Inception

Mercury Voice

Inception

Mercury Voice is a diffusion language model tuned for the language-reasoning component of real-time voice agents. It generates text, reasons, and calls tools; speech recognition and synthesis are supplied by the surrounding voice stack. Three reasoning-effort settings balance response quality and latency. Enterprise API access became generally available after an earlier preview announcement. Public weights and parameter counts are undisclosed. Reported latency depends on hardware, concurrency, and prompt distribution; production applications require workload-specific evaluation.

Mercury 2.5

Inception

Mercury 2.5 is Inception’s updated hosted diffusion reasoning model for coding agents, structured generation, and low-latency conversational workflows. It improves the quality and serving tradeoff over Mercury 2 while preserving parallel refinement. API and chat access are publicly available, with enterprise deployment options. Public weights and parameter counts are undisclosed. Reported latency depends on hardware, concurrency, and prompt distribution; production applications require workload-specific evaluation.

Mercury Edit 2

Inception

Mercury Edit 2 is Inception’s specialized diffusion model for predicting a developer’s next code edit from recent changes and repository context. Preference training targets useful, selective suggestions rather than overly frequent edits. It complements completion endpoints and is available through the Inception API and editor integrations. Public weights and parameter counts are undisclosed. Reported latency depends on hardware, concurrency, and prompt distribution; production applications require workload-specific evaluation.

Mercury 2

Inception

Mercury 2 is Inception’s hosted reasoning language model based on diffusion. Parallel refinement generates multiple tokens per iteration instead of purely sequential decoding. Tunable reasoning, native tool use, and schema-aligned JSON support coding, retrieval pipelines, and interactive agent loops. Public weights and parameter counts are undisclosed. Reported latency depends on hardware, concurrency, and prompt distribution; production applications require workload-specific evaluation.