Python · AGPL-3.0
ahtx/kindi
Kindi 0.4: local LLM inference on low-cost NVIDIA GPUs, Radeon 780M and CPUs. Bonsai 2B-27B, AH-Nanbeige4.3-33B and experimental Nemotron, with an OpenAI-compatible server.
★ 123
Stars
32 forks · 11 open issues
+6.4/day
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
37.7
Momentum / 100
see the breakdown below
19d ago
Created
last push 3d ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 16.7 | +6.4/day, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 0.0 | needs 7-day and 30-day rates side by side |
| Freshness | 15 | 15.0 | last push 3d ago; decays to zero at 180 days |
| Scale | 15 | 6.1 | 123 stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 37.7 | sum of the above |
Detail
| Topics | amdamperebitnetcudakeplerllm-inferencelocal-llmlow-cost-gpumaxwellopenai-compatiblepascalquadrorocmtensor-parallelismternary |
| Matched on | LLM & Inference (llm-inference) |
| Short window | +45 stars over 7 days = 6.4/day |
| Long window | no snapshot 14–45 days old yet |
| Lifetime average | 7.46 stars/day over 16 days |
| First seen here | 2026-10-25 |
| Last read | 2d ago |