{ "data": { "a": { "slug": "koboldcpp", "name": "KoboldCpp", "vendor": "LostRuins (Concedo)", "vendorUrl": "https://koboldcpp.net", "kind": "http-api", "category": "local-ai", "summary": "Open-source program for running GGUF models on the owner's own computer, built on llama.cpp. One executable serves a web interface and KoboldAI, OpenAI, Ollama and Anthropic compatible APIs on port 5001.", "url": "https://www.anchorterminal.com/tools/koboldcpp", "markdownUrl": "https://www.anchorterminal.com/tools/koboldcpp.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/koboldcpp.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/koboldcpp.json", "dns": "koboldcpp.grade.anchorterminal.com", "repo": "https://github.com/LostRuins/koboldcpp", "license": "AGPL-3.0 for KoboldCpp and KoboldAI Lite. The bundled GGML, llama.cpp and stable-diffusion.cpp code stays under MIT", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "koboldai/koboldcpp" } ], "auth": "none", "authNotes": "No credential by default. `--password` (or the `KCPP_PASSWORD` environment variable) sets one shared key, sent as `Authorization: Bearer`, and the server reads it from the header only. The key guards text routes. Image generation, upscaling, `/sdapi/v1/interrogate` and `/tts_to_audio` skip the check, and the `--help` text says image endpoints are not secured. Admin routes need `--admin`, an `--admindir` and, when set, a separate `--adminpassword`. Keys have no scopes and change only with a restart. With no `--host` the server listens on all routable interfaces, and CORS reflects any Origin with credentials allowed (https://github.com/LostRuins/koboldcpp/blob/concedo/koboldcpp.py).", "pricing": "free", "pricingNotes": "Free under AGPL-3.0, with no account, key or card. Nothing is sold by the project. The owner pays for hardware and electricity, and the README links third-party GPU rental (RunPod, SimplePod) and Google Colab as other places to run it.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the README, the wiki, the API document or `koboldcpp.py` (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 11972, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://github.com/LostRuins/koboldcpp/wiki", "llmsTxt": "https://koboldcpp.net/llms.txt", "openapi": "https://lite.koboldai.net/koboldcpp_api.json", "capabilities": [ "inference.local", "inference.open-weights", "agent.mcp-client", "embed.text", "image.generate", "speech.stt", "speech.tts", "audio.music" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "openai-compatible", "openapi", "llms-txt", "docker", "agpl", "no-telemetry" ], "lastRelease": "2026-11-02", "graded": true, "anchor": { "graded": true, "score": 62.1, "grade": "B", "agentReady": false, "rank": 571, "ranked": true, "rankOf": 1486, "categoryRank": 4, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 82, "payments": 60, "reliability": 63, "schema": 79, "security": 38, "transparency": 55 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-03" }, "negative": 0, "verdict": "One file runs text, image, speech and music models behind an OpenAPI 3.0.3 document that 1.124.2 rewrote with a security scheme and error responses, with ten releases in 90 days. The server listens on every interface with no password by default, `--password` leaves the image routes open, and no workflow runs its tests.", "bestFor": "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.", "strengths": [ "OpenAPI 3.0.3 document served at `/api?json=1`, rewritten in 1.124.2 with 69 operations, a `BearerAuth` scheme and documented 401 and 503 responses", "KoboldAI, OpenAI, Ollama, Anthropic, AUTOMATIC1111 and ComfyUI style routes from one server on port 5001", "Ten tagged releases between 15 August and 2 November 2026", "AGPL-3.0, with no telemetry or update check found in `koboldcpp.py` and a wiki statement that inputs are sent nowhere", "Admin functions are off by default and take their own `--adminpassword`" ], "weaknesses": [ "With no `--host` the server accepts connections on all routable interfaces, and no password is set by default", "`--password` covers text routes only. The `--help` text says image endpoints are not secured", "CORS reflects any Origin with credentials allowed and permits private-network requests", "No `SECURITY.md` or security.txt, and the one advisory (GHSA-qhvp-gj7g-rw26) is in no public database we could read", "No workflow runs a test. All eight workflows are builds started by hand, and the AutoGuess pull-request test was removed by 1.123" ], "agentNotes": [ "Start with `--host 127.0.0.1` and `--password`. The default listens on every interface with no key", "Send the password as `Authorization: Bearer \u003cpassword\u003e`. It is not read from the query string", "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`", "Pass `max_length` or `max_tokens`. The default is 2,048 tokens unless `--defaultgenamt` changes it", "Send a `genkey` with each generation so `/api/extra/generate/check` and `/api/extra/abort` act on your request and not another caller's" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 62.1 } ], "editorialScores": { "ergonomics": 65, "maintenance": 82, "payments": 60, "reliability": 63, "schema": 79, "security": 38, "transparency": 70 }, "provenanceScore": 39, "checked": { "categories": { "ergonomics": "2026-11-03", "maintenance": "2026-11-03", "payments": "2026-11-03", "reliability": "2026-11-03", "schema": "2026-11-03", "security": "2026-11-03", "transparency": "2026-11-03" }, "last": "2026-11-03", "lastMoved": "2026-11-03", "oldest": "2026-11-03", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "curl -fLo koboldcpp-linux-x64 https://github.com/LostRuins/koboldcpp/releases/latest/download/koboldcpp-linux-x64 \u0026\u0026 chmod +x koboldcpp-linux-x64 \u0026\u0026 ./koboldcpp-linux-x64\n./koboldcpp-linux-x64 --model /path/to/model.gguf # listens on port 5001", "http": "curl --request POST \\\n --url http://localhost:5001/api/v1/generate \\\n --header \"Content-Type: application/json\" \\\n --data '{\"prompt\": \"Niko the kobold stalked carefully down the alley,\", \"max_context_length\": 2048, \"max_length\": 100}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/koboldcpp" }, "area": "models", "provenance": { "legalEntity": "", "domain": "koboldcpp.net", "domainRegistered": "2026-03-18", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/LostRuins/koboldcpp/releases", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "No legal entity is named in the repository, the wiki or koboldcpp.net. The maintainer publishes as LostRuins on GitHub and Concedo on Discord, and the Windows binary's version resource gives KoboldAI as the company name.", "The project publishes no terms of service and no privacy policy, so both fields are empty. The licence is AGPL-3.0 and the only privacy statement is an FAQ entry in the wiki.", "The README calls koboldcpp.net the official community website. RDAP gives its registration date as 2026-03-18 and Cloudflare, Inc. as registrar. The README warns that koboldcpp.com is a fake site.", "koboldcpp.net/.well-known/security.txt and koboldai.org/.well-known/security.txt return 404. koboldcpp.net/llms.txt returns a short index that links llms-small.txt and llms-full.txt.", "There's no shared hosted endpoint. The server runs on the owner's machine. The online API reference is on lite.koboldai.net." ], "score": 39 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/koboldcpp.json", "live": { "slug": "koboldcpp", "versions": [ { "registry": "github", "name": "LostRuins/koboldcpp", "version": "v1.124.2", "released": "2026-10-31", "seenAt": "2026-11-06T23:37:28.927081688Z" } ], "githubStars": 12173, "securityTxt": { "url": "https://koboldcpp.net/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:02:05.668927806Z" }, "llmsTxt": { "url": "https://koboldcpp.net/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:49.848956908Z" }, "domain": { "domain": "koboldcpp.net", "registered": "2026-03-18", "source": "https://rdap.verisign.com/net/v1/domain/koboldcpp.net", "checkedAt": "2026-11-01T14:20:21.980776805Z" }, "github": { "repo": "lostruins/koboldcpp", "checkedAt": "2026-11-02T09:01:50.914110073Z", "stars": 12130, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T03:39:19Z", "openIssues": 530, "openPRs": 8, "issuesOpened90d": 104, "issuesClosed90d": 65, "prsMerged90d": 56, "advisories": [ { "ghsa": "GHSA-4pq2-hqcm-7phq", "severity": "high", "published": "2026-10-31T05:06:41Z" }, { "ghsa": "GHSA-xv6q-pfc5-4vf3", "severity": "high", "published": "2026-10-31T05:05:48Z" }, { "ghsa": "GHSA-h59g-8cq4-cqjj", "severity": "high", "published": "2026-10-13T13:48:50Z" }, { "ghsa": "GHSA-qhvp-gj7g-rw26", "severity": "low", "published": "2026-08-29T03:32:25Z" } ], "replies": { "sampled": 25, "unanswered": 5, "medianDays": 0.3 } }, "updatedAt": "2026-11-07T16:02:05.668927806Z" } }, "answer": "KoboldCpp scores 62.1 (B) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability and transparency \u0026 trust.", "b": { "slug": "privategpt", "name": "PrivateGPT", "vendor": "Zylon (PriBAI Technology Spain S.L.)", "vendorUrl": "https://docs.privategpt.dev", "kind": "http-api", "category": "local-ai", "summary": "PrivateGPT is Zylon's open-source server that puts an Anthropic-style messages API, document ingestion, retrieval with citations, built-in tools and MCP connectors in front of any OpenAI-compatible local model server. The owner runs it.", "url": "https://www.anchorterminal.com/tools/privategpt", "markdownUrl": "https://www.anchorterminal.com/tools/privategpt.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/privategpt.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/privategpt.json", "dns": "privategpt.grade.anchorterminal.com", "repo": "https://github.com/zylon-ai/private-gpt", "license": "Apache-2.0", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "zylonai/private-gpt" } ], "auth": "none", "authNotes": "Authentication is off by default. When `server.auth.enabled` is set, every request must carry one static secret in the `Authorization` header, compared with the whole header value. There are no per-user keys, scopes or rotation, and the docs show it as a Bearer token, a Basic value and an Anthropic API key in different places (checked 2026-11-06).", "pricing": "free", "pricingNotes": "Free under Apache-2.0 with no account or card. The cost is the owner's hardware and model server. Zylon sells a separate enterprise platform built on PrivateGPT through demos, with no public price (checked 2026-11-06).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the source, the OpenAPI file or the docs (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 57600, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://docs.privategpt.dev/introduction", "llmsTxt": "https://docs.privategpt.dev/llms.txt", "openapi": "https://raw.githubusercontent.com/zylon-ai/private-gpt/main/fern/openapi/openapi.json", "capabilities": [ "inference.local", "memory.search", "agent.mcp-client" ], "tags": [ "open-source", "local", "self-hosted", "docker", "openapi", "llms-txt", "rag", "mcp-client", "anthropic-compatible", "python", "free" ], "lastRelease": "2026-06-18", "graded": true, "anchor": { "graded": true, "score": 53.2, "grade": "D", "agentReady": false, "rank": 954, "ranked": true, "rankOf": 1486, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 64, "maintenance": 41, "payments": 60, "reliability": 70, "schema": 83, "security": 32, "transparency": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": -7, "negativeNotes": [ "Issue #2269, opened 11 June 2026, reports that the async ingestion API reads any local path given as a URI artifact. The stale bot closed it as not planned on 5 July with no maintainer reply, and `load_file_from_uri` in the source of 29 October 2026 still falls back to reading a local file for any value that isn't a URL, s3 or base64. With authentication off and a 0.0.0.0 bind by default, that is an open file-read path on a default install. Read from the source, not run (-7). https://github.com/zylon-ai/private-gpt/issues/2269" ], "verdict": "PrivateGPT 1.0 is an Apache-2.0 server that gives local models an Anthropic-style messages API with retrieval, citations, tools and MCP, documented by an OpenAPI file and llms.txt. A default start has authentication off, listens on every interface and reads local paths given as URIs, and a public report of that was closed without a reply.", "bestFor": "A local backend for apps and agents that want an Anthropic-style API with document retrieval, citations and tools over local models.", "strengths": [ "Messages API modelled on Anthropic's, so Claude Code and Anthropic SDKs work by changing the base URL", "OpenAPI file of 38 paths, llms.txt and Markdown copies of every docs page", "Retrieval with citations, async ingestion, web, database and tabular tools, and remote MCP servers in one API", "Apache-2.0, with no telemetry to Zylon found in the source and OpenTelemetry tracing off by default", "Works with Ollama, llama.cpp, vLLM, LM Studio or any OpenAI-compatible server" ], "weaknesses": [ "Authentication is off by default, the server binds 0.0.0.0 and CORS allows every origin", "When on, authentication is one shared static secret, with no per-user keys or scopes", "A June 2026 report of local file reads through URI artifacts was closed by a stale bot, and the source still reads local paths", "No release since 1.0.1 in June 2026 while main has moved on, including a breaking change", "Code execution runs as a host subprocess with resource limits, not in a container" ], "agentNotes": [ "Turn on `server.auth` and bind to 127.0.0.1 before exposing an instance, since a default start answers any caller", "Point Anthropic SDKs or Claude Code at the server with `ANTHROPIC_BASE_URL=http://localhost:8080`", "Start an OpenAI-compatible model server and an embedding server first, and set `OPENAI_API_BASE` and `OPENAI_EMBEDDING_API_BASE`", "Pass ingested documents through `tool_context` to get answers with citations", "Treat web fetch, search and MCP results as untrusted, since PrivateGPT documents no prompt-injection handling" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.2 } ], "editorialScores": { "ergonomics": 64, "maintenance": 41, "payments": 60, "reliability": 70, "schema": 83, "security": 32, "transparency": 67 }, "provenanceScore": 61, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "brew tap zylon-ai/tap\nbrew install private-gpt", "http": "curl http://localhost:8080/v1/messages \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"qwen3.5:35b\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain retrieval-augmented generation.\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/privategpt" }, "area": "models", "provenance": { "legalEntity": "PriBAI Technology Spain S.L.", "domain": "privategpt.dev", "domainRegistered": "2023-10-16", "endpointOnVendorDomain": null, "terms": "https://github.com/zylon-ai/private-gpt/blob/main/LICENSE", "privacy": "", "statusPage": "", "changelog": "https://github.com/zylon-ai/private-gpt/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-11-06", "notes": [ "Self-hosted software with no hosted endpoint, so the Apache-2.0 licence stands in for terms and no privacy policy is scored.", "The zylon.ai terms name PriBAI Technology Spain S.L. (VAT ESB56550130) under Spanish law and cover the website and Zylon services. They forbid access through bots, scripts or scrapers, outside standard search engine or browser use. We read the terms and two public pages.", "RDAP gives privategpt.dev a registration date of 16 October 2023.", "docs.privategpt.dev/.well-known/security.txt and www.zylon.ai/.well-known/security.txt answer 404. SECURITY.md in the repository is the reporting route.", "docs.privategpt.dev and www.zylon.ai robots.txt allow our reader. wheels.privategpt.dev has no robots.txt (404)." ], "score": 61 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/privategpt.json", "live": { "slug": "privategpt", "versions": [ { "registry": "github", "name": "zylon-ai/private-gpt", "version": "v1.0.1", "released": "2026-06-18", "seenAt": "2026-11-06T23:58:40.643071731Z" } ], "githubStars": 57632, "securityTxt": { "url": "https://privategpt.dev/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T15:59:53.351491852Z" }, "llmsTxt": { "url": "https://docs.privategpt.dev/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:41.730243326Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/zylon-ai/private-gpt/main/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:24:15.016082629Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "767d5dd99544" }, { "url": "https://raw.githubusercontent.com/zylon-ai/private-gpt/main/LICENSE", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:24:17.075442465Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "839fbbcddc72" } ], "updatedAt": "2026-11-07T15:59:53.351491852Z" } }, "edges": [ { "by": 41, "category": "maintenance", "leads": "koboldcpp", "name": "Maintenance \u0026 community", "reasons": { "a": "Release 1.124.2 on 2 November 2026, tagged the day before this check, read from the tag dates in a clone since GitHub's release pages refuse our session (30). Ten tagged releases since 5 August 2026 (1.119 on 15 August, 1.120, 1.121, 1.122, 1.122.1, 1.123, 1.123.1, 1.124, 1.124.1 and 1.124.2) (20). 524 open issues and 5 open pull requests, with replies on all 24 of the newest open issues, per the 8 October check, not re-read on 3 November. The README points to GitHub Discussions and a Discord server. One person, Concedo, is the main author of the project's own commits (20 of 25). No client library. The official Docker image was last updated on 14 September 2026, before the six newest releases, and has 167,319 pulls (6 of 15). Upstream llama.cpp is merged regularly and builds run on GitHub Actions for five targets, but they are started by hand, `requirements.txt` pins only minimum versions and there's no Dependabot (6 of 10). 30 + 20 + 20 + 6 + 6 = 82.", "b": "The last release is 1.0.1, dated 16 June 2026 in the changelog and tagged 18 June, 141 days before the check (10 of 30). No release or dated changelog entry in the 90 days since 8 August (0 of 20). Maintainers commit most days and outside pull requests merged in October, but 23 pull requests are open and the stale bot closes issues, including two security reports, with no maintainer reply (13 of 25). Homebrew tap, wheel index and Docker images ship with releases, and Anthropic SDKs work against it. No product MCP server of its own, though it connects to remote MCP servers (10 of 15). Dependabot, uv.lock, actions pinned by commit since 19 October and dependency CVE upgrades in June, July and August (8 of 10). 10 + 0 + 13 + 10 + 8 = 41." }, "scores": { "a": 82, "b": 41 } }, { "by": 9, "category": "transparency", "leads": "privategpt", "name": "Transparency \u0026 trust", "reasons": { "a": "The editorial half. AGPL-3.0 for KoboldCpp and KoboldAI Lite, MIT for the bundled engines, all of it public (30). No privacy policy. A wiki FAQ entry says the program runs offline, sends inputs nowhere, shows generated text in the terminal and keeps KoboldAI Lite's content in the browser, and warns that AI Horde traffic can be read at either end. That agrees with `koboldcpp.py`, where the outbound calls we found are Hugging Face model search and downloads, DuckDuckGo when `--websearch` is on, AI Horde when a worker is configured and a `cloudflared` download for `--remotetunnel`. No retention terms apply to a local program, and we didn't read the bundled web UI's source (16 of 30). Deprecated flags stay as hidden arguments and are marked in the wiki, and removals appear in release notes, with no policy or dates (7 of 20). No telemetry, analytics or update check in `koboldcpp.py`, so nothing to opt out of. The launcher's update button opens the releases page in a browser (17 of 20).", "b": "Apache-2.0 (30). The OpenAPI description says no data leaves the execution environment, but the docs list cloud gateways as model providers and web search goes to outside services when enabled, and no privacy statement covers the software. Zylon's privacy policy covers its website (15 of 30). The 1.0 rewrite was marked as a breaking change in the changelog, and there is no deprecation policy (6 of 20). No telemetry to Zylon found in the source. OpenTelemetry tracing is off by default and its exporters write local files or to the owner's collector, documented on the observability page (16 of 20). 30 + 15 + 6 + 16 = 67." }, "scores": { "a": 55, "b": 64 } }, { "by": 7, "category": "reliability", "leads": "privategpt", "name": "Reliability", "reasons": { "a": "Read with the local-software lines, since KoboldCpp runs on the owner's machine with no hosted service. Single-file binaries on GitHub releases for Windows x64, Linux x64 and Apple Silicon macOS, with `nocuda` and `oldpc` variants and the hardware each suits stated in the README and release notes, plus the `koboldai/koboldcpp` Docker image. No package-manager release of the project's own, since the Nix and AUR packages are third-party (18 of 20). Eight workflows in the repository at 1.124.2, all builds started by hand. The AutoGuess test that ran on pull requests and three unofficial test builds were gone by 1.123 (13 October 2026), so no workflow runs the test suite. The macOS build, also started by hand, runs the built binary once on a small model as its only check. The `tests` folder holds 526 lines of Python in four files that nothing runs automatically (5 of 25). 524 open issues and 5 open pull requests with no stale bot, and replies on the 24 newest open issues, per the 8 October check, not re-read on 3 November, since GitHub's pages refuse our session (16 of 25). Sequential 1.x version numbers with notes on every release. 1.123 replaced `--multiuser` with `--queuelimit` and kept the old flag as a hidden deprecated argument, so existing launch commands still start. No changelog file and no stated semver rule (9 of 15). Version 1.124.2 (15). 18 + 5 + 16 + 9 + 15 = 63.", "b": "Read with the local-software lines, since PrivateGPT runs on the owner's hardware with no hosted service behind it. Homebrew tap, `uv tool install` from Zylon's own wheel index (not PyPI) and Docker Hub images `zylonai/private-gpt` 1.0.1 of 18 June 2026. Python 3.11 only, stated in pyproject.toml, and it needs a separate OpenAI-compatible model server (17 of 20). tests.yml runs format, lint, typecheck and the tests affected by each push on main, with the full suite of 217 test files on release pull requests. We couldn't see run results because the GitHub API refused us, and issue #2441 of 1 November reports the Claude spec update workflow failing (15 of 25). GitHub shows 3 open issues of about 1,250, because a stale bot closes quiet issues, two security reports among them, with no maintainer reply (12 of 25). release-please keeps a changelog with breaking changes marked, but no release has been cut since 1.0.1 while main carries 51 commits since 8 August, among them a breaking observability change of 23 October (11 of 15). Version 1.0.1 (15). 17 + 15 + 12 + 11 + 15 = 70." }, "scores": { "a": 63, "b": 70 } }, { "by": 6, "category": "security", "leads": "koboldcpp", "name": "Security \u0026 auth", "reasons": { "a": "Read with the tool checklist, credential model first. No credential by default. `--password` sets one shared key, sent as a Bearer token and never read from the query string, with a separate `--adminpassword` for admin routes. Keys have no scopes and change only with a restart, and the key doesn't cover image generation, upscaling, `/sdapi/v1/interrogate` or `/tts_to_audio`, as the `--help` text says (11 of 30). Admin mode, web search, MCP servers and the agent are off by default, the agent asks for confirmation of tool calls unless set to auto or off, and `/api/extra/shutdown` answers only local callers with `--singleinstance`. But with no `--host` the server listens on all routable interfaces, CORS reflects any Origin with credentials and allows private-network requests, so a web page or another machine on the network can call a server with no password (7 of 20). The server returns model output unless web search or MCP tools are on. The wiki lists flags for a public instance and the 1.122 notes tell users to take care when approving tool calls, with no guidance on untrusted content (7 of 15). Prompts and outputs print to the terminal unless `--quiet` is set and `/api/extra/perf` gives timing counters. No per-key record or log file was found (6 of 15). No `SECURITY.md` (none in the repository at 1.124.2), security.txt or bug bounty. GitHub private vulnerability reporting is open, and one advisory was published on 29 August 2026 (GHSA-qhvp-gj7g-rw26, Low) with the fix committed on 18 August, per the 8 October check (GitHub's pages weren't readable on 3 November and OSV holds no record of it). 1.124 masks passwords and keys in the startup print, and further bounds checks for the legacy loaders landed in 1.124, hardening that names no flaw (7 of 20).", "b": "Read with the tool checklist. Authentication is off by default, and when on it is one static secret compared with the whole `Authorization` header, with a sample `secret:key` value in settings.yaml. There are no per-user keys or scopes, `private-gpt serve` binds 0.0.0.0 by default and CORS allows every origin, so a default start answers anyone on the network. The docs disagree on the header (Bearer, Basic or an Anthropic key) (6 of 30). Tools are chosen per request and code execution has internet off by default, but bash runs as a host subprocess with resource limits, not in a container, and nothing asks for approval (6 of 20). Web fetch, web search, documents and MCP servers bring untrusted text to the model. A public prompt-injection report (#2270) was closed by the stale bot, and no guidance was found beyond a 19 October change that bounds tool output (3 of 15). OpenTelemetry traces cover every request, model call, tool and sandbox step, off by default, with local JSON lines exporters (10 of 15). SECURITY.md since 23 July 2026 asks for private reports through GitHub or Discord. No bounty, no certification, and the June and July security reports in issues were closed by a bot with no reply (7 of 20). 6 + 6 + 3 + 10 + 7 = 32." }, "scores": { "a": 38, "b": 32 } } ], "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "LostRuins (Concedo)", "b": "Zylon (PriBAI Technology Spain S.L.)", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "AGPL-3.0 for KoboldCpp and KoboldAI Lite. The bundled GGML, llama.cpp and stable-diffusion.cpp code stays under MIT", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-02", "b": "2026-06-18", "name": "Last release" }, { "a": "no document linked", "b": "no date given", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "12k stars", "b": "58k stars", "name": "Popularity" }, { "a": "2.8/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "KoboldCpp scores 62.1 (B) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability and transparency \u0026 trust.", "question": "Which is better for AI agents, KoboldCpp or PrivateGPT?" }, { "answer": "Neither needs a key.", "question": "Do KoboldCpp and PrivateGPT need an API key?" }, { "answer": "No hosted endpoint is listed for KoboldCpp. No hosted endpoint is listed for PrivateGPT.", "question": "Can an agent call KoboldCpp and PrivateGPT without installing anything?" }, { "answer": "Yes. 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). PrivateGPT is open source (Apache-2.0).", "question": "Are KoboldCpp and PrivateGPT open source?" } ], "goodFor": [ { "aheadOn": [ "Security \u0026 auth, 38 against 32", "Maintenance \u0026 community, 82 against 41" ], "also": [ "Free to start without a card", "No incidents deducted, where PrivateGPT loses 7 points for them" ], "goodFor": "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.", "slug": "koboldcpp", "watchFor": "With no `--host` the server accepts connections on all routable interfaces, and no password is set by default" }, { "aheadOn": [ "Reliability, 70 against 63", "Transparency \u0026 trust, 64 against 55" ], "also": null, "goodFor": "A local backend for apps and agents that want an Anthropic-style API with document retrieval, citations and tools over local models.", "slug": "privategpt", "watchFor": "Authentication is off by default, the server binds 0.0.0.0 and CORS allows every origin" } ], "history": { "koboldcpp": [ { "causes": [ "product" ], "date": "2026-11-03", "delta": 1.1, "from": 61, "fromGrade": "C", "to": 62.1, "toGrade": "B" }, { "causes": [ "evidence" ], "date": "2026-10-28", "delta": 0.3, "from": 60.7, "fromGrade": "C", "to": 61, "toGrade": "C" }, { "causes": [ "evidence" ], "date": "2026-10-27", "delta": 0.2, "from": 60.5, "fromGrade": "C", "to": 60.7, "toGrade": "C" } ], "privategpt": null }, "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-koboldcpp.json", "title": "AnythingLLM vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-privategpt.json", "title": "AnythingLLM vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/berth-vs-koboldcpp.json", "title": "Berth vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/berth-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/berth-vs-privategpt.json", "title": "Berth vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/berth-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-koboldcpp.json", "title": "BitRun vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/bitrun-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-privategpt.json", "title": "BitRun vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/bitrun-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-koboldcpp.json", "title": "Docker Model Runner vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-privategpt.json", "title": "Docker Model Runner vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-koboldcpp.json", "title": "Foundry Local vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-privategpt.json", "title": "Foundry Local vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-koboldcpp.json", "title": "Core vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-privategpt.json", "title": "Core vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-koboldcpp.json", "title": "GPT4All vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-privategpt.json", "title": "GPT4All vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.json", "title": "HyperQwen vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-privategpt.json", "title": "HyperQwen vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-koboldcpp.json", "title": "Jan vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/jan-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-privategpt.json", "title": "Jan vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/jan-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-koboldcpp.json", "title": "Khoj vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/khoj-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade.json", "title": "KoboldCpp vs Lemonade", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-llama-cpp.json", "title": "KoboldCpp vs llama.cpp", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-lm-studio.json", "title": "KoboldCpp vs LM Studio", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-localai.json", "title": "KoboldCpp vs LocalAI", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.json", "title": "KoboldCpp vs MLX LM", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-ollama.json", "title": "KoboldCpp vs Ollama", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-open-webui.json", "title": "KoboldCpp vs Open WebUI", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-screenpipe.json", "title": "KoboldCpp vs screenpipe", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-text-generation-webui.json", "title": "KoboldCpp vs TextGen", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-vllm.json", "title": "KoboldCpp vs vLLM", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-privategpt.json", "title": "Lemonade vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/lemonade-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/llama-cpp-vs-privategpt.json", "title": "llama.cpp vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-privategpt.json", "title": "LM Studio vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/localai-vs-privategpt.json", "title": "LocalAI vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/localai-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-privategpt.json", "title": "MLX LM vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-privategpt.json", "title": "Ollama vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/ollama-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/open-webui-vs-privategpt.json", "title": "Open WebUI vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/open-webui-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/privategpt-vs-screenpipe.json", "title": "PrivateGPT vs screenpipe", "url": "https://www.anchorterminal.com/compare/privategpt-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/privategpt-vs-text-generation-webui.json", "title": "PrivateGPT vs TextGen", "url": "https://www.anchorterminal.com/compare/privategpt-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/privategpt-vs-vllm.json", "title": "PrivateGPT vs vLLM", "url": "https://www.anchorterminal.com/compare/privategpt-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-privategpt.json", "title": "Khoj vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/khoj-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/localghost-vs-privategpt.json", "title": "LocalGhost vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/localghost-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-underdog.json", "title": "KoboldCpp vs Underdog", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-underdog" } ], "panel": null, "scores": [ { "by": 7, "edge": "privategpt", "key": "reliability", "koboldcpp": 63, "name": "Reliability", "privategpt": 70, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 4, "edge": "privategpt", "key": "schema", "koboldcpp": 79, "name": "Schema \u0026 documentation", "privategpt": 83, "weight": 13 }, { "by": 1, "edge": "koboldcpp", "key": "ergonomics", "koboldcpp": 65, "name": "Agent ergonomics", "privategpt": 64, "weight": 13 }, { "by": 6, "edge": "koboldcpp", "key": "security", "koboldcpp": 38, "name": "Security \u0026 auth", "privategpt": 32, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "koboldcpp": 60, "name": "Payments \u0026 pricing", "privategpt": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 41, "edge": "koboldcpp", "key": "maintenance", "koboldcpp": 82, "name": "Maintenance \u0026 community", "privategpt": 41, "weight": 7 }, { "by": 9, "edge": "privategpt", "key": "transparency", "koboldcpp": 55, "name": "Transparency \u0026 trust", "privategpt": 64, "weight": 7 } ], "summary": "KoboldCpp scores 62.1 (B) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability and transparency \u0026 trust. Both do local inference.", "tasks": null, "tutorials": [], "verdicts": { "koboldcpp": "One file runs text, image, speech and music models behind an OpenAPI 3.0.3 document that 1.124.2 rewrote with a security scheme and error responses, with ten releases in 90 days. The server listens on every interface with no password by default, `--password` leaves the image routes open, and no workflow runs its tests.", "privategpt": "PrivateGPT 1.0 is an Apache-2.0 server that gives local models an Anthropic-style messages API with retrieval, citations, tools and MCP, documented by an OpenAPI file and llms.txt. A default start has authentication off, listens on every interface and reads local paths given as URIs, and a public report of that was closed without a reply." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt", "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.min.md" }, "markdown": "KoboldCpp scores 62.1 (B) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability and transparency \u0026 trust. Both do local inference.\n\n- KoboldCpp: grade B, 62.1/100, rank #571 of 1486. Markdown https://www.anchorterminal.com/tools/koboldcpp.md · JSON https://www.anchorterminal.com/api/v1/tools/koboldcpp.json\n- PrivateGPT: grade D, 53.2/100, rank #954 of 1486. Markdown https://www.anchorterminal.com/tools/privategpt.md · JSON https://www.anchorterminal.com/api/v1/tools/privategpt.json\n- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md\n- All 280 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md\n\n## Which one, for what\n\n### KoboldCpp (B)\n\nGood 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.\n\nAhead on:\n- Security \u0026 auth, 38 against 32\n- Maintenance \u0026 community, 82 against 41\n\nAlso in its favour:\n- Free to start without a card\n- No incidents deducted, where PrivateGPT loses 7 points for them\n\nWatch for: With no `--host` the server accepts connections on all routable interfaces, and no password is set by default\n\n### PrivateGPT (D)\n\nGood for: A local backend for apps and agents that want an Anthropic-style API with document retrieval, citations and tools over local models.\n\nAhead on:\n- Reliability, 70 against 63\n- Transparency \u0026 trust, 64 against 55\n\nWatch for: Authentication is off by default, the server binds 0.0.0.0 and CORS allows every origin\n\n\n## Why the edge\n\n### Maintenance \u0026 community: KoboldCpp +41\n\n- KoboldCpp (82): Release 1.124.2 on 2 November 2026, tagged the day before this check, read from the tag dates in a clone since GitHub's release pages refuse our session (30). Ten tagged releases since 5 August 2026 (1.119 on 15 August, 1.120, 1.121, 1.122, 1.122.1, 1.123, 1.123.1, 1.124, 1.124.1 and 1.124.2) (20). 524 open issues and 5 open pull requests, with replies on all 24 of the newest open issues, per the 8 October check, not re-read on 3 November. The README points to GitHub Discussions and a Discord server. One person, Concedo, is the main author of the project's own commits (20 of 25). No client library. The official Docker image was last updated on 14 September 2026, before the six newest releases, and has 167,319 pulls (6 of 15). Upstream llama.cpp is merged regularly and builds run on GitHub Actions for five targets, but they are started by hand, `requirements.txt` pins only minimum versions and there's no Dependabot (6 of 10). 30 + 20 + 20 + 6 + 6 = 82.\n- PrivateGPT (41): The last release is 1.0.1, dated 16 June 2026 in the changelog and tagged 18 June, 141 days before the check (10 of 30). No release or dated changelog entry in the 90 days since 8 August (0 of 20). Maintainers commit most days and outside pull requests merged in October, but 23 pull requests are open and the stale bot closes issues, including two security reports, with no maintainer reply (13 of 25). Homebrew tap, wheel index and Docker images ship with releases, and Anthropic SDKs work against it. No product MCP server of its own, though it connects to remote MCP servers (10 of 15). Dependabot, uv.lock, actions pinned by commit since 19 October and dependency CVE upgrades in June, July and August (8 of 10). 10 + 0 + 13 + 10 + 8 = 41.\n\n### Transparency \u0026 trust: PrivateGPT +9\n\n- KoboldCpp (55): The editorial half. AGPL-3.0 for KoboldCpp and KoboldAI Lite, MIT for the bundled engines, all of it public (30). No privacy policy. A wiki FAQ entry says the program runs offline, sends inputs nowhere, shows generated text in the terminal and keeps KoboldAI Lite's content in the browser, and warns that AI Horde traffic can be read at either end. That agrees with `koboldcpp.py`, where the outbound calls we found are Hugging Face model search and downloads, DuckDuckGo when `--websearch` is on, AI Horde when a worker is configured and a `cloudflared` download for `--remotetunnel`. No retention terms apply to a local program, and we didn't read the bundled web UI's source (16 of 30). Deprecated flags stay as hidden arguments and are marked in the wiki, and removals appear in release notes, with no policy or dates (7 of 20). No telemetry, analytics or update check in `koboldcpp.py`, so nothing to opt out of. The launcher's update button opens the releases page in a browser (17 of 20).\n- PrivateGPT (64): Apache-2.0 (30). The OpenAPI description says no data leaves the execution environment, but the docs list cloud gateways as model providers and web search goes to outside services when enabled, and no privacy statement covers the software. Zylon's privacy policy covers its website (15 of 30). The 1.0 rewrite was marked as a breaking change in the changelog, and there is no deprecation policy (6 of 20). No telemetry to Zylon found in the source. OpenTelemetry tracing is off by default and its exporters write local files or to the owner's collector, documented on the observability page (16 of 20). 30 + 15 + 6 + 16 = 67.\n\n### Reliability: PrivateGPT +7\n\n- KoboldCpp (63): Read with the local-software lines, since KoboldCpp runs on the owner's machine with no hosted service. Single-file binaries on GitHub releases for Windows x64, Linux x64 and Apple Silicon macOS, with `nocuda` and `oldpc` variants and the hardware each suits stated in the README and release notes, plus the `koboldai/koboldcpp` Docker image. No package-manager release of the project's own, since the Nix and AUR packages are third-party (18 of 20). Eight workflows in the repository at 1.124.2, all builds started by hand. The AutoGuess test that ran on pull requests and three unofficial test builds were gone by 1.123 (13 October 2026), so no workflow runs the test suite. The macOS build, also started by hand, runs the built binary once on a small model as its only check. The `tests` folder holds 526 lines of Python in four files that nothing runs automatically (5 of 25). 524 open issues and 5 open pull requests with no stale bot, and replies on the 24 newest open issues, per the 8 October check, not re-read on 3 November, since GitHub's pages refuse our session (16 of 25). Sequential 1.x version numbers with notes on every release. 1.123 replaced `--multiuser` with `--queuelimit` and kept the old flag as a hidden deprecated argument, so existing launch commands still start. No changelog file and no stated semver rule (9 of 15). Version 1.124.2 (15). 18 + 5 + 16 + 9 + 15 = 63.\n- PrivateGPT (70): Read with the local-software lines, since PrivateGPT runs on the owner's hardware with no hosted service behind it. Homebrew tap, `uv tool install` from Zylon's own wheel index (not PyPI) and Docker Hub images `zylonai/private-gpt` 1.0.1 of 18 June 2026. Python 3.11 only, stated in pyproject.toml, and it needs a separate OpenAI-compatible model server (17 of 20). tests.yml runs format, lint, typecheck and the tests affected by each push on main, with the full suite of 217 test files on release pull requests. We couldn't see run results because the GitHub API refused us, and issue #2441 of 1 November reports the Claude spec update workflow failing (15 of 25). GitHub shows 3 open issues of about 1,250, because a stale bot closes quiet issues, two security reports among them, with no maintainer reply (12 of 25). release-please keeps a changelog with breaking changes marked, but no release has been cut since 1.0.1 while main carries 51 commits since 8 August, among them a breaking observability change of 23 October (11 of 15). Version 1.0.1 (15). 17 + 15 + 12 + 11 + 15 = 70.\n\n### Security \u0026 auth: KoboldCpp +6\n\n- KoboldCpp (38): Read with the tool checklist, credential model first. No credential by default. `--password` sets one shared key, sent as a Bearer token and never read from the query string, with a separate `--adminpassword` for admin routes. Keys have no scopes and change only with a restart, and the key doesn't cover image generation, upscaling, `/sdapi/v1/interrogate` or `/tts_to_audio`, as the `--help` text says (11 of 30). Admin mode, web search, MCP servers and the agent are off by default, the agent asks for confirmation of tool calls unless set to auto or off, and `/api/extra/shutdown` answers only local callers with `--singleinstance`. But with no `--host` the server listens on all routable interfaces, CORS reflects any Origin with credentials and allows private-network requests, so a web page or another machine on the network can call a server with no password (7 of 20). The server returns model output unless web search or MCP tools are on. The wiki lists flags for a public instance and the 1.122 notes tell users to take care when approving tool calls, with no guidance on untrusted content (7 of 15). Prompts and outputs print to the terminal unless `--quiet` is set and `/api/extra/perf` gives timing counters. No per-key record or log file was found (6 of 15). No `SECURITY.md` (none in the repository at 1.124.2), security.txt or bug bounty. GitHub private vulnerability reporting is open, and one advisory was published on 29 August 2026 (GHSA-qhvp-gj7g-rw26, Low) with the fix committed on 18 August, per the 8 October check (GitHub's pages weren't readable on 3 November and OSV holds no record of it). 1.124 masks passwords and keys in the startup print, and further bounds checks for the legacy loaders landed in 1.124, hardening that names no flaw (7 of 20).\n- PrivateGPT (32): Read with the tool checklist. Authentication is off by default, and when on it is one static secret compared with the whole `Authorization` header, with a sample `secret:key` value in settings.yaml. There are no per-user keys or scopes, `private-gpt serve` binds 0.0.0.0 by default and CORS allows every origin, so a default start answers anyone on the network. The docs disagree on the header (Bearer, Basic or an Anthropic key) (6 of 30). Tools are chosen per request and code execution has internet off by default, but bash runs as a host subprocess with resource limits, not in a container, and nothing asks for approval (6 of 20). Web fetch, web search, documents and MCP servers bring untrusted text to the model. A public prompt-injection report (#2270) was closed by the stale bot, and no guidance was found beyond a 19 October change that bounds tool output (3 of 15). OpenTelemetry traces cover every request, model call, tool and sandbox step, off by default, with local JSON lines exporters (10 of 15). SECURITY.md since 23 July 2026 asks for private reports through GitHub or Discord. No bounty, no certification, and the June and July security reports in issues were closed by a bot with no reply (7 of 20). 6 + 6 + 3 + 10 + 7 = 32.\n\n## Score by category\n\n| Category | Weight | KoboldCpp | PrivateGPT | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 63 | 70 | PrivateGPT +7 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 79 | 83 | PrivateGPT +4 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 64 | KoboldCpp +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 32 | KoboldCpp +6 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 82 | 41 | KoboldCpp +41 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 55 | 64 | PrivateGPT +9 |\n| Negative events | ≤15 | 0 | -7 | |\n| **Total** | | **62.1 · B** | **53.2 · D** | |\n\n## Facts side by side\n\n| Fact | KoboldCpp | PrivateGPT |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | LostRuins (Concedo) | Zylon (PriBAI Technology Spain S.L.) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| 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 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-02 | 2026-06-18 |\n| Terms last updated | no document linked | no date given |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | not read yet | not found in the text |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | not found in the text |\n| Arbitration or class-action waiver | not read yet | not found in the text |\n| Popularity | 12k stars | 58k stars |\n| Agent reviews | 2.8/5 (4) | none |\n\n## How the scores have moved\n\n### KoboldCpp\n\n- +1.1 on 3 November 2026 (C to B): product\n- +0.3 on 28 October 2026: new evidence\n- +0.2 on 27 October 2026: new evidence\n\n### PrivateGPT\n\nNo score change since it was listed.\n\n## Verdicts\n\n**KoboldCpp.** One file runs text, image, speech and music models behind an OpenAPI 3.0.3 document that 1.124.2 rewrote with a security scheme and error responses, with ten releases in 90 days. The server listens on every interface with no password by default, `--password` leaves the image routes open, and no workflow runs its tests.\n\n**PrivateGPT.** PrivateGPT 1.0 is an Apache-2.0 server that gives local models an Anthropic-style messages API with retrieval, citations, tools and MCP, documented by an OpenAPI file and llms.txt. A default start has authentication off, listens on every interface and reads local paths given as URIs, and a public report of that was closed without a reply.\n\n## Before you call either\n\n### KoboldCpp\n\n1. Start with `--host 127.0.0.1` and `--password`. The default listens on every interface with no key\n2. Send the password as `Authorization: Bearer \u003cpassword\u003e`. It is not read from the query string\n3. 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`\n4. Pass `max_length` or `max_tokens`. The default is 2,048 tokens unless `--defaultgenamt` changes it\n5. Send a `genkey` with each generation so `/api/extra/generate/check` and `/api/extra/abort` act on your request and not another caller's\n\n### PrivateGPT\n\n1. Turn on `server.auth` and bind to 127.0.0.1 before exposing an instance, since a default start answers any caller\n2. Point Anthropic SDKs or Claude Code at the server with `ANTHROPIC_BASE_URL=http://localhost:8080`\n3. Start an OpenAI-compatible model server and an embedding server first, and set `OPENAI_API_BASE` and `OPENAI_EMBEDDING_API_BASE`\n4. Pass ingested documents through `tool_context` to get answers with citations\n5. Treat web fetch, search and MCP results as untrusted, since PrivateGPT documents no prompt-injection handling\n\n## Questions\n\n### Which is better for AI agents, KoboldCpp or PrivateGPT?\n\nKoboldCpp scores 62.1 (B) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability and transparency \u0026 trust.\n\n### Do KoboldCpp and PrivateGPT need an API key?\n\nNeither needs a key.\n\n### Can an agent call KoboldCpp and PrivateGPT without installing anything?\n\nNo hosted endpoint is listed for KoboldCpp. No hosted endpoint is listed for PrivateGPT.\n\n### Are KoboldCpp and PrivateGPT open source?\n\nYes. 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). PrivateGPT is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.json, and with the fewest tokens: https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"koboldcpp\", \"b\": \"privategpt\"}`. From a terminal: `anchor compare koboldcpp privategpt`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/koboldcpp.json and https://www.anchorterminal.com/api/v1/tools/privategpt.json\n\n## Other comparisons with KoboldCpp or PrivateGPT\n\n- [AnythingLLM vs KoboldCpp](https://www.anchorterminal.com/compare/anythingllm-vs-koboldcpp.md)\n- [AnythingLLM vs PrivateGPT](https://www.anchorterminal.com/compare/anythingllm-vs-privategpt.md)\n- [Berth vs KoboldCpp](https://www.anchorterminal.com/compare/berth-vs-koboldcpp.md)\n- [Berth vs PrivateGPT](https://www.anchorterminal.com/compare/berth-vs-privategpt.md)\n- [BitRun vs KoboldCpp](https://www.anchorterminal.com/compare/bitrun-vs-koboldcpp.md)\n- [BitRun vs PrivateGPT](https://www.anchorterminal.com/compare/bitrun-vs-privategpt.md)\n- [Docker Model Runner vs KoboldCpp](https://www.anchorterminal.com/compare/docker-model-runner-vs-koboldcpp.md)\n- [Docker Model Runner vs PrivateGPT](https://www.anchorterminal.com/compare/docker-model-runner-vs-privategpt.md)\n- [Foundry Local vs KoboldCpp](https://www.anchorterminal.com/compare/foundry-local-vs-koboldcpp.md)\n- [Foundry Local vs PrivateGPT](https://www.anchorterminal.com/compare/foundry-local-vs-privategpt.md)\n- [Core vs KoboldCpp](https://www.anchorterminal.com/compare/ghost-core-vs-koboldcpp.md)\n- [Core vs PrivateGPT](https://www.anchorterminal.com/compare/ghost-core-vs-privategpt.md)\n- [GPT4All vs KoboldCpp](https://www.anchorterminal.com/compare/gpt4all-vs-koboldcpp.md)\n- [GPT4All vs PrivateGPT](https://www.anchorterminal.com/compare/gpt4all-vs-privategpt.md)\n- [HyperQwen vs KoboldCpp](https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.md)\n- [HyperQwen vs PrivateGPT](https://www.anchorterminal.com/compare/hyperqwen-vs-privategpt.md)\n- [Jan vs KoboldCpp](https://www.anchorterminal.com/compare/jan-vs-koboldcpp.md)\n- [Jan vs PrivateGPT](https://www.anchorterminal.com/compare/jan-vs-privategpt.md)\n- [Khoj vs KoboldCpp](https://www.anchorterminal.com/compare/khoj-vs-koboldcpp.md)\n- [KoboldCpp vs Lemonade](https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade.md)\n- [KoboldCpp vs llama.cpp](https://www.anchorterminal.com/compare/koboldcpp-vs-llama-cpp.md)\n- [KoboldCpp vs LM Studio](https://www.anchorterminal.com/compare/koboldcpp-vs-lm-studio.md)\n- [KoboldCpp vs LocalAI](https://www.anchorterminal.com/compare/koboldcpp-vs-localai.md)\n- [KoboldCpp vs MLX LM](https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.md)\n- [KoboldCpp vs Ollama](https://www.anchorterminal.com/compare/koboldcpp-vs-ollama.md)\n- [KoboldCpp vs Open WebUI](https://www.anchorterminal.com/compare/koboldcpp-vs-open-webui.md)\n- [KoboldCpp vs screenpipe](https://www.anchorterminal.com/compare/koboldcpp-vs-screenpipe.md)\n- [KoboldCpp vs TextGen](https://www.anchorterminal.com/compare/koboldcpp-vs-text-generation-webui.md)\n- [KoboldCpp vs vLLM](https://www.anchorterminal.com/compare/koboldcpp-vs-vllm.md)\n- [Lemonade vs PrivateGPT](https://www.anchorterminal.com/compare/lemonade-vs-privategpt.md)\n- [llama.cpp vs PrivateGPT](https://www.anchorterminal.com/compare/llama-cpp-vs-privategpt.md)\n- [LM Studio vs PrivateGPT](https://www.anchorterminal.com/compare/lm-studio-vs-privategpt.md)\n- [LocalAI vs PrivateGPT](https://www.anchorterminal.com/compare/localai-vs-privategpt.md)\n- [MLX LM vs PrivateGPT](https://www.anchorterminal.com/compare/mlx-lm-vs-privategpt.md)\n- [Ollama vs PrivateGPT](https://www.anchorterminal.com/compare/ollama-vs-privategpt.md)\n- [Open WebUI vs PrivateGPT](https://www.anchorterminal.com/compare/open-webui-vs-privategpt.md)\n- [PrivateGPT vs screenpipe](https://www.anchorterminal.com/compare/privategpt-vs-screenpipe.md)\n- [PrivateGPT vs TextGen](https://www.anchorterminal.com/compare/privategpt-vs-text-generation-webui.md)\n- [PrivateGPT vs vLLM](https://www.anchorterminal.com/compare/privategpt-vs-vllm.md)\n- [Khoj vs PrivateGPT](https://www.anchorterminal.com/compare/khoj-vs-privategpt.md)\n- [LocalGhost vs PrivateGPT](https://www.anchorterminal.com/compare/localghost-vs-privategpt.md)\n- [KoboldCpp vs Underdog](https://www.anchorterminal.com/compare/koboldcpp-vs-underdog.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "KoboldCpp vs PrivateGPT", "url": "" } ], "description": "KoboldCpp scores 62.1 (B) to PrivateGPT's 53.2 (D) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "KoboldCpp B 62.1", "PrivateGPT D 53.2", "scores" ], "h1": "KoboldCpp vs PrivateGPT", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/koboldcpp-vs-privategpt", "published": "2026-10-01", "section": "tools", "title": "KoboldCpp vs PrivateGPT for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt" }, "tokens": { "markdown": 5200, "slim": 2980 }, "version": 1 }