{ "data": { "a": { "slug": "ollama", "name": "Ollama", "vendor": "Ollama Inc.", "vendorUrl": "https://ollama.com", "kind": "http-api", "category": "local-ai", "summary": "Open-source model runner for macOS, Windows and Linux, with a local API and a library of downloadable models.", "url": "https://www.anchorterminal.com/tools/ollama", "markdownUrl": "https://www.anchorterminal.com/tools/ollama.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ollama.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ollama.json", "dns": "ollama.grade.anchorterminal.com", "repo": "https://github.com/ollama/ollama", "license": "MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "docker.io/ollama/ollama" }, { "registry": "pypi", "name": "ollama" }, { "registry": "npm", "name": "ollama" } ], "auth": "none", "authNotes": "The local API at http://localhost:11434 takes no credential. It binds 127.0.0.1, answers a foreign Host header with 403 while bound to loopback, and allows cross-origin calls from 127.0.0.1 and 0.0.0.0 unless `OLLAMA_ORIGINS` adds more. Anything that reaches the port can generate, pull, push, create, copy and delete models. Cloud models through the local server need `ollama signin`, which signs requests with the install's own key. Direct calls to https://ollama.com/api and /v1 need a Bearer API key from ollama.com/settings/keys, which doesn't expire and has no scopes, and is revoked from the same page (https://github.com/ollama/ollama/blob/main/docs/api/authentication.mdx).", "pricing": "freemium", "pricingNotes": "The server, CLI and desktop app are free under MIT with no account. Ollama Cloud has five plans on ollama.com/pricing. Free ($0, starter usage credits, starter models, 1 concurrent request), Pro ($20 a month or $200 a year, $60 of usage credits a month, 3 concurrent requests), Max ($100 a month, $300 of credits, 10 concurrent requests), Team ($500 a month, $1,000 of shared credits, unlimited users) and Enterprise (custom). Usage is priced per model by the token, and the page doesn't say whether the Free plan needs a card (checked 2026-10-03).", "priceSummary": "$20 / mo", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the pricing page or the source (checked 2026-10-03).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 181200, "npmWeekly": 871543, "pypiWeekly": null, "asOf": "2026-10-03" }, "docsUrl": "https://docs.ollama.com", "llmsTxt": "https://docs.ollama.com/llms.txt", "openapi": "https://raw.githubusercontent.com/ollama/ollama/main/docs/openapi.yaml", "capabilities": [ "inference.local", "inference.open-weights", "inference.llm", "embed.text", "inference.decision", "web.search", "web.fetch" ], "tags": [ "open-source", "local", "self-hosted", "hosted", "freemium", "no-card", "openai-compatible", "openapi", "llms-txt", "docker", "go", "python", "typescript", "pre-1.0", "no-auth" ], "lastRelease": "2026-11-02", "graded": true, "anchor": { "graded": true, "score": 46.3, "grade": "D", "agentReady": false, "rank": 1176, "ranked": true, "rankOf": 1510, "categoryRank": 16, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 81, "payments": 60, "reliability": 53, "schema": 79, "security": 32, "transparency": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": -15, "negativeNotes": [ "2025-11-04 to 2026-11-04, counted one by one by this run's values, as llama-cpp and vllm. CVE-2025-63389 (MITRE, 18 December 2025, Critical 9.8, unauthenticated model management through v0.12.3, no fixed version) 2. Fixed or older Highs over two months take 1 each, CVE-2025-15514 (VulnCheck, 12 January 2026), CVE-2025-66959 and CVE-2025-66960 (MITRE, 21 January, GGUF decoder), CVE-2026-42248 and CVE-2026-42249 (CERT Polska, 29 April, Windows updater, CNA rating 7.7, fixed in v0.23.3 under a note reading `app: harden update flows`), CVE-2026-7482 (4 May, GGUF heap read, fixed in 0.17.1), CVE-2026-5757 (CERT/CC, 26 June, quantisation heap read), CVE-2026-15685 (ZDI, 13 July, downloadBlob), CVE-2026-65315 (VulnCheck, 21 July, GGUF metadata) and CVE-2026-85180 (VulnCheck, 3 September, tensor-layer redirects), 10. One under two months takes 2, CVE-2026-102697 (VulnCheck, 29 September, agent-mode Bash approval, fixed in 0.31.2). CVE-2026-103663 (CERT Polska, 8 October, /api/pull digest path traversal) is rated Medium 6.9 by its CNA on OSV and fixed in 0.35.0, so as a fixed third-party Medium it costs 0, like the VulDB Lows and Mediums (CVE-2026-5530, -7020, -86289, -108836). 2 + 10 + 2 = 14. Ollama published no advisory for any of them. https://osv.dev/vulnerability/CVE-2025-63389 and https://osv.dev/vulnerability/CVE-2026-103663", "Undisclosed telemetry, -2. At v0.40.14 the desktop app's update check (app/updater/updater.go) runs every hour, sends the OS, architecture, version, a timestamp, a signed nonce and, on macOS, the install's device ID to ollama.com, and keeps running when automatic updates are off. The FAQ says only that the app downloads updates, the privacy policy (per the 3 October reading) names device information and app versions in general terms, and no page describes the check or a way to stop it. With no description and no opt-out this is the low end, as prismic and qwenpaw took; matomo, whose update check is documented with an off switch, took none. https://github.com/ollama/ollama/blob/main/app/updater/updater.go", "Total 14 + 2 = 16, held at the -15 floor. Without the telemetry term the advisories alone give -14." ], "verdict": "A local model runner with native, OpenAI-compatible and Anthropic-compatible routes, an OpenAPI file and 35 releases in 90 days. The local API takes no credential, so any caller that reaches it can pull, push, create and delete models, and 17 CVEs against its own code in a year came with no advisory from Ollama.", "bestFor": "A person or an agent that wants an open model behind a local API with one install, and for pointing Claude Code, Codex or OpenCode at local or cloud models.", "strengths": [ "An OpenAPI 3.1 file for the 15 native operations and llms.txt with 68 links to Markdown pages", "Native, OpenAI-compatible and Anthropic-compatible routes on one local port, with `ollama launch` for Claude Code, Codex and OpenCode", "35 stable releases in the 90 days to 4 November 2026, and official Python and JavaScript libraries released on 28 September", "Local prompts stay on the machine, and `OLLAMA_NO_CLOUD=1` turns off cloud models and web search", "Binds 127.0.0.1 by default and refuses foreign Host headers while bound to loopback" ], "weaknesses": [ "No credential on the local API, and any caller that reaches it can pull, push, create and delete models", "No security advisory published by Ollama, against 17 CVEs on its own code in the year to 4 November 2026", "The Windows updater installed unsigned files until v0.23.3 on 12 May 2026, fixed under a release note that didn't mention security", "The desktop app checks ollama.com every hour with a signed request, even with automatic updates off, and no documented way to stop it", "A default context of 4k tokens below 24 GiB of VRAM, where the docs say agents need 64,000" ], "agentNotes": [ "Send `\"stream\": false` for one JSON body. The native routes stream NDJSON by default", "Set `OLLAMA_CONTEXT_LENGTH=64000` or `options.num_ctx` before agent work. The default is 4k below 24 GiB of VRAM", "Back off on a 503. It means the queue (512 by default) is full", "Put an authenticating proxy in front before binding past 127.0.0.1. The server checks no credential", "Expect model names with a `cloud` tag to run on Ollama's servers. They need `ollama signin` and fail with `OLLAMA_NO_CLOUD=1`" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 46.3 } ], "editorialScores": { "ergonomics": 75, "maintenance": 81, "payments": 60, "reliability": 53, "schema": 79, "security": 32, "transparency": 66 }, "provenanceScore": 59, "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": "curl -fsSL https://ollama.com/install.sh | sh # macOS and Linux; Windows: irm https://ollama.com/install.ps1 | iex\nollama pull gemma4:e2b", "http": "curl http://localhost:11434/api/chat \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"gemma4:e2b\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Say hello in one sentence.\"}],\n \"stream\": false\n }'", "claudeCode": "ollama launch claude # or: ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_API_KEY=\"\" ANTHROPIC_BASE_URL=http://localhost:11434 claude --model qwen3.5" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/ollama" }, "area": "models", "unitPrices": [ { "item": "Ollama Cloud Pro", "unit": "month", "usd": 20, "note": "$60 of usage credits a month, 3 concurrent requests. $200 a year" }, { "item": "Ollama Cloud Max", "unit": "month", "usd": 100, "note": "$300 of usage credits a month, 10 concurrent requests" }, { "item": "Ollama Cloud Team", "unit": "month", "usd": 500, "note": "$1,000 of shared usage credits a month, unlimited users, 10 concurrent requests" } ], "provenance": { "legalEntity": "Ollama Inc.", "domain": "ollama.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://ollama.com/terms", "privacy": "https://ollama.com/privacy", "statusPage": "", "changelog": "https://github.com/ollama/ollama/releases", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "The terms (last updated May 2026, read on 4 November) name Ollama Inc., under California law with arbitration in San Francisco, and bar using automated means to access the services, defined to include the website, without permission. The privacy policy was last updated in March 2026 (3 October reading).", "ollama.com/.well-known/security.txt returned 404 on 3 October. SECURITY.md asks for reports through GitHub private advisories since 12 October 2026.", "status.ollama.com didn't resolve on 3 October, and we found no other status page for Ollama Cloud.", "The API an agent calls runs on the owner's machine, so there's no shared endpoint to check. Ollama Cloud answers at https://ollama.com/api and /v1." ], "score": 59 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ollama.json", "live": { "slug": "ollama", "versions": [ { "registry": "github", "name": "ollama/ollama", "version": "v0.40.15", "released": "2026-11-03", "seenAt": "2026-11-06T23:50:49.932246355Z" }, { "registry": "npm", "name": "ollama", "version": "0.6.4", "seenAt": "2026-11-06T23:50:49.031026643Z" }, { "registry": "pypi", "name": "ollama", "version": "0.6.3", "released": "2026-09-29", "seenAt": "2026-11-06T23:50:48.923699946Z" } ], "githubStars": 186142, "npmWeekly": 1219881, "pypiWeekly": 3130866, "securityTxt": { "url": "https://ollama.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T15:59:37.442843158Z" }, "llmsTxt": { "url": "https://docs.ollama.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:21.158363015Z" }, "domain": { "domain": "ollama.com", "registered": "2017-05-08", "source": "https://rdap.verisign.com/com/v1/domain/ollama.com", "checkedAt": "2026-11-01T14:19:26.375059158Z" }, "pages": [ { "url": "https://ollama.com/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:15:15.703398458Z", "changedAt": "2026-11-07T14:15:15.703398458Z", "fingerprint": "dfeddfd60dba" }, { "url": "https://ollama.com/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:15:17.914723835Z", "changedAt": "2026-11-07T14:15:17.914723835Z", "fingerprint": "c29eb0715f26" } ], "github": { "repo": "ollama/ollama", "checkedAt": "2026-11-02T09:11:40.15884608Z", "stars": 185649, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T05:30:37Z", "openIssues": 2635, "openPRs": 1906, "issuesOpened90d": 682, "issuesClosed90d": 403, "prsMerged90d": 288, "replies": { "sampled": 13, "unanswered": 5, "medianDays": 0 } }, "updatedAt": "2026-11-07T15:59:37.442843158Z" } }, "answer": "PrivateGPT scores 53.2 (D) on agent readiness against Ollama's 46.3 (D), and leads in 3 of 7 scored categories. Ollama leads on agent ergonomics and maintenance \u0026 community.", "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": 40, "category": "maintenance", "leads": "ollama", "name": "Maintenance \u0026 community", "reasons": { "a": "v0.40.14, tagged on 2 November 2026 and pinned to llama.cpp b11963 (30). 35 stable releases in the 90 days from 6 August, v0.32.7 (9 August) to v0.40.14, plus release candidates, which a default install doesn't get (20). Open issues and reply times per the 3 October check (2.5k open issues and 1.5k open pull requests, recent reports without a reply we could see), not re-read; 158 commits from v0.35.1 to v0.40.14, 113 citing a pull request number (10 of 25). Official Python (v0.6.3) and JavaScript (v0.6.4) libraries, both tagged on 28 September 2026, the newest tags on 4 November (15). Go 1.26.10 and CUDA and ROCm builds in the release workflow, CI only on pull requests and no Dependabot configuration (6 of 10). 30 + 20 + 10 + 15 + 6 = 81.", "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": 81, "b": 41 } }, { "by": 17, "category": "reliability", "leads": "privategpt", "name": "Reliability", "reasons": { "a": "Read with the local-software lines, since the API an agent calls is the Ollama server on the owner's machine, as llama-cpp, lm-studio, vllm and docker-model-runner are. Ollama Cloud has no status page we could reach (status.ollama.com didn't resolve on 3 October), and we graded the local server. Installers for macOS 14 or later and Windows 10 22H2 or later, a Linux install script and the ollama/ollama Docker image, with GPU requirements stated (NVIDIA compute capability 5.0 and driver 550 or newer, ROCm, Vulkan, Metal and MLX) (20). The test workflow runs Go tests and builds on pull requests only (test.yaml at v0.40.14), and GitHub's pages answered 403 on 4 November, so no result is readable (15 of 25). Open issues and pull requests per the 3 October check (2.5k and 1.5k, recent regressions without a reply we could see), not re-read (9 of 25). Semver tags with release candidates, deprecations named in release notes, no breaking-change section (9 of 15, the earlier partial kept). Version 0.40.14, pre-1.0 (0). 20 + 15 + 9 + 9 + 0 = 53.", "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": 53, "b": 70 } }, { "by": 11, "category": "ergonomics", "leads": "ollama", "name": "Agent ergonomics", "reasons": { "a": "Read for an API. Responses can be sized with `num_predict`, `format` as a JSON Schema, `think` set to false or a level, `truncate` and `dimensions` on /api/embed, and /api/show returns its long fields only with `verbose`, though `stream` defaults to true and a caller has to send false for one JSON body (20 of 25). Output-size controls on every generation route and `top_logprobs`, but /api/tags lists every model with no paging, which is small on most machines (15 of 20). Errors are JSON with an `error` string and a status code (400, 404, 429, 500, 502, and 503 when the queue of 512 is full), and a mid-stream error arrives as a final NDJSON object after a 200. There's no error code beyond the message (13 of 20). Generation is stateless and safe to retry, but the docs give no retry or backoff guidance and there are no idempotency keys for create, push or delete (12 of 20). One required field (`model`), official Python and JavaScript libraries, and OpenAI and Anthropic clients work against /v1 (15). Per the 3 October reading of the docs, which are unchanged in kind at v0.40.14 in the repository.", "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": 75, "b": 64 } } ], "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Ollama Inc.", "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": "Freemium", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence", "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": "2026-05-01", "b": "no date given", "name": "Terms last updated" }, { "a": "2026-03-01", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "181k stars, 872k npm/wk", "b": "58k stars", "name": "Popularity" }, { "a": "2.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "PrivateGPT scores 53.2 (D) on agent readiness against Ollama's 46.3 (D), and leads in 3 of 7 scored categories. Ollama leads on agent ergonomics and maintenance \u0026 community.", "question": "Which is better for AI agents, Ollama or PrivateGPT?" }, { "answer": "Neither needs a key.", "question": "Do Ollama and PrivateGPT need an API key?" }, { "answer": "No hosted endpoint is listed for Ollama. No hosted endpoint is listed for PrivateGPT.", "question": "Can an agent call Ollama and PrivateGPT without installing anything?" }, { "answer": "Yes. Ollama is open source (MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence). PrivateGPT is open source (Apache-2.0).", "question": "Are Ollama and PrivateGPT open source?" } ], "goodFor": [ { "aheadOn": [ "Agent ergonomics, 75 against 64", "Maintenance \u0026 community, 81 against 41" ], "also": [ "Free to start without a card" ], "goodFor": "A person or an agent that wants an open model behind a local API with one install, and for pointing Claude Code, Codex or OpenCode at local or cloud models.", "slug": "ollama", "watchFor": "No credential on the local API, and any caller that reaches it can pull, push, create and delete models" }, { "aheadOn": [ "Reliability, 70 against 53" ], "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": { "ollama": [ { "causes": [ "security", "correction" ], "date": "2026-11-04", "delta": -10.3, "from": 56.6, "fromGrade": "C", "to": 46.3, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.3, "from": 56.3, "fromGrade": "C", "to": 56.6, "toGrade": "C" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.3, "from": 56.6, "fromGrade": "C", "to": 56.3, "toGrade": "C" } ], "privategpt": null }, "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-ollama.json", "title": "AnythingLLM vs Ollama", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-ollama" }, { "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-ollama.json", "title": "Berth vs Ollama", "url": "https://www.anchorterminal.com/compare/berth-vs-ollama" }, { "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-ollama.json", "title": "BitRun vs Ollama", "url": "https://www.anchorterminal.com/compare/bitrun-vs-ollama" }, { "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-ollama.json", "title": "Docker Model Runner vs Ollama", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama" }, { "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-ollama.json", "title": "Foundry Local vs Ollama", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-ollama" }, { "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-ollama.json", "title": "Core vs Ollama", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-ollama" }, { "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-ollama.json", "title": "GPT4All vs Ollama", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-ollama" }, { "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-ollama.json", "title": "HyperQwen vs Ollama", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-ollama" }, { "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-ollama.json", "title": "Jan vs Ollama", "url": "https://www.anchorterminal.com/compare/jan-vs-ollama" }, { "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-ollama.json", "title": "Khoj vs Ollama", "url": "https://www.anchorterminal.com/compare/khoj-vs-ollama" }, { "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-privategpt.json", "title": "KoboldCpp vs PrivateGPT", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-ollama.json", "title": "Lemonade vs Ollama", "url": "https://www.anchorterminal.com/compare/lemonade-vs-ollama" }, { "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-ollama.json", "title": "llama.cpp vs Ollama", "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-ollama" }, { "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-ollama.json", "title": "LM Studio vs Ollama", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-ollama" }, { "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-ollama.json", "title": "LocalAI vs Ollama", "url": "https://www.anchorterminal.com/compare/localai-vs-ollama" }, { "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-ollama.json", "title": "MLX LM vs Ollama", "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-ollama" }, { "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-open-webui.json", "title": "Ollama vs Open WebUI", "url": "https://www.anchorterminal.com/compare/ollama-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-screenpipe.json", "title": "Ollama vs screenpipe", "url": "https://www.anchorterminal.com/compare/ollama-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-text-generation-webui.json", "title": "Ollama vs TextGen", "url": "https://www.anchorterminal.com/compare/ollama-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-vllm.json", "title": "Ollama vs vLLM", "url": "https://www.anchorterminal.com/compare/ollama-vs-vllm" }, { "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/ollama-vs-underdog.json", "title": "Ollama vs Underdog", "url": "https://www.anchorterminal.com/compare/ollama-vs-underdog" } ], "panel": null, "scores": [ { "by": 17, "edge": "privategpt", "key": "reliability", "name": "Reliability", "ollama": 53, "privategpt": 70, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 4, "edge": "privategpt", "key": "schema", "name": "Schema \u0026 documentation", "ollama": 79, "privategpt": 83, "weight": 13 }, { "by": 11, "edge": "ollama", "key": "ergonomics", "name": "Agent ergonomics", "ollama": 75, "privategpt": 64, "weight": 13 }, { "by": 0, "edge": "", "key": "security", "name": "Security \u0026 auth", "ollama": 32, "privategpt": 32, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "ollama": 60, "privategpt": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 40, "edge": "ollama", "key": "maintenance", "name": "Maintenance \u0026 community", "ollama": 81, "privategpt": 41, "weight": 7 }, { "by": 1, "edge": "privategpt", "key": "transparency", "name": "Transparency \u0026 trust", "ollama": 63, "privategpt": 64, "weight": 7 } ], "summary": "PrivateGPT scores 53.2 (D) on agent readiness against Ollama's 46.3 (D), and leads in 3 of 7 scored categories. Ollama leads on agent ergonomics and maintenance \u0026 community. Both do local inference.", "tasks": null, "tutorials": [], "verdicts": { "ollama": "A local model runner with native, OpenAI-compatible and Anthropic-compatible routes, an OpenAPI file and 35 releases in 90 days. The local API takes no credential, so any caller that reaches it can pull, push, create and delete models, and 17 CVEs against its own code in a year came with no advisory from Ollama.", "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/ollama-vs-privategpt", "json": "https://www.anchorterminal.com/compare/ollama-vs-privategpt.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/ollama-vs-privategpt.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/ollama-vs-privategpt.min.md" }, "markdown": "PrivateGPT scores 53.2 (D) on agent readiness against Ollama's 46.3 (D), and leads in 3 of 7 scored categories. Ollama leads on agent ergonomics and maintenance \u0026 community. Both do local inference.\n\n- Ollama: grade D, 46.3/100, rank #1176 of 1510. Markdown https://www.anchorterminal.com/tools/ollama.md · JSON https://www.anchorterminal.com/api/v1/tools/ollama.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### Ollama (D)\n\nGood for: A person or an agent that wants an open model behind a local API with one install, and for pointing Claude Code, Codex or OpenCode at local or cloud models.\n\nAhead on:\n- Agent ergonomics, 75 against 64\n- Maintenance \u0026 community, 81 against 41\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: No credential on the local API, and any caller that reaches it can pull, push, create and delete models\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 53\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: Ollama +40\n\n- Ollama (81): v0.40.14, tagged on 2 November 2026 and pinned to llama.cpp b11963 (30). 35 stable releases in the 90 days from 6 August, v0.32.7 (9 August) to v0.40.14, plus release candidates, which a default install doesn't get (20). Open issues and reply times per the 3 October check (2.5k open issues and 1.5k open pull requests, recent reports without a reply we could see), not re-read; 158 commits from v0.35.1 to v0.40.14, 113 citing a pull request number (10 of 25). Official Python (v0.6.3) and JavaScript (v0.6.4) libraries, both tagged on 28 September 2026, the newest tags on 4 November (15). Go 1.26.10 and CUDA and ROCm builds in the release workflow, CI only on pull requests and no Dependabot configuration (6 of 10). 30 + 20 + 10 + 15 + 6 = 81.\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### Reliability: PrivateGPT +17\n\n- Ollama (53): Read with the local-software lines, since the API an agent calls is the Ollama server on the owner's machine, as llama-cpp, lm-studio, vllm and docker-model-runner are. Ollama Cloud has no status page we could reach (status.ollama.com didn't resolve on 3 October), and we graded the local server. Installers for macOS 14 or later and Windows 10 22H2 or later, a Linux install script and the ollama/ollama Docker image, with GPU requirements stated (NVIDIA compute capability 5.0 and driver 550 or newer, ROCm, Vulkan, Metal and MLX) (20). The test workflow runs Go tests and builds on pull requests only (test.yaml at v0.40.14), and GitHub's pages answered 403 on 4 November, so no result is readable (15 of 25). Open issues and pull requests per the 3 October check (2.5k and 1.5k, recent regressions without a reply we could see), not re-read (9 of 25). Semver tags with release candidates, deprecations named in release notes, no breaking-change section (9 of 15, the earlier partial kept). Version 0.40.14, pre-1.0 (0). 20 + 15 + 9 + 9 + 0 = 53.\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### Agent ergonomics: Ollama +11\n\n- Ollama (75): Read for an API. Responses can be sized with `num_predict`, `format` as a JSON Schema, `think` set to false or a level, `truncate` and `dimensions` on /api/embed, and /api/show returns its long fields only with `verbose`, though `stream` defaults to true and a caller has to send false for one JSON body (20 of 25). Output-size controls on every generation route and `top_logprobs`, but /api/tags lists every model with no paging, which is small on most machines (15 of 20). Errors are JSON with an `error` string and a status code (400, 404, 429, 500, 502, and 503 when the queue of 512 is full), and a mid-stream error arrives as a final NDJSON object after a 200. There's no error code beyond the message (13 of 20). Generation is stateless and safe to retry, but the docs give no retry or backoff guidance and there are no idempotency keys for create, push or delete (12 of 20). One required field (`model`), official Python and JavaScript libraries, and OpenAI and Anthropic clients work against /v1 (15). Per the 3 October reading of the docs, which are unchanged in kind at v0.40.14 in the repository.\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## Score by category\n\n| Category | Weight | Ollama | PrivateGPT | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 53 | 70 | PrivateGPT +17 |\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) | 75 | 64 | Ollama +11 |\n| Security \u0026 auth | 14% (17.5 this run) | 32 | 32 | even |\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) | 81 | 41 | Ollama +40 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 63 | 64 | PrivateGPT +1 |\n| Negative events | ≤15 | -15 | -7 | |\n| **Total** | | **46.3 · D** | **53.2 · D** | |\n\n## Facts side by side\n\n| Fact | Ollama | PrivateGPT |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Ollama Inc. | 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 | Freemium | Free |\n| x402 | no | no |\n| Licence | MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence | 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 | 2026-05-01 | no date given |\n| Privacy policy last updated | 2026-03-01 | no document linked |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | yes | not found in the text |\n| Popularity | 181k stars, 872k npm/wk | 58k stars |\n| Agent reviews | 2.5/5 (2) | none |\n\n## How the scores have moved\n\n### Ollama\n\n- -10.3 on 4 November 2026 (C to D): security, correction\n- +0.3 on 27 October 2026: checklist\n- -0.3 on 8 October 2026: checklist\n\n### PrivateGPT\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Ollama.** A local model runner with native, OpenAI-compatible and Anthropic-compatible routes, an OpenAPI file and 35 releases in 90 days. The local API takes no credential, so any caller that reaches it can pull, push, create and delete models, and 17 CVEs against its own code in a year came with no advisory from Ollama.\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### Ollama\n\n1. Send `\"stream\": false` for one JSON body. The native routes stream NDJSON by default\n2. Set `OLLAMA_CONTEXT_LENGTH=64000` or `options.num_ctx` before agent work. The default is 4k below 24 GiB of VRAM\n3. Back off on a 503. It means the queue (512 by default) is full\n4. Put an authenticating proxy in front before binding past 127.0.0.1. The server checks no credential\n5. Expect model names with a `cloud` tag to run on Ollama's servers. They need `ollama signin` and fail with `OLLAMA_NO_CLOUD=1`\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, Ollama or PrivateGPT?\n\nPrivateGPT scores 53.2 (D) on agent readiness against Ollama's 46.3 (D), and leads in 3 of 7 scored categories. Ollama leads on agent ergonomics and maintenance \u0026 community.\n\n### Do Ollama and PrivateGPT need an API key?\n\nNeither needs a key.\n\n### Can an agent call Ollama and PrivateGPT without installing anything?\n\nNo hosted endpoint is listed for Ollama. No hosted endpoint is listed for PrivateGPT.\n\n### Are Ollama and PrivateGPT open source?\n\nYes. Ollama is open source (MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence). PrivateGPT is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/ollama-vs-privategpt.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ollama-vs-privategpt.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"ollama\", \"b\": \"privategpt\"}`. From a terminal: `anchor compare ollama privategpt`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ollama.json and https://www.anchorterminal.com/api/v1/tools/privategpt.json\n\n## Other comparisons with Ollama or PrivateGPT\n\n- [AnythingLLM vs Ollama](https://www.anchorterminal.com/compare/anythingllm-vs-ollama.md)\n- [AnythingLLM vs PrivateGPT](https://www.anchorterminal.com/compare/anythingllm-vs-privategpt.md)\n- [Berth vs Ollama](https://www.anchorterminal.com/compare/berth-vs-ollama.md)\n- [Berth vs PrivateGPT](https://www.anchorterminal.com/compare/berth-vs-privategpt.md)\n- [BitRun vs Ollama](https://www.anchorterminal.com/compare/bitrun-vs-ollama.md)\n- [BitRun vs PrivateGPT](https://www.anchorterminal.com/compare/bitrun-vs-privategpt.md)\n- [Docker Model Runner vs Ollama](https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.md)\n- [Docker Model Runner vs PrivateGPT](https://www.anchorterminal.com/compare/docker-model-runner-vs-privategpt.md)\n- [Foundry Local vs Ollama](https://www.anchorterminal.com/compare/foundry-local-vs-ollama.md)\n- [Foundry Local vs PrivateGPT](https://www.anchorterminal.com/compare/foundry-local-vs-privategpt.md)\n- [Core vs Ollama](https://www.anchorterminal.com/compare/ghost-core-vs-ollama.md)\n- [Core vs PrivateGPT](https://www.anchorterminal.com/compare/ghost-core-vs-privategpt.md)\n- [GPT4All vs Ollama](https://www.anchorterminal.com/compare/gpt4all-vs-ollama.md)\n- [GPT4All vs PrivateGPT](https://www.anchorterminal.com/compare/gpt4all-vs-privategpt.md)\n- [HyperQwen vs Ollama](https://www.anchorterminal.com/compare/hyperqwen-vs-ollama.md)\n- [HyperQwen vs PrivateGPT](https://www.anchorterminal.com/compare/hyperqwen-vs-privategpt.md)\n- [Jan vs Ollama](https://www.anchorterminal.com/compare/jan-vs-ollama.md)\n- [Jan vs PrivateGPT](https://www.anchorterminal.com/compare/jan-vs-privategpt.md)\n- [Khoj vs Ollama](https://www.anchorterminal.com/compare/khoj-vs-ollama.md)\n- [KoboldCpp vs Ollama](https://www.anchorterminal.com/compare/koboldcpp-vs-ollama.md)\n- [KoboldCpp vs PrivateGPT](https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.md)\n- [Lemonade vs Ollama](https://www.anchorterminal.com/compare/lemonade-vs-ollama.md)\n- [Lemonade vs PrivateGPT](https://www.anchorterminal.com/compare/lemonade-vs-privategpt.md)\n- [llama.cpp vs Ollama](https://www.anchorterminal.com/compare/llama-cpp-vs-ollama.md)\n- [llama.cpp vs PrivateGPT](https://www.anchorterminal.com/compare/llama-cpp-vs-privategpt.md)\n- [LM Studio vs Ollama](https://www.anchorterminal.com/compare/lm-studio-vs-ollama.md)\n- [LM Studio vs PrivateGPT](https://www.anchorterminal.com/compare/lm-studio-vs-privategpt.md)\n- [LocalAI vs Ollama](https://www.anchorterminal.com/compare/localai-vs-ollama.md)\n- [LocalAI vs PrivateGPT](https://www.anchorterminal.com/compare/localai-vs-privategpt.md)\n- [MLX LM vs Ollama](https://www.anchorterminal.com/compare/mlx-lm-vs-ollama.md)\n- [MLX LM vs PrivateGPT](https://www.anchorterminal.com/compare/mlx-lm-vs-privategpt.md)\n- [Ollama vs Open WebUI](https://www.anchorterminal.com/compare/ollama-vs-open-webui.md)\n- [Ollama vs screenpipe](https://www.anchorterminal.com/compare/ollama-vs-screenpipe.md)\n- [Ollama vs TextGen](https://www.anchorterminal.com/compare/ollama-vs-text-generation-webui.md)\n- [Ollama vs vLLM](https://www.anchorterminal.com/compare/ollama-vs-vllm.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- [Ollama vs Underdog](https://www.anchorterminal.com/compare/ollama-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": "Ollama vs PrivateGPT", "url": "" } ], "description": "PrivateGPT scores 53.2 (D) to Ollama's 46.3 (D) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Ollama D 46.3", "PrivateGPT D 53.2", "scores" ], "h1": "Ollama vs PrivateGPT", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/ollama-vs-privategpt", "published": "2026-10-01", "section": "tools", "title": "Ollama vs PrivateGPT for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/ollama-vs-privategpt" }, "tokens": { "markdown": 4250, "slim": 2030 }, "version": 1 }