{ "data": { "a": { "slug": "jan", "name": "Jan", "vendor": "Menlo Research", "vendorUrl": "https://jan.ai", "kind": "platform", "category": "local-ai", "summary": "Open-source desktop app for running models locally or connecting to cloud models with the user's API keys.", "url": "https://www.anchorterminal.com/tools/jan", "markdownUrl": "https://www.anchorterminal.com/tools/jan.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/jan.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/jan.json", "dns": "jan.grade.anchorterminal.com", "repo": "https://github.com/janhq/jan", "license": "Apache-2.0", "transports": [ "http" ], "packages": [], "auth": "api-key", "authNotes": "The Local API Server takes one optional key set in Settings, empty by default, sent as `Authorization: Bearer` or `X-Api-Key`. There are no scopes and no keys per client. It binds to 127.0.0.1 by default and checks the Host header, and a Trusted Hosts list governs other hostnames and browser origins. Since 0.8.5 a 0.0.0.0 bind enforces that list (GHSA-x6p8-7cp8-c3p6), and since 0.8.8 untrusted browser origins are refused. `jan serve`, from the separately installed CLI, takes `--api-key`, empty by default. Cloud provider keys sit in the OS keyring since 0.8.4.", "pricing": "free", "pricingNotes": "Free and Apache-2.0, with no account and nothing to buy. Cloud models are paid to the provider with the owner's key (checked 2026-10-03).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-03).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 44800, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-03" }, "docsUrl": "https://www.jan.ai/docs/desktop/api-server", "openapi": "https://raw.githubusercontent.com/janhq/jan/main/src-tauri/static/openapi.json", "capabilities": [ "inference.local", "inference.open-weights", "agent.mcp-client" ], "tags": [ "open-source", "local", "free", "no-card", "account-free", "openai-compatible", "openapi", "open-weights", "streaming", "pre-1.0" ], "lastRelease": "2026-10-27", "graded": true, "anchor": { "graded": true, "score": 57.2, "grade": "C", "agentReady": false, "rank": 808, "ranked": true, "rankOf": 1510, "categoryRank": 7, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 46, "maintenance": 77, "payments": 60, "reliability": 61, "schema": 56, "security": 46, "transparency": 70 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "Apache-2.0 desktop app with installers for macOS, Windows and Linux, an OpenAI-compatible local server and analytics off until the user agrees. Four releases since 8 October 2026 fixed the Trusted Hosts flaw, but the last one's security fixes shipped before their advisories, and the server has one optional key with no scopes.", "bestFor": "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.", "strengths": [ "Apache-2.0, with installers for macOS, Windows and Linux plus Flathub and the Microsoft Store", "Product analytics off until the user agrees at first launch, with a toggle in Settings", "MCP tool calls ask for approval by default, and server-side tool execution through the API is off by default", "Four releases between 8 and 27 October 2026, each with a dated changelog entry", "A security policy with private reporting through GitHub advisories or email and acknowledgement within 3 business days" ], "weaknesses": [ "0.8.8's security fixes shipped on 28 October 2026 with advisories promised later, and none was published by 4 November", "One optional API key with no scopes, empty by default", "0.8.5 renamed the desktop executable and stopped bundling the `jan` CLI in a patch release", "New Hugging Face downloads go through Menlo's mirror at apps.jan.ai, which neither privacy page mentions", "No llms.txt, plain-text error bodies, and the OpenAPI file on the docs site is for the retired Cortex API" ], "agentNotes": [ "Ask the owner to start the server (Settings, Local API Server) or run `jan serve` from the separately installed CLI. 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", "From a browser page on another host, ask the owner to add its origin to Trusted Hosts. Since 0.8.8 untrusted origins are refused" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 57.2 } ], "editorialScores": { "ergonomics": 46, "maintenance": 77, "payments": 60, "reliability": 61, "schema": 56, "security": 46, "transparency": 66 }, "provenanceScore": 74, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "flatpak install flathub ai.jan.Jan # or the macOS, Windows and Linux installers at https://jan.ai", "http": "curl http://127.0.0.1:1337/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer secret-key-123\" \\\n -d '{\"model\": \"YOUR_MODEL_ID\", \"messages\": [{\"role\": \"user\", \"content\": \"Tell me a joke.\"}]}'", "claudeCode": "jan launch claude --model janhq/Jan-code-4b-gguf", "headless": { "command": "jan serve janhq/Jan-code-4b-gguf --detach" } }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/jan" }, "area": "models", "provenance": { "legalEntity": "Menlo Research Pte Ltd", "domain": "jan.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://www.jan.ai/docs/desktop/privacy-policy", "statusPage": "", "changelog": "https://www.jan.ai/changelog", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "The privacy policy (last updated 16 January 2025) names Menlo Research Pte Ltd, and the repository's LICENSE names Menlo Research.", "We found no terms of use on jan.ai or in the docs source.", "jan.ai/.well-known/security.txt returned 404 on 3 October. SECURITY.md in the repository, added on 26 October 2026, takes reports through GitHub Security Advisories or security@jan.ai.", "The registration date is carried from the earlier listing.", "There's no hosted endpoint. The server answers on the owner's machine, at 127.0.0.1:1337 by default." ], "score": 74 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/jan.json", "live": { "slug": "jan", "versions": [ { "registry": "github", "name": "janhq/jan", "version": "v0.8.8", "released": "2026-10-28", "seenAt": "2026-11-06T23:35:38.295493365Z" } ], "githubStars": 45537, "securityTxt": { "url": "https://jan.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:32.407850894Z" }, "domain": { "domain": "jan.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/jan.ai", "checkedAt": "2026-11-01T14:12:01.612504635Z" }, "pages": [ { "url": "https://www.jan.ai/changelog", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:30:20.738572219Z", "changedAt": "2026-10-28T04:51:24.881001Z", "fingerprint": "1186b9afa570" }, { "url": "https://www.jan.ai/docs/desktop/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:30:22.920133272Z", "changedAt": "2026-10-16T22:38:03.339905618Z", "fingerprint": "0830daaedd2a" } ], "github": { "repo": "janhq/jan", "checkedAt": "2026-11-02T08:57:06.324523168Z", "stars": 45296, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T08:51:46Z", "openIssues": 399, "openPRs": 170, "issuesOpened90d": 341, "issuesClosed90d": 287, "prsMerged90d": 349, "ci": { "branch": "main", "runs": 50, "success": 23, "failure": 0, "other": 27, "latest": "success", "latestAt": "2026-11-02T08:01:53Z" }, "advisories": [ { "ghsa": "GHSA-63g6-28fr-v4rm", "severity": "low", "published": "2026-10-29T10:44:59Z" }, { "ghsa": "GHSA-3g72-3hpm-xrwj", "severity": "high", "published": "2026-10-29T10:44:57Z" }, { "ghsa": "GHSA-g9j3-j6vx-jqf7", "severity": "medium", "published": "2026-10-29T10:44:55Z" }, { "ghsa": "GHSA-p283-6wfr-f93j", "severity": "critical", "published": "2026-10-29T10:44:52Z" }, { "ghsa": "GHSA-x6p8-7cp8-c3p6", "severity": "high", "published": "2026-10-29T10:44:50Z" }, { "ghsa": "GHSA-7j4g-mj5j-p842", "severity": "medium", "published": "2026-10-29T10:44:47Z" }, { "ghsa": "GHSA-j2wh-9mvv-j5w6", "severity": "medium", "published": "2026-10-29T10:44:45Z" }, { "ghsa": "GHSA-9qq3-j6jv-qmpv", "severity": "high", "published": "2026-10-29T10:44:42Z" }, { "ghsa": "GHSA-959c-grmq-2738", "severity": "high", "published": "2026-10-29T10:44:40Z" }, { "ghsa": "GHSA-66pg-h682-8cmf", "severity": "high", "published": "2026-10-29T10:44:37Z" }, { "ghsa": "GHSA-j6hv-vhmg-vpj6", "severity": "critical", "published": "2026-10-29T10:44:35Z" } ], "replies": { "sampled": 25, "unanswered": 21, "medianDays": 2.8 } }, "updatedAt": "2026-11-07T16:00:32.407850894Z" } }, "answer": "Jan scores 57.2 (C) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability, schema \u0026 documentation and agent ergonomics.", "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": 960, "ranked": true, "rankOf": 1510, "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": 36, "category": "maintenance", "leads": "jan", "name": "Maintenance \u0026 community", "reasons": { "a": "0.8.8, tagged on 27 October 2026 and dated 28 October in the changelog, 8 days before this check (30). Four releases since 6 August, 0.8.5 on 8 October, 0.8.6 on 9 October, 0.8.7 on 19 October and 0.8.8 on 27 October, each with a dated changelog entry (20). New issues get labels and milestones, per the 3 October check, and reply times couldn't be read (15). No MCP registry entry read and no SDK in the stable release. The 0.8.5 notes say agent work stays in the nightly channel (3). A Dependabot config, CI on pushes to main and a pinned Rust toolchain (1.98.0) (9). 30 + 20 + 15 + 3 + 9 = 77.", "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": 77, "b": 41 } }, { "by": 27, "category": "schema", "leads": "privategpt", "name": "Schema \u0026 documentation", "reasons": { "a": "Read with the API lines. The server serves an OpenAPI 3.0 file at /openapi.json with a Swagger page at /, covering 4 paths (models, chat completions, messages, orchestrations) with typed schemas and a bearer scheme, but only 200 responses, and /completions, /embeddings and /messages/count_tokens aren't in it. The spec on the docs site is the retired Cortex API (12). No llms.txt at jan.ai or www.jan.ai (404 on 3 October), and no Markdown copies of pages found (0). The API server page explains each setting and when to change it (127.0.0.1 or 0.0.0.0, the key, CORS for browser clients, server-side tool execution) (12). Request schemas in the spec mark required fields and use enums, while the extra llama.cpp parameters and errors are described only in prose (10). One curl example, and a troubleshooting list for connection refused, 401, 404 and CORS errors. Error bodies are plain text (9). A /v1 prefix, semver releases and a dated changelog with GitHub release notes (13). No llms.txt at www.jan.ai on 4 November (404). 12 + 0 + 12 + 10 + 9 + 13 = 56.", "b": "An OpenAPI file of 38 paths in the repository (fern/openapi/openapi.json, version 1.0.1), also served by each instance at /openapi.json, with the messages API modelled on Anthropic's (25). docs.privategpt.dev serves llms.txt, a Markdown copy of every page and a docs MCP server (10). The docs explain each endpoint group, startup and model discovery, and a compatibility table says which parts of the Claude API are supported, partial or missing, such as prompt caching and OAuth (15 of 20). Pydantic models with literal type discriminators and required fields, while settings and tool context are wide objects (12 of 15). curl examples for each guide and a `/v1/messages/validate` route, with error shapes not documented as a list (9 of 15). `/v1` paths and a dated changelog, though releases trail main by more than four months (12 of 15). 25 + 10 + 15 + 12 + 9 + 12 = 83." }, "scores": { "a": 56, "b": 83 } }, { "by": 18, "category": "ergonomics", "leads": "privategpt", "name": "Agent ergonomics", "reasons": { "a": "Read with the API lines. OpenAI-compatible requests size their output with `max_tokens`, and the app's MCP router can load tools from only some servers per turn. 0.8.5 caps tool results before they enter the conversation (15). `GET /models` lists everything, with no paging or filters (8). Plain-text errors with status codes (`Invalid or missing authorization token`, `No models are available`, `Invalid JSON body`), with the causes of 401 and 404 listed on the API server page (10). Stateless chat completions are safe to repeat. No retry or idempotency guidance (6). The defaults suit a local caller (127.0.0.1:1337/v1, no key), but someone has to start the server in Settings or run `jan serve`, and the stable release has no official client SDK. Any OpenAI or Anthropic SDK works (7). 15 + 8 + 10 + 6 + 7 = 46.", "b": "Read for an HTTP API an agent calls on a local instance. Token counting, `top_k` style retrieval settings, citation output and response byte caps let a caller size context (18 of 25). Artifact listing by namespace and retrieval filters, with no documented cursor pagination (12 of 20). FastAPI validation errors name the field and the validate route checks a request before running it, but there is no error catalogue (12 of 20). Async messages and ingestion return task ids with status, cancel and delete routes. No idempotency keys were found (10 of 20). Anthropic SDKs and Claude Code work by pointing `ANTHROPIC_BASE_URL` at the server, but a model server and an embedding server have to be configured first (12 of 15). 18 + 12 + 12 + 10 + 12 = 64." }, "scores": { "a": 46, "b": 64 } }, { "by": 14, "category": "security", "leads": "jan", "name": "Security \u0026 auth", "reasons": { "a": "Read with the tool checklist. One optional key typed into Settings, empty by default, accepted as `Authorization: Bearer` or `X-Api-Key`, with no scopes, names or keys per client. `jan serve --api-key` defaults to empty too (10). The app asks before each MCP tool call by default, with an allow-all switch, and server-side tool execution through the API is off by default for every endpoint. The key can't be limited. The 0.0.0.0 bind that dropped Trusted Hosts in 0.8.4 was fixed in 0.8.5 on 8 October 2026, and 0.8.8 checks the Origin of browser requests (11). The docs advise a key when binding to 0.0.0.0 but say nothing on injected instructions in tool results. 0.8.5 caps tool-result size, and 0.8.8 opens links from replies and tool results in the system browser (5). Verbose server logs are on by default with a Server Logs view (10). SECURITY.md, added on 26 October 2026, takes reports through GitHub Security Advisories or security@jan.ai, promises acknowledgement within 3 business days and credits researchers. No bounty and no security.txt at jan.ai. CVE-2026-66005, published by VulnCheck, records the 0.0.0.0 flaw, and the 0.8.8 notes say advisories for its fixes will follow (10). 10 + 11 + 5 + 10 + 10 = 46.", "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": 46, "b": 32 } }, { "by": 9, "category": "reliability", "leads": "privategpt", "name": "Reliability", "reasons": { "a": "Read with the local-software lines, since Jan runs on the owner's machine with no hosted service behind its API. Installers for macOS 13.6 or later, Windows 10 or later and Linux (.deb and AppImage), plus Flathub and the Microsoft Store, with requirements in the README and the install guides (20). The Linter \u0026 Test workflow runs `make test-ts` and `make test-ci-rust` on pushes to main that touch the app's code. Its run results are on GitHub's pages, which our reader can't open, so the result is unread and the line takes 15 of 25. 409 open issues and 133 open pull requests on 3 October, with labels, milestones and a stale bot that closes issues after 180 days without activity, not re-read on 4 November (15). Semver tags and a dated changelog per release with Migration notes, but 0.8.5 renamed the desktop executable and stopped bundling the `jan` CLI in a patch release (11, held as a partial). 0.8.8, pre-1.0 (0). 20 + 15 + 15 + 11 + 0 = 61.", "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": 61, "b": 70 } }, { "by": 6, "category": "transparency", "leads": "jan", "name": "Transparency \u0026 trust", "reasons": { "a": "Apache-2.0 for the app, the server and the CLI (30). The privacy policy (Menlo Research Pte Ltd, last updated 16 January 2025) says analytics are opt-in, tied to a random ID, sent to PostHog EU and kept up to 12 months. A second privacy page still names Cortex, a retired engine, and says usage logs never leave the computer. Neither mentions the update check to apps.jan.ai or that new model downloads from Hugging Face go through Menlo's mirror at apps.jan.ai first (14). No deprecation policy. The 0.8.4 and 0.8.5 notes have Migration sections and the 0.8.8 notes list what users might notice, each on release day (6). Analytics are asked for at first launch and off until accepted (the code opts out by default, turns off autocapture and session recording and strips URL properties), with a toggle under Settings, Privacy. The update check and the download mirror aren't disclosed (16). 30 + 14 + 6 + 16 = 66.", "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": 70, "b": 64 } } ], "facts": [ { "a": "Platform", "b": "HTTP API", "name": "Kind" }, { "a": "Menlo Research", "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": "API key", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-27", "b": "2026-06-18", "name": "Last release" }, { "a": "no document linked", "b": "no date given", "name": "Terms last updated" }, { "a": "2025-01-16", "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": "45k stars", "b": "58k stars", "name": "Popularity" }, { "a": "2/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Jan scores 57.2 (C) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability, schema \u0026 documentation and agent ergonomics.", "question": "Which is better for AI agents, Jan or PrivateGPT?" }, { "answer": "No hosted endpoint is listed for Jan. No hosted endpoint is listed for PrivateGPT.", "question": "Can an agent call Jan and PrivateGPT without installing anything?" }, { "answer": "Yes. Jan is open source (Apache-2.0). PrivateGPT is open source (Apache-2.0).", "question": "Are Jan and PrivateGPT open source?" } ], "goodFor": [ { "aheadOn": [ "Security \u0026 auth, 46 against 32", "Maintenance \u0026 community, 77 against 41", "Transparency \u0026 trust, 70 against 64" ], "also": [ "Free to start without a card", "No incidents deducted, where PrivateGPT loses 7 points for them" ], "goodFor": "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.", "slug": "jan", "watchFor": "0.8.8's security fixes shipped on 28 October 2026 with advisories promised later, and none was published by 4 November" }, { "aheadOn": [ "Reliability, 70 against 61", "Schema \u0026 documentation, 83 against 56", "Agent ergonomics, 64 against 46" ], "also": [ "No key needed to call it" ], "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": { "jan": [ { "causes": [ "security", "product", "correction", "event" ], "date": "2026-11-04", "delta": 5.8, "from": 51.4, "fromGrade": "D", "to": 57.2, "toGrade": "C" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.1, "from": 51.3, "fromGrade": "D", "to": 51.4, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.1, "from": 51.4, "fromGrade": "D", "to": 51.3, "toGrade": "D" } ], "privategpt": null }, "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-jan.json", "title": "AnythingLLM vs Jan", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-jan" }, { "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-jan.json", "title": "Berth vs Jan", "url": "https://www.anchorterminal.com/compare/berth-vs-jan" }, { "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-jan.json", "title": "BitRun vs Jan", "url": "https://www.anchorterminal.com/compare/bitrun-vs-jan" }, { "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-jan.json", "title": "Docker Model Runner vs Jan", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-jan" }, { "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-jan.json", "title": "Foundry Local vs Jan", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-jan" }, { "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-jan.json", "title": "Core vs Jan", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-jan" }, { "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-jan.json", "title": "GPT4All vs Jan", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-jan" }, { "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-jan.json", "title": "HyperQwen vs Jan", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-jan" }, { "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-khoj.json", "title": "Jan vs Khoj", "url": "https://www.anchorterminal.com/compare/jan-vs-khoj" }, { "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-lemonade.json", "title": "Jan vs Lemonade", "url": "https://www.anchorterminal.com/compare/jan-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-llama-cpp.json", "title": "Jan vs llama.cpp", "url": "https://www.anchorterminal.com/compare/jan-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-lm-studio.json", "title": "Jan vs LM Studio", "url": "https://www.anchorterminal.com/compare/jan-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-localai.json", "title": "Jan vs LocalAI", "url": "https://www.anchorterminal.com/compare/jan-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-mlx-lm.json", "title": "Jan vs MLX LM", "url": "https://www.anchorterminal.com/compare/jan-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-ollama.json", "title": "Jan vs Ollama", "url": "https://www.anchorterminal.com/compare/jan-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-open-webui.json", "title": "Jan vs Open WebUI", "url": "https://www.anchorterminal.com/compare/jan-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-screenpipe.json", "title": "Jan vs screenpipe", "url": "https://www.anchorterminal.com/compare/jan-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-text-generation-webui.json", "title": "Jan vs TextGen", "url": "https://www.anchorterminal.com/compare/jan-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-vllm.json", "title": "Jan vs vLLM", "url": "https://www.anchorterminal.com/compare/jan-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.json", "title": "KoboldCpp vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt" }, { "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/jan-vs-underdog.json", "title": "Jan vs Underdog", "url": "https://www.anchorterminal.com/compare/jan-vs-underdog" } ], "panel": null, "scores": [ { "by": 9, "edge": "privategpt", "jan": 61, "key": "reliability", "name": "Reliability", "privategpt": 70, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 27, "edge": "privategpt", "jan": 56, "key": "schema", "name": "Schema \u0026 documentation", "privategpt": 83, "weight": 13 }, { "by": 18, "edge": "privategpt", "jan": 46, "key": "ergonomics", "name": "Agent ergonomics", "privategpt": 64, "weight": 13 }, { "by": 14, "edge": "jan", "jan": 46, "key": "security", "name": "Security \u0026 auth", "privategpt": 32, "weight": 14 }, { "by": 0, "edge": "", "jan": 60, "key": "payments", "name": "Payments \u0026 pricing", "privategpt": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 36, "edge": "jan", "jan": 77, "key": "maintenance", "name": "Maintenance \u0026 community", "privategpt": 41, "weight": 7 }, { "by": 6, "edge": "jan", "jan": 70, "key": "transparency", "name": "Transparency \u0026 trust", "privategpt": 64, "weight": 7 } ], "summary": "Jan scores 57.2 (C) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability, schema \u0026 documentation and agent ergonomics. Both do local inference.", "tasks": null, "tutorials": [], "verdicts": { "jan": "Apache-2.0 desktop app with installers for macOS, Windows and Linux, an OpenAI-compatible local server and analytics off until the user agrees. Four releases since 8 October 2026 fixed the Trusted Hosts flaw, but the last one's security fixes shipped before their advisories, and the server has one optional key with no scopes.", "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/jan-vs-privategpt", "json": "https://www.anchorterminal.com/compare/jan-vs-privategpt.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/jan-vs-privategpt.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/jan-vs-privategpt.min.md" }, "markdown": "Jan scores 57.2 (C) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability, schema \u0026 documentation and agent ergonomics. Both do local inference.\n\n- Jan: grade C, 57.2/100, rank #808 of 1510. Markdown https://www.anchorterminal.com/tools/jan.md · JSON https://www.anchorterminal.com/api/v1/tools/jan.json\n- PrivateGPT: grade D, 53.2/100, rank #960 of 1510. 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### Jan (C)\n\nGood 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.\n\nAhead on:\n- Security \u0026 auth, 46 against 32\n- Maintenance \u0026 community, 77 against 41\n- Transparency \u0026 trust, 70 against 64\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: 0.8.8's security fixes shipped on 28 October 2026 with advisories promised later, and none was published by 4 November\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 61\n- Schema \u0026 documentation, 83 against 56\n- Agent ergonomics, 64 against 46\n\nAlso in its favour:\n- No key needed to call it\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: Jan +36\n\n- Jan (77): 0.8.8, tagged on 27 October 2026 and dated 28 October in the changelog, 8 days before this check (30). Four releases since 6 August, 0.8.5 on 8 October, 0.8.6 on 9 October, 0.8.7 on 19 October and 0.8.8 on 27 October, each with a dated changelog entry (20). New issues get labels and milestones, per the 3 October check, and reply times couldn't be read (15). No MCP registry entry read and no SDK in the stable release. The 0.8.5 notes say agent work stays in the nightly channel (3). A Dependabot config, CI on pushes to main and a pinned Rust toolchain (1.98.0) (9). 30 + 20 + 15 + 3 + 9 = 77.\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### Schema \u0026 documentation: PrivateGPT +27\n\n- Jan (56): Read with the API lines. The server serves an OpenAPI 3.0 file at /openapi.json with a Swagger page at /, covering 4 paths (models, chat completions, messages, orchestrations) with typed schemas and a bearer scheme, but only 200 responses, and /completions, /embeddings and /messages/count_tokens aren't in it. The spec on the docs site is the retired Cortex API (12). No llms.txt at jan.ai or www.jan.ai (404 on 3 October), and no Markdown copies of pages found (0). The API server page explains each setting and when to change it (127.0.0.1 or 0.0.0.0, the key, CORS for browser clients, server-side tool execution) (12). Request schemas in the spec mark required fields and use enums, while the extra llama.cpp parameters and errors are described only in prose (10). One curl example, and a troubleshooting list for connection refused, 401, 404 and CORS errors. Error bodies are plain text (9). A /v1 prefix, semver releases and a dated changelog with GitHub release notes (13). No llms.txt at www.jan.ai on 4 November (404). 12 + 0 + 12 + 10 + 9 + 13 = 56.\n- PrivateGPT (83): An OpenAPI file of 38 paths in the repository (fern/openapi/openapi.json, version 1.0.1), also served by each instance at /openapi.json, with the messages API modelled on Anthropic's (25). docs.privategpt.dev serves llms.txt, a Markdown copy of every page and a docs MCP server (10). The docs explain each endpoint group, startup and model discovery, and a compatibility table says which parts of the Claude API are supported, partial or missing, such as prompt caching and OAuth (15 of 20). Pydantic models with literal type discriminators and required fields, while settings and tool context are wide objects (12 of 15). curl examples for each guide and a `/v1/messages/validate` route, with error shapes not documented as a list (9 of 15). `/v1` paths and a dated changelog, though releases trail main by more than four months (12 of 15). 25 + 10 + 15 + 12 + 9 + 12 = 83.\n\n### Agent ergonomics: PrivateGPT +18\n\n- Jan (46): Read with the API lines. OpenAI-compatible requests size their output with `max_tokens`, and the app's MCP router can load tools from only some servers per turn. 0.8.5 caps tool results before they enter the conversation (15). `GET /models` lists everything, with no paging or filters (8). Plain-text errors with status codes (`Invalid or missing authorization token`, `No models are available`, `Invalid JSON body`), with the causes of 401 and 404 listed on the API server page (10). Stateless chat completions are safe to repeat. No retry or idempotency guidance (6). The defaults suit a local caller (127.0.0.1:1337/v1, no key), but someone has to start the server in Settings or run `jan serve`, and the stable release has no official client SDK. Any OpenAI or Anthropic SDK works (7). 15 + 8 + 10 + 6 + 7 = 46.\n- PrivateGPT (64): Read for an HTTP API an agent calls on a local instance. Token counting, `top_k` style retrieval settings, citation output and response byte caps let a caller size context (18 of 25). Artifact listing by namespace and retrieval filters, with no documented cursor pagination (12 of 20). FastAPI validation errors name the field and the validate route checks a request before running it, but there is no error catalogue (12 of 20). Async messages and ingestion return task ids with status, cancel and delete routes. No idempotency keys were found (10 of 20). Anthropic SDKs and Claude Code work by pointing `ANTHROPIC_BASE_URL` at the server, but a model server and an embedding server have to be configured first (12 of 15). 18 + 12 + 12 + 10 + 12 = 64.\n\n### Security \u0026 auth: Jan +14\n\n- Jan (46): Read with the tool checklist. One optional key typed into Settings, empty by default, accepted as `Authorization: Bearer` or `X-Api-Key`, with no scopes, names or keys per client. `jan serve --api-key` defaults to empty too (10). The app asks before each MCP tool call by default, with an allow-all switch, and server-side tool execution through the API is off by default for every endpoint. The key can't be limited. The 0.0.0.0 bind that dropped Trusted Hosts in 0.8.4 was fixed in 0.8.5 on 8 October 2026, and 0.8.8 checks the Origin of browser requests (11). The docs advise a key when binding to 0.0.0.0 but say nothing on injected instructions in tool results. 0.8.5 caps tool-result size, and 0.8.8 opens links from replies and tool results in the system browser (5). Verbose server logs are on by default with a Server Logs view (10). SECURITY.md, added on 26 October 2026, takes reports through GitHub Security Advisories or security@jan.ai, promises acknowledgement within 3 business days and credits researchers. No bounty and no security.txt at jan.ai. CVE-2026-66005, published by VulnCheck, records the 0.0.0.0 flaw, and the 0.8.8 notes say advisories for its fixes will follow (10). 10 + 11 + 5 + 10 + 10 = 46.\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### Reliability: PrivateGPT +9\n\n- Jan (61): Read with the local-software lines, since Jan runs on the owner's machine with no hosted service behind its API. Installers for macOS 13.6 or later, Windows 10 or later and Linux (.deb and AppImage), plus Flathub and the Microsoft Store, with requirements in the README and the install guides (20). The Linter \u0026 Test workflow runs `make test-ts` and `make test-ci-rust` on pushes to main that touch the app's code. Its run results are on GitHub's pages, which our reader can't open, so the result is unread and the line takes 15 of 25. 409 open issues and 133 open pull requests on 3 October, with labels, milestones and a stale bot that closes issues after 180 days without activity, not re-read on 4 November (15). Semver tags and a dated changelog per release with Migration notes, but 0.8.5 renamed the desktop executable and stopped bundling the `jan` CLI in a patch release (11, held as a partial). 0.8.8, pre-1.0 (0). 20 + 15 + 15 + 11 + 0 = 61.\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### Transparency \u0026 trust: Jan +6\n\n- Jan (70): Apache-2.0 for the app, the server and the CLI (30). The privacy policy (Menlo Research Pte Ltd, last updated 16 January 2025) says analytics are opt-in, tied to a random ID, sent to PostHog EU and kept up to 12 months. A second privacy page still names Cortex, a retired engine, and says usage logs never leave the computer. Neither mentions the update check to apps.jan.ai or that new model downloads from Hugging Face go through Menlo's mirror at apps.jan.ai first (14). No deprecation policy. The 0.8.4 and 0.8.5 notes have Migration sections and the 0.8.8 notes list what users might notice, each on release day (6). Analytics are asked for at first launch and off until accepted (the code opts out by default, turns off autocapture and session recording and strips URL properties), with a toggle under Settings, Privacy. The update check and the download mirror aren't disclosed (16). 30 + 14 + 6 + 16 = 66.\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## Score by category\n\n| Category | Weight | Jan | PrivateGPT | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 61 | 70 | PrivateGPT +9 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 56 | 83 | PrivateGPT +27 |\n| Agent ergonomics | 13% (16.2 this run) | 46 | 64 | PrivateGPT +18 |\n| Security \u0026 auth | 14% (17.5 this run) | 46 | 32 | Jan +14 |\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) | 77 | 41 | Jan +36 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 70 | 64 | Jan +6 |\n| Negative events | ≤15 | 0 | -7 | |\n| **Total** | | **57.2 · C** | **53.2 · D** | |\n\n## Facts side by side\n\n| Fact | Jan | PrivateGPT |\n| --- | --- | --- |\n| Kind | Platform | HTTP API |\n| Vendor | Menlo Research | Zylon (PriBAI Technology Spain S.L.) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-27 | 2026-06-18 |\n| Terms last updated | no document linked | no date given |\n| Privacy policy last updated | 2025-01-16 | 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 | 45k stars | 58k stars |\n| Agent reviews | 2/5 (2) | none |\n\n## How the scores have moved\n\n### Jan\n\n- +5.8 on 4 November 2026 (D to C): security, product, correction, negative event\n- +0.1 on 27 October 2026: checklist\n- -0.1 on 8 October 2026: checklist\n\n### PrivateGPT\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Jan.** Apache-2.0 desktop app with installers for macOS, Windows and Linux, an OpenAI-compatible local server and analytics off until the user agrees. Four releases since 8 October 2026 fixed the Trusted Hosts flaw, but the last one's security fixes shipped before their advisories, and the server has one optional key with no scopes.\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### Jan\n\n1. Ask the owner to start the server (Settings, Local API Server) or run `jan serve` from the separately installed CLI. Nothing listens until then\n2. Call http://127.0.0.1:1337/v1 for the app and localhost:6767/v1 for `jan serve`. The ports differ\n3. Read /openapi.json from the running server, not the spec on the docs site, which describes the retired Cortex API\n4. Branch on the status code. Error bodies are plain text\n5. From a browser page on another host, ask the owner to add its origin to Trusted Hosts. Since 0.8.8 untrusted origins are refused\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, Jan or PrivateGPT?\n\nJan scores 57.2 (C) on agent readiness against PrivateGPT's 53.2 (D), and leads in 3 of 7 scored categories. PrivateGPT leads on reliability, schema \u0026 documentation and agent ergonomics.\n\n### Can an agent call Jan and PrivateGPT without installing anything?\n\nNo hosted endpoint is listed for Jan. No hosted endpoint is listed for PrivateGPT.\n\n### Are Jan and PrivateGPT open source?\n\nYes. Jan is open source (Apache-2.0). PrivateGPT is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/jan-vs-privategpt.json, and with the fewest tokens: https://www.anchorterminal.com/compare/jan-vs-privategpt.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"jan\", \"b\": \"privategpt\"}`. From a terminal: `anchor compare jan privategpt`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/jan.json and https://www.anchorterminal.com/api/v1/tools/privategpt.json\n\n## Other comparisons with Jan or PrivateGPT\n\n- [AnythingLLM vs Jan](https://www.anchorterminal.com/compare/anythingllm-vs-jan.md)\n- [AnythingLLM vs PrivateGPT](https://www.anchorterminal.com/compare/anythingllm-vs-privategpt.md)\n- [Berth vs Jan](https://www.anchorterminal.com/compare/berth-vs-jan.md)\n- [Berth vs PrivateGPT](https://www.anchorterminal.com/compare/berth-vs-privategpt.md)\n- [BitRun vs Jan](https://www.anchorterminal.com/compare/bitrun-vs-jan.md)\n- [BitRun vs PrivateGPT](https://www.anchorterminal.com/compare/bitrun-vs-privategpt.md)\n- [Docker Model Runner vs Jan](https://www.anchorterminal.com/compare/docker-model-runner-vs-jan.md)\n- [Docker Model Runner vs PrivateGPT](https://www.anchorterminal.com/compare/docker-model-runner-vs-privategpt.md)\n- [Foundry Local vs Jan](https://www.anchorterminal.com/compare/foundry-local-vs-jan.md)\n- [Foundry Local vs PrivateGPT](https://www.anchorterminal.com/compare/foundry-local-vs-privategpt.md)\n- [Core vs Jan](https://www.anchorterminal.com/compare/ghost-core-vs-jan.md)\n- [Core vs PrivateGPT](https://www.anchorterminal.com/compare/ghost-core-vs-privategpt.md)\n- [GPT4All vs Jan](https://www.anchorterminal.com/compare/gpt4all-vs-jan.md)\n- [GPT4All vs PrivateGPT](https://www.anchorterminal.com/compare/gpt4all-vs-privategpt.md)\n- [HyperQwen vs Jan](https://www.anchorterminal.com/compare/hyperqwen-vs-jan.md)\n- [HyperQwen vs PrivateGPT](https://www.anchorterminal.com/compare/hyperqwen-vs-privategpt.md)\n- [Jan vs Khoj](https://www.anchorterminal.com/compare/jan-vs-khoj.md)\n- [Jan vs KoboldCpp](https://www.anchorterminal.com/compare/jan-vs-koboldcpp.md)\n- [Jan vs Lemonade](https://www.anchorterminal.com/compare/jan-vs-lemonade.md)\n- [Jan vs llama.cpp](https://www.anchorterminal.com/compare/jan-vs-llama-cpp.md)\n- [Jan vs LM Studio](https://www.anchorterminal.com/compare/jan-vs-lm-studio.md)\n- [Jan vs LocalAI](https://www.anchorterminal.com/compare/jan-vs-localai.md)\n- [Jan vs MLX LM](https://www.anchorterminal.com/compare/jan-vs-mlx-lm.md)\n- [Jan vs Ollama](https://www.anchorterminal.com/compare/jan-vs-ollama.md)\n- [Jan vs Open WebUI](https://www.anchorterminal.com/compare/jan-vs-open-webui.md)\n- [Jan vs screenpipe](https://www.anchorterminal.com/compare/jan-vs-screenpipe.md)\n- [Jan vs TextGen](https://www.anchorterminal.com/compare/jan-vs-text-generation-webui.md)\n- [Jan vs vLLM](https://www.anchorterminal.com/compare/jan-vs-vllm.md)\n- [KoboldCpp vs PrivateGPT](https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.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- [Jan vs Underdog](https://www.anchorterminal.com/compare/jan-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": "Jan vs PrivateGPT", "url": "" } ], "description": "Jan scores 57.2 (C) to PrivateGPT's 53.2 (D) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Jan C 57.2", "PrivateGPT D 53.2", "scores" ], "h1": "Jan vs PrivateGPT", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/jan-vs-privategpt", "published": "2026-10-01", "section": "tools", "title": "Jan vs PrivateGPT for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/jan-vs-privategpt" }, "tokens": { "markdown": 5600, "slim": 3480 }, "version": 1 }