DeepSeek model deployment and inference
Recent window: last 5.2 months (2026-04-24 → 2026-09-28), compared with the prior 5.2 months.
These products provide deployment configurations, inference engines, and fine-tuning recipes tailored for running DeepSeek and other open-weight language models. They are primarily used by machine learning engineers and infrastructure teams optimizing local or enterprise hardware like NVIDIA DGX systems. Unlike general AI developer platforms, this cluster centers specifically on self-hosting and accelerating high-performance open model architectures.
Metrics
- Stage
- heating
- Recent count
- 68
- Prior count
- 4
- Total count
- 78
- Momentum
- 300.00
- Attention
- 0.57
- Crowding
- 0.31
- Concentration
- 0.82
- Opportunity
- 0.61
Opportunity components
- Attention
- 0.57
- Low crowding
- 0.69
- Momentum (normalized)
- 1.00
- Low concentration
- 0.18
Monthly trajectory
Source split
- github
- 54 (0.79)
- hn
- 7 (0.10)
- ph
- 7 (0.10)
- yc
- 0 (0.00)
Dominant source: github · Divergence: 0.79
Similar themes
- graphics rendering and visual tools (0.44)
- gpu optimization and frame generation tools (0.44)
- DeepSeek harness plugins and tooling (0.43)
- OpenAI-compatible AI API gateways (0.35)
- generative video and image API gateways (0.35)
- efficient local AI inference tools (0.34)
- AI API proxies and developer tools (0.31)
- gaming performance and optimization utilities (0.31)