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

{
The right issue is harder because it requires callback compatibility across distinct response schemas, token accounting, content extraction, and regression coverage; the left issue is comparatively localized URL routing and configuration propagation.
}
https://github.com/berriai/litellm/issues/29575 3:1 https://github.com/berriai/litellm/issues/30217

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

{
The right-hand issue is harder because it requires provider-specific request translation, validation against AWS Converse behavior, and regression coverage across caching variants. The left-hand issue is comparatively localized to model-key preservation and pricing metadata propagation in the UI path.
}
https://github.com/berriai/litellm/issues/34248 3:1 https://github.com/berriai/litellm/issues/27612

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

{
12875 requires tracing configuration precedence, persistence, startup synchronization, and rollout behavior across proxy state and storage, with substantial regression risk; 30657 is comparatively localized provider/model routing work with focused tests.
}
https://github.com/berriai/litellm/issues/12875 4:1 https://github.com/berriai/litellm/issues/30657

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

{
The right issue is harder because it spans configuration persistence, runtime loading, and guardrail behavior across multiple execution paths, with compatibility and regression-testing risk. The left issue appears localized to endpoint construction and targeted coverage.
}
https://github.com/berriai/litellm/issues/30008 3:1 https://github.com/berriai/litellm/issues/25748

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

{
The right issue is harder because it requires redesigning failure-safe queue and persistence semantics, coordinating retries, locking, recovery, and regression coverage. The left issue is comparatively localized to input normalization and provider-specific translation with focused tests.
}
https://github.com/berriai/litellm/issues/33873 4:1 https://github.com/berriai/litellm/issues/27276

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

{
The right-side task requires coordinated schema normalization across API variants, provider compatibility handling, and broader regression coverage. The left-side task is narrower, mainly involving validation or normalization of outbound metadata values, with comparatively limited behavioral surface area.
}
https://github.com/berriai/litellm/issues/27276 3:1 https://github.com/berriai/litellm/issues/27458

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

{
The streaming-cost issue is harder because it spans provider response parsing, stream aggregation, usage-schema propagation, and compatibility tests, whereas the metadata issue is more likely isolated to the Anthropic request path and field propagation.
}
https://github.com/berriai/litellm/issues/16021 3:1 https://github.com/berriai/litellm/issues/28082

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

{
#35524 requires designing a reliable atomic reservation fallback across unknown-cost and multimodal requests, preserving accounting correctness under concurrency and adding broad regression coverage. #31260 is primarily a scoped propagation and cache-metadata consistency fix across a few synchronous paths.
}
https://github.com/berriai/litellm/issues/35524 3:2 https://github.com/berriai/litellm/issues/31260

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

{
The idle-timeout feature is harder because it requires coordinated, security-sensitive authentication changes across session state, token expiration, activity tracking, sliding renewal, configuration, and frontend logout behavior. The callback issue is comparatively narrower, centered on correcting configuration/UI merge precedence and validating callback initialization.
}
https://github.com/berriai/litellm/issues/28237 3:1 https://github.com/berriai/litellm/issues/12118

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

{
The vLLM change is harder because it affects shared streaming response normalization, compatibility with multiple reasoning-field formats, and regression coverage across proxy paths. The xAI change is narrower provider integration work involving model capability classification, endpoint routing, and targeted image API tests.
}
https://github.com/berriai/litellm/issues/26501 5:3 https://github.com/berriai/litellm/issues/26184