Estimate OCI Functions costs based on invocations, memory, and execution duration.
Last verified: May 2026
Output will appear here...The estimator computes OCI Functions monthly cost as: (invocations × $0.00000020) + (GB-seconds × $0.0000020), with 2M invocations and 400K GB-seconds subtracted as free tier. GB-seconds = (memory in GB × execution duration in seconds × invocations). Output shows comparison to equivalent always-on compute (1 OCPU compute instance running 730 hours) to surface the threshold where serverless wins on cost.
OCI Functions is a serverless compute platform based on the open-source Fn Project that lets you run code without provisioning servers. Pricing is based on function invocations and the compute time measured in GB-seconds (memory allocated multiplied by execution duration). OCI Functions includes a generous free tier of 2 million invocations and 400,000 GB-seconds per month. This cost estimator calculates monthly expenses based on your expected invocation volume, average execution duration, and memory allocation per function, helping you understand when serverless is more economical than always-on compute.
Your team is comparing OCI Functions vs an always-on 1-OCPU compute instance for a webhook receiver handling 100K invocations/month at 200ms avg duration with 256 MB memory. Functions cost: 100K invocations × $0.0000002 = $0.02 + (100K × 0.25 GB × 0.2s = 5K GB-s, all in free tier) = $0.02/month. Compute instance: $25/month always-on. Functions wins by 1000x for this workload pattern.
OCI Functions' 2M free invocations/month is 2x AWS Lambda's 1M free. For low-traffic webhooks and event handlers, OCI Functions can effectively be free where Lambda would start charging. For greenfield serverless work on OCI, this matters.
Memory allocation directly determines CPU and price. Don't blindly set 1024 MB if your function only needs 256 MB — you're paying 4x more. Profile actual memory usage with OCI Logging and right-size. The free tier covers most lightweight functions entirely.
OCI Functions cold start times are competitive with AWS Lambda (~100ms-1s for typical functions). For latency-sensitive workloads, deploy to a region close to consumers and consider provisioning warm functions via scheduled keep-alive invocations from OCI Scheduler.
Both charge per invocation and per GB-second of compute time. OCI Functions includes 2 million free invocations and 400,000 GB-seconds per month, comparable to AWS Lambda's 1 million free invocations and 400,000 GB-seconds. Per-invocation and per-GB-second rates are similar, but OCI's advantage is the higher free invocation count and the absence of data transfer charges within the same region. For high-volume workloads, the pricing difference is usually marginal.
The three biggest cost drivers are invocation count, memory allocation, and execution duration. Memory is the most impactful because it directly multiplies the GB-second calculation — a function running with 1024 MB for 1 second costs twice as much as one running with 512 MB for 1 second. Optimizing execution duration through code performance improvements and right-sizing memory allocation are the most effective cost reduction strategies.
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