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Diffusion-based LLMs (Mercury) that generate tokens in parallel for faster, cheaper inference than autoregressive models.

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Pricing

No public pricing

No public pricing

No public pricing

Core features
  • Diffusion-based language generation
  • Parallel token generation for speed
  • Lower inference cost than conventional LLMs
  • Fine-grained output/schema control
  • API access
  • Enterprise deployment
Use cases
  • Low-latency LLM inference
  • Cost-sensitive high-volume generation
  • Structured/schema-constrained outputs
  • Enterprise AI deployments
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