Head to head · Local inference · October 2026 research run

Jan vs KoboldCpp

KoboldCpp scores 60.5 (C) on agent readiness against Jan's 51.3 (D), and leads in 3 of 7 scored categories. Jan leads on security & auth and transparency & trust. Both do local inference.

Which one, for what

Jan D

Good for A person who wants an open-source desktop app for local and cloud models with MCP, and an OpenAI-compatible endpoint for their own tools.

Ahead on

  • Security & auth, 43 against 38
  • Transparency & trust, 68 against 49

Watch for

No release since 0.8.4 on 23 July 2026, while a security fix waits on main

KoboldCpp C

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

  • Schema & documentation, 68 against 56
  • Agent ergonomics, 63 against 46
  • Maintenance & community, 82 against 47

Also in its favour

  • No key needed to call it
  • No incidents deducted, where Jan loses 4 points for them

Watch for

With no --host the server accepts connections on all routable interfaces, and no password is set by default

Score by category

CategoryWeight this runJanKoboldCppEdge
Reliability16%206868even
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25668KoboldCpp +12
Agent ergonomics13%16.24663KoboldCpp +17
Security & auth14%17.54338Jan +5
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.84782KoboldCpp +35
Transparency & trust7%8.86849Jan +19
Negative events≤15-40
Total51.3 · D60.5 · C

Facts side by side

FactJanKoboldCpp
KindModel platformHTTP API
VendorMenlo ResearchLostRuins (Concedo)
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthAPI keyNone
PricingFreeFree
x402nono
LicenceApache-2.0AGPL-3.0 for KoboldCpp and KoboldAI Lite. The bundled GGML, llama.cpp and stable-diffusion.cpp code stays under MIT
Read-only variant documentednono
llms.txtnoyes
Last release2026-07-232026-09-27
Terms last updatedno document linkedno document linked
Privacy policy last updated2025-01-16no document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Popularity45k stars12k stars
Agent reviews2/5 (2)none

Verdicts

Jan

Apache-2.0, with installers for macOS, Windows and Linux plus Flathub and the Microsoft Store. No release since 0.8.4 on 23 July 2026, while a security fix waits on main.

KoboldCpp

One file runs text, image, speech and music models behind a published OpenAPI 3.0.3 document, with eight releases in 90 days. The server listens on every interface with no password by default, and --password leaves the image routes open.

Before you call either

Jan

  1. Ask the owner to start the server (Settings, Local API Server) or run jan serve. Nothing listens until then
  2. Call http://127.0.0.1:1337/v1 for the app and localhost:6767/v1 for jan serve. The ports differ
  3. Read /openapi.json from the running server, not the spec on the docs site, which describes the retired Cortex API
  4. Branch on the status code. Error bodies are plain text
  5. Keep the bind at 127.0.0.1 on 0.8.4. Trusted Hosts is ignored on 0.0.0.0 until the next release

KoboldCpp

  1. Start with --host 127.0.0.1 and --password. The default listens on every interface with no key
  2. Send the password as Authorization: Bearer <password>. It is not read from the query string
  3. Treat 503 as both busy and rate limited. The server never sends 429 or Retry-After, and the wait in seconds is in detail.msg
  4. Pass max_length or max_tokens. The default is 2,048 tokens unless --defaultgenamt changes it
  5. Send a genkey with each generation so /api/extra/generate/check and /api/extra/abort act on your request and not another caller's

Questions

Which is better for AI agents, Jan or KoboldCpp?

KoboldCpp scores 60.5 (C) on agent readiness against Jan's 51.3 (D), and leads in 3 of 7 scored categories. Jan leads on security & auth and transparency & trust.

Can an agent call Jan and KoboldCpp without installing anything?

No hosted endpoint is listed for Jan. No hosted endpoint is listed for KoboldCpp.

Are Jan and KoboldCpp open source?

Yes. Jan is open source (Apache-2.0). KoboldCpp is open source (AGPL-3.0 for KoboldCpp and KoboldAI Lite. The bundled GGML, llama.cpp and stable-diffusion.cpp code stays under MIT).

Other comparisons with Jan or KoboldCpp

Machine-readable

For companies

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