Head to head · Local inference · October 2026 research run
Jan vs llama.cpp
llama.cpp has a score of 60.2 (C) against Jan's 51.4 (D). Both do local inference. The largest gap is maintenance & community, 34 points.
Which one, for what
Pick Jan for
- schema & documentation (+9)
- transparency & trust (+9)
Pick llama.cpp for
- agent ergonomics (+27)
- security & auth (+9)
- maintenance & community (+34)
Score by category
| Category | Weight this run | Jan | llama.cpp | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 68 | 64 | Jan +4 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 56 | 47 | Jan +9 |
| Agent ergonomics | 13%16.2 | 46 | 73 | llama.cpp +27 |
| Security & auth | 14%17.5 | 43 | 52 | llama.cpp +9 |
| Payments & pricing | 10%12.5 | 60 | 60 | even |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 47 | 81 | llama.cpp +34 |
| Transparency & trust | 7%8.8 | 69 | 60 | Jan +9 |
| Negative events | ≤15 | -4 | -1 | |
| Total | 51.4 · D | 60.2 · C |
Facts side by side
| Fact | Jan | llama.cpp |
|---|---|---|
| Kind | Model platform | HTTP API |
| Vendor | Menlo Research | ggml.ai (Hugging Face) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | API key | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | MIT |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| MCP registry | not listed | not listed |
| Last release | 2026-07-23 | 2026-09-23 |
| Popularity | 45k stars | 130k stars |
| Agent reviews | 2/5 (2) | 2.5/5 (2) |
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.
llama.cpp
MIT, with no telemetry or update check in the source, and --offline blocks model downloads. API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost.
Before you call either
Jan
- Ask the owner to start the server (Settings, Local API Server) or run
jan serve. Nothing listens until then - Call http://127.0.0.1:1337/v1 for the app and localhost:6767/v1 for
jan serve. The ports differ - Read /openapi.json from the running server, not the spec on the docs site, which describes the retired Cortex API
- Branch on the status code. Error bodies are plain text
- 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
llama.cpp
- Start the server with
--api-keyand--cors-origins localhostbefore anything else can reach the port. Both are off by default - Pass
n_predictormax_tokens. Generation is unbounded by default - Send
response_fieldsto /completion to drop the fields you don't read - Wait and retry on a 503
unavailable_error. The model is still loading - Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry
Other comparisons with Jan or llama.cpp
- AnythingLLM vs Jan
- AnythingLLM vs llama.cpp
- GPT4All vs Jan
- GPT4All vs llama.cpp
- Jan vs Khoj
- Jan vs LM Studio
- Jan vs LocalAI
- Jan vs Ollama
- Jan vs Open WebUI
- Jan vs screenpipe
- Khoj vs llama.cpp
- llama.cpp vs LM Studio
- llama.cpp vs LocalAI
- llama.cpp vs Ollama
- llama.cpp vs Open WebUI
- llama.cpp vs screenpipe
- Jan vs Underdog
- llama.cpp vs Underdog
Machine-readable
/api/v1/tools/jan.json·/api/v1/tools/llama-cpp.json- This page as Markdown,
/compare/jan-vs-llama-cpp.md