Medium 3.5
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI.
Empirical Evaluation Results
Architectural Profile & Capabilities
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex... On ARMES, Medium 3.5 operates via strict RAM-only Zero Data Retention inference pipelines. User inputs, prompts, and completions are processed ephemerally and are never stored, logged, or indexed for model training.
Autoregressive dense transformer with grouped-query attention (GQA) and rotary position embeddings calibrated for low TTFT.
Recommended Workloads & Primary Use Cases
- •Deep reasoning passes utilize test-time compute which may increase time-to-first-token (TTFT).
- •Long-context retrieval beyond 200K tokens requires structured needle-in-haystack prompt framing.
- •Tool definitions should enforce strict JSON Schema validation constraints.
Calls to Medium 3.5 are routed through strict Zero Data Retention inference channels. Prompts and outputs are never stored, indexed, or monitored by Mistral AI.
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