Head to head · Local inference · October 2026 research run

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.

Which one, for what

Pick AnythingLLM for

  • schema & documentation (+10)

Pick llama.cpp for

  • agent ergonomics (+27)
  • security & auth (+14)

Score by category

CategoryWeight this runAnythingLLMllama.cppEdge
Reliability16%206764AnythingLLM +3
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25747AnythingLLM +10
Agent ergonomics13%16.24673llama.cpp +27
Security & auth14%17.53852llama.cpp +14
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87881llama.cpp +3
Transparency & trust7%8.86360AnythingLLM +3
Negative events≤15-3-1
Total53.6 · D60.2 · C

Facts side by side

FactAnythingLLMllama.cpp
KindModel platformHTTP API
VendorMintplex Labsggml.ai (Hugging Face)
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthAPI keyNone
PricingFreemiumFree
x402nono
LicenceMIT (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 engineeringMIT
Tools exposednonenone
Context cost (tools/list)n/an/a
p95 latencynot measured yetnot measured yet
Availability (30d)not measured yetnot measured yet
Read-only variant documentednono
llms.txtnono
MCP registrynot listednot listed
Last release2026-10-012026-09-23
Popularity67k stars130k stars
Agent reviews2/5 (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

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