Banana.dev officially ceased operations on March 31, 2024, turning off its API servers and ending its run as a serverless GPU provider. If you are reading this in 2026, the service is long dead. You cannot deploy models, you cannot generate API keys, and the dashboard is gone. While it historically offered a compelling "one-line deploy" experience for machine learning models, its business model eventually collapsed under the weight of low margins and high infrastructure costs in the GPU resale market.
Before its shutdown, Banana was a favorite among indie developers for its Potassium SDK, which allowed you to define an inference pipeline in a single Python file (app.py) and deploy it with a git push. It handled the containerization, cold starts (typically around 2 seconds), and auto-scaling to zero. For a time, it was the fastest way to get a custom Bert or Stable Diffusion model behind a REST API without touching Kubernetes. A typical workload of 10,000 SDXL images might have cost $20-30 on Banana, comparable to raw instance costs on AWS but with significantly less headache.
The service’s demise serves as a case study in the economics of "wrapping" cloud providers. Banana rented GPUs from upstream providers (like CoreWeave or AWS) and resold them. When GPU scarcity hit and margins tightened, the unit economics stopped making sense. The founder, Erik Dunteman, was transparent about this, noting that the "reseller" model for serverless GPUs is incredibly difficult to sustain against first-party providers.
If you are maintaining a legacy codebase that uses the banana-dev Python package or the Potassium framework, you must migrate immediately. The spiritual successor for the "code-as-infra" workflow is Modal, which offers a similar (but more powerful) Python-native experience. for those who preferred the container-based approach, RunPod Serverless is the direct functional equivalent. Do not attempt to use Banana for any new or existing workloads.
Pricing
There is no active pricing because the service is defunct. Historically, Banana charged strictly for usage: roughly $0.0002 to $0.001 per second depending on the GPU (T4 to A100), with no cost for idle time (scale-to-zero).
The "free tier" was essentially a small credit grant for new accounts, but the platform eventually struggled to support free usage due to the high cost of reserving GPU capacity. In 2026 terms, the cost to run Banana is effectively infinite purely in terms of opportunity cost and wasted engineering time. Use RunPod (starting at ~$0.20/hr for serverless) or Modal for transparent, sustainable pricing models.
Technical Verdict
The technology was excellent for its time but is now obsolete. The Potassium framework was a clever abstraction that simplified creating an inference server, but it is no longer maintained. Documentation is offline or archived, and the API endpoints return 404s or connection errors. Relying on any part of the Banana stack today guarantees failure. Migration to Modal or RunPod is not just recommended; it is mandatory.
Quick Start
# SERVICE IS DEFUNCT (March 2024). Do not use.
import banana_dev as banana
# This code will hang or error out
api_key = "YOUR_API_KEY"
model_key = "YOUR_MODEL_KEY"
out = banana.run(api_key, model_key, {"prompt": "Hello world"})
print(out)Watch Out
- The API servers are permanently offline (since March 31, 2024).
- The Potassium GitHub repository is archived and unmaintained.
- Any legacy credits or balances are forfeit and inaccessible.
- Documentation links now mostly redirect to 404s or blog posts about the shutdown.