed compute units, multiple engineers are hitting the same quota, you need deterministic benchmarks, or UK data residency is on your compliance list. A 5060 Ti makes an ideal first production GPU because the cost step is digestible and concurrency capacity is real. See also 5060 Ti for startup MVP.
Graduate from Colab notebooks to production
Always-on Blackwell 16GB, root access, no session timeouts. UK dedicated hosting.
Order the RTX 5060 Ti 16GBSee also: for startup MVP, concurrent users, break-even calculator, FP8 deployment.
