Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
Issue 30641 is harder because it spans backend configuration discovery, secure secret handling, API/UI state synchronization, deployment variants, and broad regression testing. Issue 33893 is more localized to provider authentication and request-routing logic with focused adapter tests.
}
https://github.com/berriai/litellm/issues/30641 4:1 https://github.com/berriai/litellm/issues/33893

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The left issue is harder because it spans Vertex pass-through routing, request-body model resolution, persisted origin context across asynchronous follow-up calls, configuration gating, and multi-project credential behavior. The right issue is mainly a bounded admin UI and settings/API extension using existing visibility patterns.
}
https://github.com/berriai/litellm/issues/32216 3:1 https://github.com/berriai/litellm/issues/32451

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
#32562 requires cross-path async stream error propagation, protocol-correct terminal events, and regression coverage; #26424 is a localized logging-severity and traceback-handling adjustment.
}
https://github.com/berriai/litellm/issues/32562 5:1 https://github.com/berriai/litellm/issues/26424

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The left issue is harder because it involves provider-specific reasoning-output behavior, model-version compatibility, and validation of silent response degradation across Anthropic integrations. The right issue is a narrower request-parameter translation with a more localized implementation and test surface.
}
https://github.com/berriai/litellm/issues/25965 4:1 https://github.com/berriai/litellm/issues/27453

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
#34384 has no actionable technical specification, so its implementation scope and risk are unbounded; #31336 is a narrowly scoped Helm-chart values/template addition.
}
https://github.com/berriai/litellm/issues/34384 2:1 https://github.com/berriai/litellm/issues/31336

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The left task spans backend integration, external service interaction, model metadata, metric computation, error handling, and propagation across multiple observability adapters. The right task is a localized dashboard taxonomy and form-state correction with comparatively limited regression risk.
}
https://github.com/berriai/litellm/issues/31226 8:1 https://github.com/berriai/litellm/issues/32621

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
#14505 is harder because it requires cross-cutting security-context integration, trusted identity resolution, enforcement against conflicting inputs, provider-specific propagation, and broad regression coverage. #30008 is comparatively localized to configuration plumbing and runtime formatting behavior.
}
https://github.com/berriai/litellm/issues/14505 5:1 https://github.com/berriai/litellm/issues/30008

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
Azure-to-Anthropic compatibility crosses proxy request translation, provider-specific parameter filtering, and integration testing, creating broader uncertainty; the duration rollover issue is a localized calculation fix with targeted regression tests.
}
https://github.com/berriai/litellm/issues/26214 3:1 https://github.com/berriai/litellm/issues/17993

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The right-hand change is harder because it spans request-log data interpretation, cache-aware token and cost presentation, edge-case handling, and regression coverage. The left-hand change is comparatively localized to provider catalog/UI integration with limited behavioral risk.
}
https://github.com/berriai/litellm/issues/32045 4:1 https://github.com/berriai/litellm/issues/34499

Sorting LiteLLM GitHub issues by difficulty to implement. Higher = harder.

{
The left task requires tracing fallback metadata through the Anthropic translation and response layers while preserving compatibility across headers, payloads, streaming, and tests. The right task is primarily an incremental model-registration and capability update within existing image-generation pathways, with narrower integration risk.
}
https://github.com/berriai/litellm/issues/35246 3:1 https://github.com/berriai/litellm/issues/26615