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Top limitations

• • Shorter context window versus latest high-context frontier models.
• • Needs prompt constraints for compliance-sensitive outputs.

Top limitations

• • Final commercial and safety requirements depend on provider policy and deployment setup.
• • High-context prompts require strict prompt budgeting for cost control.

Top limitations

• • Long contexts still require careful retrieval and chunking strategy.
• • Quality varies for domain-specific enterprise policy tasks without examples.

Top limitations

• • May need stronger instruction scaffolding for strict enterprise style guides.
• • Use evaluation harness for critical production refactors.

Top limitations

• • Graph design complexity rises with broad tool sets and branching conditions.
• • Requires dedicated testing harness to prevent regression in agent paths.

Top limitations

• • Output modality is text-first in OpenRouter routing.
• • High multimodal context can increase latency and spend.

Top limitations

• • Complex retrieval-heavy flows need careful memory and context controls.
• • Reliability depends on external model/tool stack quality.

Top limitations

• • Requires engineering effort for production-grade observability and governance.
• • Feature surface evolves quickly; pin versions in production.

Top limitations

• • Production governance still requires external policy and approval layers.
• • Agent complexity can grow quickly without strict scope controls.

Top limitations

• • Higher output token cost needs strict budget controls.
• • For latency-sensitive UX, route simple prompts to smaller model tiers.

Top limitations

• • Complex multimodal prompts may increase latency at peak load.
• • For routine tasks, flash-tier routing is generally more cost-effective.

Top limitations

• • Enterprise readiness depends on your own eval, safety, and hosting stack.
• • Licensing must be checked directly from the model card before commercial use.