BerriAI/litellm · error · ValueError

No models configured for tier {tier_key}

Error message

No models configured for tier {tier_key}

What it means

Routing guard in the complexity router: the tier has no entry in config.tiers at all (and no default_model fallback applied), so the router cannot map this complexity tier to any model.

Source

Thrown at litellm/router_strategy/complexity_router/complexity_router.py:1200

        self,
        tier: ComplexityTier,
        raw_messages: list[dict[str, Any]] | None,
        resolved_messages: list[dict[str, Any]] | None,
        request_kwargs: dict,
    ) -> str:
        if not self.config.plugins:
            return self.get_model_for_tier(tier)

        from litellm.types.router import RoutingContext

        tier_key: Final = tier.value
        metadata_key: Final = "litellm_metadata" if "litellm_metadata" in request_kwargs else "metadata"
        pool: Final = tuple(self._tier_pools().get(tier_key, ()))
        if not pool:
            # Nothing for the plugins to filter. Falling through would raise the
            # plugin-filtering error below and send the operator hunting for a policy
            # plugin that never ran, so name the real problem: the tier has no models.
            raise ValueError(f"No models configured for tier {tier_key}")
        context = RoutingContext(
            raw_messages=raw_messages or [],
            structured_messages=resolved_messages or [],
            candidate_models=list(pool),
            metadata=request_kwargs.get(metadata_key) or {},
        )
        for plugin in self.config.plugins:
            context = await plugin.run(context)

        if not context.candidate_models:
            # A plugin narrowing a tier to zero candidates is a policy decision (e.g. no
            # model this tenant's budget allows) -- falling back to default_model here
            # (which was never checked against the plugins) would let that policy be
            # silently bypassed. Raise instead, matching the Router-level plugin
            # pipeline's own fail-closed behavior for the same situation.
            raise ValueError(f"No candidate models left for tier {tier_key} after routing-plugin filtering")
        return self._pick_from_tier_value(context.candidate_models, tier_key)

View on GitHub (pinned to 77b7c6c40c)

Solutions

1. Configure models for the tier in the complexity router config.

When it happens

Trigger: Thrown at litellm/router_strategy/complexity_router/complexity_router.py:1200 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of BerriAI/litellm@77b7c6c40c (2026-08-18). Data as JSON: /api/errors/a9de7d511107eb12. Report an issue: GitHub.