# KoboldCpp vs vLLM (slim)

> KoboldCpp scores 60.5 (C) to vLLM's 57.7 (C) for local inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/koboldcpp-vs-vllm.md (~2,550 tokens) · this version ~530 tokens · JSON https://www.anchorterminal.com/compare/koboldcpp-vs-vllm.json · canonical https://www.anchorterminal.com/compare/koboldcpp-vs-vllm
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · Updated: 2026-10-09

KoboldCpp scores 60.5 (C) on agent readiness against vLLM's 57.7 (C), and leads in 1 of 7 scored categories. vLLM leads on security & auth, maintenance & community and transparency & trust. Both do local inference.

- KoboldCpp: C 60.5, rank #510 of 950 · https://www.anchorterminal.com/tools/koboldcpp.min.md
- vLLM: C 57.7, rank #600 of 950 · https://www.anchorterminal.com/tools/vllm.min.md
- KoboldCpp, good for An owner who wants text, image, speech and music models behind one executable with a writing and roleplay interface, and clients that speak the KoboldAI, OpenAI, Ollama or Anthropic formats. Ahead on Reliability, 68 against 62. Also No incidents deducted, where vLLM loses 6 points for them.
- vLLM, good for An owner with a GPU server who wants many concurrent requests against one open-weight model behind OpenAI or Anthropic compatible routes. Ahead on Security & auth, 50 against 38; Maintenance & community, 88 against 82; Transparency & trust, 67 against 49.

| Category | KoboldCpp | vLLM |
| --- | --- | --- |
| Reliability (16%) | 68 | 62 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 68 | 68 |
| Agent ergonomics (13%) | 63 | 64 |
| Security & auth (14%) | 38 | 50 |
| Payments & pricing (10%) | 60 | 60 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 82 | 88 |
| Transparency & trust (7%) | 49 | 67 |

| Fact (where they differ) | KoboldCpp | vLLM |
| --- | --- | --- |
| Vendor | LostRuins (Concedo) | vLLM project (PyTorch Foundation) |
| Licence | AGPL-3.0 for KoboldCpp and KoboldAI Lite. The bundled GGML, llama.cpp and stable-diffusion.cpp code stays under MIT | Apache-2.0 |
| llms.txt | yes | no |
| Last release | 2026-09-27 | 2026-10-02 |
| Popularity | 12k stars | 93k stars |