For reka ai infrastructure and model engineering teams
Reka Flash 3 serving: loading failure or long reasoning request?
Align model revision, engine startup and request lifecycle. Distinguish a slow generation from a process that never became ready.
Free 30-day Team evaluation. No card or automatic subscription. Work email verification required.
Replay a resolved Reka AI workflow incident
Upload your log file. Review the selected evidence and masking, then run diagnosis. Keep the original log for any follow-up questions.
Before uploading, review cloud data handling and local options.
Upload your log file. Large files are processed in your browser. Only selected evidence is submitted when you run diagnosis.
Try Denpex for 30 days. FREE.
No credit card. No automatic subscription. See whether Denpex helps with an incident you already understand.
Start your free 30-day Team evaluation
Up to 50 diagnoses a day for 30 days. Verify your work email to activate an eligible company evaluation, then replay a resolved incident and compare the evidence and next steps with your team's confirmed cause.
What a useful evaluation should establish
Compare one incident your team has already resolved with the first failure, quoted evidence and remaining questions. Begin with this question: Did the serving engine finish loading this revision? Only assign a process, device or recovery state when the submitted evidence establishes it.
Did the serving engine finish loading this revision?
Evidence to compare: Model identity, engine startup output and first worker exception.
The client can fail before the model is ready. Preserve startup evidence separately from the later response code or a wrapper exception.
Was generation active when the caller timed out?
Evidence to compare: Request duration, token progress and the caller deadline.
A reasoning request can continue while a client deadline expires. A timeout alone does not show that the GPU worker failed or justify restarting it.
Does the failure actually establish memory exhaustion?
Evidence to compare: Actual allocation traceback, engine memory profile and generation settings.
Model size is not enough to select a memory remedy. Compare the operation and active workload before changing cache, context or parallelism.
Use Denpex alongside your existing telemetry tools to investigate submitted incident evidence. With monitoring configured on a supported plan, detected failures can trigger alerts and an automatic diagnosis from the captured evidence.
Inside Denpex
See the evidence, not just the claim
Follow the causal chain, inspect the quoted evidence and prepare the next handoff. These actual product captures use founder-account examples and the VS Code extension, with the source identified under each image. Open a capture to inspect it at full size.
Follow the failure through the cascade

Prepare the hardware escalation

Ask for the evidence that is missing

Keep the investigation in the editor
