Claude Haiku 4.5 vs Codestral 2508 for Persona Consistency

Persona Consistency demands maintaining a character or role over turns and resisting prompt injection. Key capabilities: contextual memory at scale (long_context), strict adherence to persona (persona_consistency), resistance to adversarial prompts (safety_calibration), and structured behavior when given format constraints (structured_output). In the provided data there is no external benchmark for this task, so our taskScore is the primary evidence: Claude Haiku 4.5 = 5/5; Codestral 2508 = 3/5. Supporting internal metrics: both models score 5/5 on long_context and 5/5 on tool_calling, so both can hold large histories and call functions reliably. Haiku has strong safety_calibration (2/5 vs Codestral's 1/5) and higher persona_consistency, while Codestral leads on structured_output (5/5 vs Haiku's 4/5) and is substantially cheaper (Haiku output $5/mTok vs Codestral $0.9/mTok). Use the persona_consistency score as the decisive signal for this task.

1. Long-form roleplay with adversarial edits — Claude Haiku 4.5 (persona_consistency 5/5, long_context 5/5, safety_calibration 2/5) will more reliably stay ‘in character’ and refuse injection attempts; expect fewer persona breaks in our tests. 2) High-volume, cost-sensitive assistants that must follow a strict output schema — Codestral 2508 (persona_consistency 3/5, structured_output 5/5) is better when you need JSON-first, low-cost inference (input $0.3/mTok, output $0.9/mTok) but you should add persona-checking prompts or external validation because its persona consistency is weaker. 3) Hybrid product: use Haiku for customer-facing persona-critical flows (onboarding, therapeutic or legal roleplay) where a 2-point persona gap matters; use Codestral for backend generation where structured output and lower cost outweigh occasional persona drift.

For Persona Consistency, choose Claude Haiku 4.5 if you need the model to reliably maintain character and resist prompt injection (5/5 in our testing, tied for 1st). Choose Codestral 2508 if you prioritize structured-output fidelity and much lower runtime costs (output $0.9/mTok) and can tolerate weaker persona guarantees (3/5 in our testing) or add external persona checks.