AI Model Timeline

Tracking the accelerating release frequency of frontier AI models.

DeepSeek-MoE

DeepSeek·

LLMsopen-weightcloud + localEdge / Consumer

Overview

Mixture-of-Experts architecture.

Capabilities and innovations

MoE efficiencyHigh throughputCost effectiveMoE EfficiencyCost-effective TrainingHigh Throughput

Benchmarks

No benchmark values are recorded for this model.

  • GPQA Diamond: not reported by the vendor
  • Humanity’s Last Exam (no tools): not reported by the vendor
  • SWE-bench Verified: not reported by the vendor
  • SWE-bench Pro: benchmark did not exist at release
  • MMLU: not reported by the vendor
  • MMLU-Pro: benchmark did not exist at release
  • Terminal-Bench 2.x: benchmark did not exist at release
  • MMMU-Pro: benchmark did not exist at release

Architecture and hardware

Parameters
14.6B total, 2.8B active per token (MoE)
Estimated VRAM at Q4
~9 GB, Edge / Consumer class

Links

More from DeepSeek

Data curated by AI Model Timeline. See the methodology for admission criteria, benchmark eras and source priority.