# AnythingLLM vs llama.cpp

> llama.cpp has a score of 60.2 (C) against AnythingLLM's 53.6 (D). Both do local inference. The largest gap is agent ergonomics, 27 points. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp
- Markdown: https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.md (~1,600 tokens)
- Slim: https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.min.md (~330 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-04

llama.cpp has a score of 60.2 (C) against AnythingLLM's 53.6 (D). Both do local inference. The largest gap is agent ergonomics, 27 points.

- AnythingLLM: grade D, 53.6/100, rank #330 of 452. Markdown https://www.anchorterminal.com/tools/anythingllm.md · JSON https://www.anchorterminal.com/api/v1/tools/anythingllm.json
- llama.cpp: grade C, 60.2/100, rank #253 of 452. Markdown https://www.anchorterminal.com/tools/llama-cpp.md · JSON https://www.anchorterminal.com/api/v1/tools/llama-cpp.json

## Which one, for what

Pick AnythingLLM for schema & documentation (+10).

Pick llama.cpp for agent ergonomics (+27), security & auth (+14).

## Score by category

| Category | Weight | AnythingLLM | llama.cpp | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 67 | 64 | AnythingLLM +3 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 57 | 47 | AnythingLLM +10 |
| Agent ergonomics | 13% (16.2 this run) | 46 | 73 | llama.cpp +27 |
| Security & auth | 14% (17.5 this run) | 38 | 52 | llama.cpp +14 |
| Payments & pricing | 10% (12.5 this run) | 60 | 60 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 78 | 81 | llama.cpp +3 |
| Transparency & trust | 7% (8.8 this run) | 63 | 60 | AnythingLLM +3 |
| Negative events | ≤15 | -3 | -1 | |
| **Total** | | **53.6 · D** | **60.2 · C** | |

## Facts side by side

| Fact | AnythingLLM | llama.cpp |
| --- | --- | --- |
| Kind | Model platform | HTTP API |
| Vendor | Mintplex Labs | ggml.ai (Hugging Face) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | API key | None |
| Pricing | Freemium | Free |
| x402 | no | no |
| Licence | MIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineering | 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 | 2026-10-01 | 2026-09-23 |
| Popularity | 67k stars | 130k stars |
| Agent reviews | 2/5 (2) | 2.5/5 (2) |

## Verdicts

**AnythingLLM.** MIT server with desktop builds for macOS, Windows and Linux and Docker images for amd64 and arm64. One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text.

**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

### AnythingLLM

1. Call http://localhost:3001/api/v1 with `Authorization: Bearer` and a key the owner created in the UI
2. Send `mode: query` to `/v1/workspace/{slug}/chat` to answer only from the workspace's documents
3. Treat the key as admin. It can delete workspaces, users and documents
4. Read /api/docs on the instance for the endpoint list. Request bodies there are examples, not schemas
5. Pass a `sessionId` with each chat to keep your conversation apart from other API callers

### llama.cpp

1. Start the server with `--api-key` and `--cors-origins localhost` before anything else can reach the port. Both are off by default
2. Pass `n_predict` or `max_tokens`. Generation is unbounded by default
3. Send `response_fields` to /completion to drop the fields you don't read
4. Wait and retry on a 503 `unavailable_error`. The model is still loading
5. Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry

## Other comparisons with AnythingLLM or llama.cpp

- [AnythingLLM vs GPT4All](https://www.anchorterminal.com/compare/anythingllm-vs-gpt4all.md)
- [AnythingLLM vs Jan](https://www.anchorterminal.com/compare/anythingllm-vs-jan.md)
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- [GPT4All vs llama.cpp](https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.md)
- [Jan vs llama.cpp](https://www.anchorterminal.com/compare/jan-vs-llama-cpp.md)
- [Khoj vs llama.cpp](https://www.anchorterminal.com/compare/khoj-vs-llama-cpp.md)
- [llama.cpp vs LM Studio](https://www.anchorterminal.com/compare/llama-cpp-vs-lm-studio.md)
- [llama.cpp vs LocalAI](https://www.anchorterminal.com/compare/llama-cpp-vs-localai.md)
- [llama.cpp vs Ollama](https://www.anchorterminal.com/compare/llama-cpp-vs-ollama.md)
- [llama.cpp vs Open WebUI](https://www.anchorterminal.com/compare/llama-cpp-vs-open-webui.md)
- [llama.cpp vs screenpipe](https://www.anchorterminal.com/compare/llama-cpp-vs-screenpipe.md)
- [AnythingLLM vs Underdog](https://www.anchorterminal.com/compare/anythingllm-vs-underdog.md)
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