{ "data": { "a": { "slug": "ghost-core", "name": "Core", "vendor": "Ghost (ZMJ, Inc.)", "vendorUrl": "https://ghost.ai", "kind": "platform", "category": "local-ai", "summary": "Core is a personal AI computer from Ghost that runs open-weight language models and a memory of the owner's apps, files and devices at home, used through Ghost's apps and an OpenAI Responses-compatible endpoint. On pre-order.", "url": "https://www.anchorterminal.com/tools/ghost-core", "markdownUrl": "https://www.anchorterminal.com/tools/ghost-core.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ghost-core.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ghost-core.json", "license": "Not stated. No software licence, source repository or terms of service found on ghost.ai (checked 2026-10-05). Models listed are Qwen 3.8-Next, Qwen 3.8-27B, Gemma 4-31B and Muse-Glimmer-30B. Ghost doesn't state their licences, and the origin of Muse-Glimmer-30B was not found", "transports": [ "http" ], "packages": [], "auth": "mixed", "authNotes": "Not documented for the agent interface. Ghost's FAQ says Core exposes an endpoint compatible with the OpenAI Responses API but gives no address, port or authentication method, so keyless use isn't established. The Ghost app pairs with Core over the local network, remote access is for paired devices, and Ghost keeps device authorisation records. Online services use Ghost's gateway or the owner's own provider API keys. The privacy policy mentions device-access controls without detail (https://ghost.ai/core, https://ghost.ai/setup, https://ghost.ai/privacy, checked 2026-10-05).", "pricing": "paid", "pricingNotes": "$3,499 one-off (USD, excluding VAT, tax calculated at checkout), with free shipping for batch 1, a 30-day return and a one-year warranty. Ghost states no subscription and no per-token inference fees. Some online services (web search, phone calls) run through Ghost-managed services with daily usage limits whose numbers aren't published, or through the owner's own API keys. Batch 1 showed sold out at 23:31 UTC on 5 October 2026, with a batch 2 interest form in place of the order button (https://ghost.ai/core, https://ghost.ai/privacy, https://ghost.ai/api/stock).", "priceSummary": "Paid", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on ghost.ai or in its site code (checked 2026-10-05). Orders go through Stripe Checkout.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-05" }, "docsUrl": "https://ghost.ai/setup", "capabilities": [ "inference.local", "inference.open-weights", "memory.user", "memory.search", "memory.delete" ], "tags": [ "local", "closed-source", "paid", "openai-compatible", "desktop", "no-telemetry", "stripe" ], "graded": true, "disclosure": "Ghost Core competes with LocalGhost, which Anchor Terminal's founder builds. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.", "competesWith": "localghost", "anchor": { "graded": true, "score": 7.4, "grade": "F", "agentReady": false, "rank": 1239, "ranked": true, "rankOf": 1239, "categoryRank": 23, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 4, "maintenance": 3, "payments": 10, "reliability": 5, "schema": 7, "security": 6, "transparency": 46 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-05" }, "negative": -2, "negativeNotes": [ "2026-10-05. Ghost's home page says 'No data ever leaves your home' and 'Everything you do with Core is run locally' (seen at 23:31 UTC on 5 October 2026), and the FAQ says Core processes data 'entirely on-device', while the privacy policy, effective 4 October 2026, says web search, phone calls and email requests go through Ghost's gateway to third-party providers that may keep them unless the owner sets their own keys, and that remote access runs through Ghost's relay. A misleading claim, weighed as Screenpipe's README claim was. The policy and the FAQ's internet answer disclose the online services, they carry task requests rather than default-on analytics, and Core hadn't shipped, so the minimum, -2. https://ghost.ai/ ; https://ghost.ai/core ; https://ghost.ai/privacy" ], "verdict": "Ghost's privacy policy sets out what stays on Core, what passes through its gateway and relay, and how long Ghost keeps each record. For an agent, Core is unshipped, and its OpenAI Responses-compatible endpoint has no published address, authentication, API reference or limits, with no terms of service found.", "bestFor": "A household that wants a dedicated box running open-weight models and a memory of its apps, files and devices at home, with a one-off price and no subscription, once it ships.", "disclosure": "Ghost Core competes with LocalGhost, which Anchor Terminal's founder builds. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.", "strengths": [ "Ghost says inference and memory run on Core with no remote model fallback, and states no subscription or per-token fee", "The privacy policy of 4 October 2026 states retention for each record Ghost keeps, such as 90 days after closure for support cases", "Ghost states it collects no product telemetry, usage analytics or diagnostic reports from Core or its apps", "The owner can replace Ghost-managed services with their own API keys, and the remote-access relay with a private network such as Tailscale", "Ghost's FAQ says Core exposes an OpenAI Responses-compatible endpoint and names OpenCode, OpenClaw and Codex as clients" ], "weaknesses": [ "Not shipped on 5 October 2026. Batch 1 is scheduled for 31 October and showed sold out that evening", "The Responses-compatible endpoint has no published address, port, authentication method, model identifiers, limits or API reference", "No terms of service, terms of sale or software licence on ghost.ai, and no security.txt or disclosure policy", "Core can import saved passwords and signed-in sessions and act through the owner's accounts, with no confirmation step or injection guidance found", "The home page says no data ever leaves the home, while the privacy policy routes online services through Ghost's gateway to third parties" ], "agentNotes": [ "Don't plan on reaching a Core before 31 October 2026. Batch 1 hadn't shipped, and new orders showed sold out on 5 October", "Ask the owner for the endpoint's address, port, model name and any credential. Ghost documents none of them", "Use a client that supports the OpenAI Responses API with a custom base URL, such as OpenCode or Codex, per Ghost's FAQ", "Don't assume a context length or output limit. Ghost states none for Qwen 3.8-Next, Qwen 3.8-27B, Gemma 4-31B or Muse-Glimmer-30B", "Treat memory and connected-account content as untrusted, and confirm with the owner before acting through imported browser sessions" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 1, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "F", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 7.4 } ], "editorialScores": { "ergonomics": 4, "maintenance": 3, "payments": 10, "reliability": 5, "schema": 7, "security": 6, "transparency": 30 }, "provenanceScore": 62, "checked": { "categories": { "ergonomics": "2026-10-05", "maintenance": "2026-10-05", "payments": "2026-10-05", "reliability": "2026-10-05", "schema": "2026-10-05", "security": "2026-10-05", "transparency": "2026-10-05" }, "last": "2026-10-05", "lastMoved": "2026-10-28", "oldest": "2026-10-05", "stale": false, "staleAfterDays": 90 } }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/ghost-core" }, "area": "models", "provenance": { "legalEntity": "ZMJ, Inc., doing business as Ghost, 325 9th Street, San Francisco, CA 94103, United States", "domain": "ghost.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://ghost.ai/privacy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-05", "notes": [ "The privacy policy, effective 4 October 2026, names ZMJ, Inc., doing business as Ghost, at 325 9th Street, San Francisco. The state of incorporation was not found.", "RDAP for ghost.ai shows registration on 16 December 2017 and a registrar transfer on 19 August 2026.", "ghost.ai/terms, /.well-known/security.txt, /llms.txt, /robots.txt and /sitemap.xml return 404. No GitHub organisation was found.", "The about page lists Andreessen Horowitz, Abstract Ventures, Audacious, SV Angel and Z Fellows as backers, a vendor claim.", "Support is support@ghost.ai. The app page's troubleshooting link uses hello@tryghost.ai.", "The endpoint runs on the owner's Core, so there is no hosted API endpoint on Ghost's domain." ], "score": 62 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ghost-core.json", "live": { "slug": "ghost-core", "securityTxt": { "url": "https://ghost.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-30T15:38:59.904592457Z" }, "domain": { "domain": "ghost.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/ghost.ai", "checkedAt": "2026-10-25T14:03:45.614886031Z" }, "pages": [ { "url": "https://ghost.ai/privacy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-30T05:40:39.519414244Z", "changedAt": "2026-10-29T05:07:49.307405653Z", "fingerprint": "465bdb7b76bf" } ], "updatedAt": "2026-10-30T15:38:59.904592457Z" } }, "answer": "HyperQwen scores 56.9 (C) on agent readiness against Core's 7.4 (F), and leads in every scored category.", "b": { "slug": "hyperqwen", "name": "HyperQwen", "vendor": "syv.ai (syv-ai on GitHub)", "vendorUrl": "https://syv.ai", "kind": "http-api", "category": "local-ai", "summary": "HyperQwen is syv.ai's open-source serving setup for Qwen3.8-27B on one 24 GB NVIDIA GPU. A patch series against a pinned vLLM, a requantisation pipeline and Docker Compose profiles run vLLM's OpenAI-compatible API on port 18020.", "url": "https://www.anchorterminal.com/tools/hyperqwen", "markdownUrl": "https://www.anchorterminal.com/tools/hyperqwen.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hyperqwen.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hyperqwen.json", "repo": "https://github.com/syv-ai/HyperQwen", "license": "Apache-2.0", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "ghcr.io/syv-ai/hyperqwen" } ], "auth": "none", "authNotes": "No credential by default. `VLLM_API_KEY` in `.env` (or an `api_key.txt` file) turns on vLLM's Bearer check. With no key, the launcher binds 127.0.0.1 outside a container, and Docker Compose publishes the port on 127.0.0.1 unless `BIND` is changed. With a key set, the launcher binds every interface. The key is vLLM's own, one static key with no scopes, which vLLM checks only under `/v1`, `/v2`, `/inference` and `/cohere` (per the vLLM listing's check of 9 October 2026, https://github.com/vllm-project/vllm/blob/main/docs/usage/security.md).", "pricing": "free", "pricingNotes": "Free under Apache-2.0 with no account, key or card. Nothing is sold. The README links a Ko-fi page for donations towards GPU time. The owner pays for a 24 GB NVIDIA GPU, about 40 GB of disk and electricity.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the README, the docs or the launch scripts (checked 2026-10-30). Nothing is sold.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 2400, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-30" }, "docsUrl": "https://github.com/syv-ai/HyperQwen#readme", "capabilities": [ "inference.local", "inference.open-weights" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "apache-2.0", "openai-compatible", "docker", "tool-calling", "reasoning", "pre-1.0" ], "graded": true, "anchor": { "graded": true, "score": 56.9, "grade": "C", "agentReady": false, "rank": 738, "ranked": true, "rankOf": 1239, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 68, "payments": 60, "reliability": 59, "schema": 56, "security": 41, "transparency": 55 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-30" }, "negative": 0, "verdict": "HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy.", "bestFor": "An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.", "strengths": [ "Prebuilt image on ghcr.io with an immutable tag per commit, built by CI that applies all 60 patches and runs the build-time tests", "Tool calling on by default with the `qwen3_coder` parser and argument schemas enforced (`TOOL_STRICT=parameter`)", "With no API key the server listens on 127.0.0.1 only, and a CI check tests that default", "Five documented setups from 64k to 240k context, with the measured cost of each knob", "Apache-2.0 throughout, with vendored kernels and patches carrying their upstream references" ], "weaknesses": [ "Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap", "No tags, releases or changelog. Changes reach users through `latest` on every push to main", "No SECURITY.md or disclosure route, and the base weights come from a third-party repository with no pinned revision", "vLLM's key covers only `/v1`-style prefixes, so control routes such as `/pause` answer without it", "First start pulls a 9.5 GB image and about 20 GB of weights and can take over 30 minutes" ], "agentNotes": [ "Call http://127.0.0.1:18020/v1 with model `qwen3.8-27b` and the `VLLM_API_KEY` value, or any string if no key was set", "Poll `/health` before the first request. A first start downloads and prepares the model and compiles kernels, which can take over 30 minutes", "Declare the context window your setup uses (65,536 by default, 131,072 for `CTX=long`, 245,760 for `CTX=huge`) so the client doesn't truncate", "Ask the owner to set `VLLM_API_KEY` before setting `BIND=0.0.0.0`, and to front the port with a proxy that allowlists routes", "Treat the README's tokens-per-second figures as the project's measurements on one RTX 3090 at 250 W" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.9 } ], "editorialScores": { "ergonomics": 65, "maintenance": 68, "payments": 60, "reliability": 59, "schema": 56, "security": 41, "transparency": 60 }, "provenanceScore": 49, "checked": { "categories": { "ergonomics": "2026-10-30", "maintenance": "2026-10-30", "payments": "2026-10-30", "reliability": "2026-10-30", "schema": "2026-10-30", "security": "2026-10-30", "transparency": "2026-10-30" }, "last": "2026-10-30", "oldest": "2026-10-30", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "git clone https://github.com/syv-ai/HyperQwen \u0026\u0026 cd HyperQwen\ncp .env.example .env\n\ndocker compose --profile single up -d # one or a few people chatting\ndocker compose --profile batch up -d # API backend, many concurrent requests" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/hyperqwen" }, "area": "models", "provenance": { "legalEntity": "syv.ai (Copenhagen, CVR DK44671247)", "domain": "syv.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://syv.ai/privatlivspolitik", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-30", "notes": [ "The Hugging Face organisation syvai, full name syv.ai, links https://syv.ai and github.com/syv-ai, and hosts the drafter files HyperQwen downloads. syv.ai's own pages don't mention HyperQwen.", "syv.ai's contact page gives the address in Copenhagen and CVR DK44671247. The Danish CVR register answered with a bot check and wasn't read.", "No terms, SECURITY.md or changelog for HyperQwen. The Apache-2.0 licence stands in for terms. The privacy policy listed is syv.ai's website policy and doesn't cover the software, which runs on the owner's machine.", "syv.ai answers 404 at /.well-known/security.txt and /security.txt." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hyperqwen.json" }, "facts": [ { "a": "Platform", "b": "HTTP API", "name": "Kind" }, { "a": "Ghost (ZMJ, Inc.)", "b": "syv.ai (syv-ai on GitHub)", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "None", "name": "Auth" }, { "a": "Paid", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Not stated. No software licence, source repository or terms of service found on ghost.ai (checked 2026-10-05). Models listed are Qwen 3.8-Next, Qwen 3.8-27B, Gemma 4-31B and Muse-Glimmer-30B. Ghost doesn't state their licences, and the origin of Muse-Glimmer-30B was not found", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-10-05", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "2.4k stars", "name": "Popularity" }, { "a": "2/5 (1)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "HyperQwen scores 56.9 (C) on agent readiness against Core's 7.4 (F), and leads in every scored category.", "question": "Which is better for AI agents, Core or HyperQwen?" }, { "answer": "No hosted endpoint is listed for Core. No hosted endpoint is listed for HyperQwen.", "question": "Can an agent call Core and HyperQwen without installing anything?" }, { "answer": "No open-source release is listed for Core. HyperQwen is open source (Apache-2.0).", "question": "Are Core and HyperQwen open source?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "A household that wants a dedicated box running open-weight models and a memory of its apps, files and devices at home, with a one-off price and no subscription, once it ships.", "slug": "ghost-core", "watchFor": "Not shipped on 5 October 2026. Batch 1 is scheduled for 31 October and showed sold out that evening" }, { "aheadOn": [ "Reliability, 59 against 5", "Schema \u0026 documentation, 56 against 7", "Agent ergonomics, 65 against 4", "Security \u0026 auth, 41 against 6", "Payments \u0026 pricing, 60 against 10", "Maintenance \u0026 community, 68 against 3", "Transparency \u0026 trust, 55 against 46" ], "also": [ "No key needed to call it", "Free to start without a card", "Open source" ], "goodFor": "An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.", "slug": "hyperqwen", "watchFor": "Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap" } ], "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-ghost-core.json", "title": "AnythingLLM vs Core", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-ghost-core" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.json", "title": "AnythingLLM vs HyperQwen", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/berth-vs-ghost-core.json", "title": "Berth vs Core", "url": "https://www.anchorterminal.com/compare/berth-vs-ghost-core" }, { "json": "https://www.anchorterminal.com/compare/berth-vs-hyperqwen.json", "title": "Berth vs HyperQwen", "url": "https://www.anchorterminal.com/compare/berth-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-ghost-core.json", "title": "BitRun vs Core", "url": "https://www.anchorterminal.com/compare/bitrun-vs-ghost-core" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.json", "title": "BitRun vs HyperQwen", "url": "https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ghost-core.json", "title": "Docker Model Runner vs Core", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ghost-core" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-hyperqwen.json", "title": "Docker Model Runner vs HyperQwen", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-ghost-core.json", "title": "Foundry Local vs Core", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-ghost-core" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.json", "title": "Foundry Local vs HyperQwen", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-gpt4all.json", "title": "Core vs GPT4All", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-gpt4all" }, { "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-khoj.json", "title": "Core vs Khoj", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-koboldcpp.json", "title": "Core vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-lemonade.json", "title": "Core vs Lemonade", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-llama-cpp.json", "title": "Core vs llama.cpp", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-lm-studio.json", "title": "Core vs LM Studio", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-localai.json", "title": "Core vs LocalAI", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-mlx-lm.json", "title": "Core vs MLX LM", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-mlx-lm" }, { "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-open-webui.json", "title": "Core vs Open WebUI", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-screenpipe.json", "title": "Core vs screenpipe", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-text-generation-webui.json", "title": "Core vs TextGen", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-vllm.json", "title": "Core vs vLLM", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen.json", "title": "GPT4All vs HyperQwen", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen" }, { "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-khoj.json", "title": "HyperQwen vs Khoj", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.json", "title": "HyperQwen vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade.json", "title": "HyperQwen vs Lemonade", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp.json", "title": "HyperQwen vs llama.cpp", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio.json", "title": "HyperQwen vs LM Studio", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-localai.json", "title": "HyperQwen vs LocalAI", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm.json", "title": "HyperQwen vs MLX LM", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm" }, { "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-open-webui.json", "title": "HyperQwen vs Open WebUI", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe.json", "title": "HyperQwen vs screenpipe", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui.json", "title": "HyperQwen vs TextGen", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-vllm.json", "title": "HyperQwen vs vLLM", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-localghost.json", "title": "Core vs LocalGhost", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-underdog.json", "title": "Core vs Underdog", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-underdog" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-underdog.json", "title": "HyperQwen vs Underdog", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-underdog" } ], "scores": [ { "by": 54, "edge": "hyperqwen", "ghost-core": 5, "hyperqwen": 59, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 49, "edge": "hyperqwen", "ghost-core": 7, "hyperqwen": 56, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 61, "edge": "hyperqwen", "ghost-core": 4, "hyperqwen": 65, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 35, "edge": "hyperqwen", "ghost-core": 6, "hyperqwen": 41, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 50, "edge": "hyperqwen", "ghost-core": 10, "hyperqwen": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 65, "edge": "hyperqwen", "ghost-core": 3, "hyperqwen": 68, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 9, "edge": "hyperqwen", "ghost-core": 46, "hyperqwen": 55, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "HyperQwen scores 56.9 (C) on agent readiness against Core's 7.4 (F), and leads in every scored category. Both do local inference.", "tutorials": [], "verdicts": { "ghost-core": "Ghost's privacy policy sets out what stays on Core, what passes through its gateway and relay, and how long Ghost keeps each record. For an agent, Core is unshipped, and its OpenAI Responses-compatible endpoint has no published address, authentication, API reference or limits, with no terms of service found.", "hyperqwen": "HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen", "json": "https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.min.md" }, "markdown": "HyperQwen scores 56.9 (C) on agent readiness against Core's 7.4 (F), and leads in every scored category. Both do local inference.\n\n- Core: grade F, 7.4/100, rank #1239 of 1239. Markdown https://www.anchorterminal.com/tools/ghost-core.md · JSON https://www.anchorterminal.com/api/v1/tools/ghost-core.json\n- HyperQwen: grade C, 56.9/100, rank #738 of 1239. Markdown https://www.anchorterminal.com/tools/hyperqwen.md · JSON https://www.anchorterminal.com/api/v1/tools/hyperqwen.json\n- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md\n- All 253 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md\n\n## Which one, for what\n\n### Core (F)\n\nGood for: A household that wants a dedicated box running open-weight models and a memory of its apps, files and devices at home, with a one-off price and no subscription, once it ships.\n\nWatch for: Not shipped on 5 October 2026. Batch 1 is scheduled for 31 October and showed sold out that evening\n\n### HyperQwen (C)\n\nGood for: An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.\n\nAhead on:\n- Reliability, 59 against 5\n- Schema \u0026 documentation, 56 against 7\n- Agent ergonomics, 65 against 4\n- Security \u0026 auth, 41 against 6\n- Payments \u0026 pricing, 60 against 10\n- Maintenance \u0026 community, 68 against 3\n- Transparency \u0026 trust, 55 against 46\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- Open source\n\nWatch for: Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap\n\n\n## Score by category\n\n| Category | Weight | Core | HyperQwen | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 5 | 59 | HyperQwen +54 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 7 | 56 | HyperQwen +49 |\n| Agent ergonomics | 13% (16.2 this run) | 4 | 65 | HyperQwen +61 |\n| Security \u0026 auth | 14% (17.5 this run) | 6 | 41 | HyperQwen +35 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 10 | 60 | HyperQwen +50 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 3 | 68 | HyperQwen +65 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 46 | 55 | HyperQwen +9 |\n| Negative events | ≤15 | -2 | 0 | |\n| **Total** | | **7.4 · F** | **56.9 · C** | |\n\n## Facts side by side\n\n| Fact | Core | HyperQwen |\n| --- | --- | --- |\n| Kind | Platform | HTTP API |\n| Vendor | Ghost (ZMJ, Inc.) | syv.ai (syv-ai on GitHub) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | None |\n| Pricing | Paid | Free |\n| x402 | no | no |\n| Licence | Not stated. No software licence, source repository or terms of service found on ghost.ai (checked 2026-10-05). Models listed are Qwen 3.8-Next, Qwen 3.8-27B, Gemma 4-31B and Muse-Glimmer-30B. Ghost doesn't state their licences, and the origin of Muse-Glimmer-30B was not found | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | 2026-10-05 | no date given |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Popularity | none | 2.4k stars |\n| Agent reviews | 2/5 (1) | none |\n\n## Verdicts\n\n**Core.** Ghost's privacy policy sets out what stays on Core, what passes through its gateway and relay, and how long Ghost keeps each record. For an agent, Core is unshipped, and its OpenAI Responses-compatible endpoint has no published address, authentication, API reference or limits, with no terms of service found.\n\n**HyperQwen.** HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy.\n\n## Before you call either\n\n### Core\n\n1. Don't plan on reaching a Core before 31 October 2026. Batch 1 hadn't shipped, and new orders showed sold out on 5 October\n2. Ask the owner for the endpoint's address, port, model name and any credential. Ghost documents none of them\n3. Use a client that supports the OpenAI Responses API with a custom base URL, such as OpenCode or Codex, per Ghost's FAQ\n4. Don't assume a context length or output limit. Ghost states none for Qwen 3.8-Next, Qwen 3.8-27B, Gemma 4-31B or Muse-Glimmer-30B\n5. Treat memory and connected-account content as untrusted, and confirm with the owner before acting through imported browser sessions\n\n### HyperQwen\n\n1. Call http://127.0.0.1:18020/v1 with model `qwen3.8-27b` and the `VLLM_API_KEY` value, or any string if no key was set\n2. Poll `/health` before the first request. A first start downloads and prepares the model and compiles kernels, which can take over 30 minutes\n3. Declare the context window your setup uses (65,536 by default, 131,072 for `CTX=long`, 245,760 for `CTX=huge`) so the client doesn't truncate\n4. Ask the owner to set `VLLM_API_KEY` before setting `BIND=0.0.0.0`, and to front the port with a proxy that allowlists routes\n5. Treat the README's tokens-per-second figures as the project's measurements on one RTX 3090 at 250 W\n\n## Questions\n\n### Which is better for AI agents, Core or HyperQwen?\n\nHyperQwen scores 56.9 (C) on agent readiness against Core's 7.4 (F), and leads in every scored category.\n\n### Can an agent call Core and HyperQwen without installing anything?\n\nNo hosted endpoint is listed for Core. No hosted endpoint is listed for HyperQwen.\n\n### Are Core and HyperQwen open source?\n\nNo open-source release is listed for Core. HyperQwen is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"ghost-core\", \"b\": \"hyperqwen\"}`. From a terminal: `anchor compare ghost-core hyperqwen`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ghost-core.json and https://www.anchorterminal.com/api/v1/tools/hyperqwen.json\n\n## Other comparisons with Core or HyperQwen\n\n- [AnythingLLM vs Core](https://www.anchorterminal.com/compare/anythingllm-vs-ghost-core.md)\n- [AnythingLLM vs HyperQwen](https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.md)\n- [Berth vs Core](https://www.anchorterminal.com/compare/berth-vs-ghost-core.md)\n- [Berth vs HyperQwen](https://www.anchorterminal.com/compare/berth-vs-hyperqwen.md)\n- [BitRun vs Core](https://www.anchorterminal.com/compare/bitrun-vs-ghost-core.md)\n- [BitRun vs HyperQwen](https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.md)\n- [Docker Model Runner vs Core](https://www.anchorterminal.com/compare/docker-model-runner-vs-ghost-core.md)\n- [Docker Model Runner vs HyperQwen](https://www.anchorterminal.com/compare/docker-model-runner-vs-hyperqwen.md)\n- [Foundry Local vs Core](https://www.anchorterminal.com/compare/foundry-local-vs-ghost-core.md)\n- [Foundry Local vs HyperQwen](https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.md)\n- [Core vs GPT4All](https://www.anchorterminal.com/compare/ghost-core-vs-gpt4all.md)\n- [Core vs Jan](https://www.anchorterminal.com/compare/ghost-core-vs-jan.md)\n- [Core vs Khoj](https://www.anchorterminal.com/compare/ghost-core-vs-khoj.md)\n- [Core vs KoboldCpp](https://www.anchorterminal.com/compare/ghost-core-vs-koboldcpp.md)\n- [Core vs Lemonade](https://www.anchorterminal.com/compare/ghost-core-vs-lemonade.md)\n- [Core vs llama.cpp](https://www.anchorterminal.com/compare/ghost-core-vs-llama-cpp.md)\n- [Core vs LM Studio](https://www.anchorterminal.com/compare/ghost-core-vs-lm-studio.md)\n- [Core vs LocalAI](https://www.anchorterminal.com/compare/ghost-core-vs-localai.md)\n- [Core vs MLX LM](https://www.anchorterminal.com/compare/ghost-core-vs-mlx-lm.md)\n- [Core vs Ollama](https://www.anchorterminal.com/compare/ghost-core-vs-ollama.md)\n- [Core vs Open WebUI](https://www.anchorterminal.com/compare/ghost-core-vs-open-webui.md)\n- [Core vs screenpipe](https://www.anchorterminal.com/compare/ghost-core-vs-screenpipe.md)\n- [Core vs TextGen](https://www.anchorterminal.com/compare/ghost-core-vs-text-generation-webui.md)\n- [Core vs vLLM](https://www.anchorterminal.com/compare/ghost-core-vs-vllm.md)\n- [GPT4All vs HyperQwen](https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen.md)\n- [HyperQwen vs Jan](https://www.anchorterminal.com/compare/hyperqwen-vs-jan.md)\n- [HyperQwen vs Khoj](https://www.anchorterminal.com/compare/hyperqwen-vs-khoj.md)\n- [HyperQwen vs KoboldCpp](https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.md)\n- [HyperQwen vs Lemonade](https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade.md)\n- [HyperQwen vs llama.cpp](https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp.md)\n- [HyperQwen vs LM Studio](https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio.md)\n- [HyperQwen vs LocalAI](https://www.anchorterminal.com/compare/hyperqwen-vs-localai.md)\n- [HyperQwen vs MLX LM](https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm.md)\n- [HyperQwen vs Ollama](https://www.anchorterminal.com/compare/hyperqwen-vs-ollama.md)\n- [HyperQwen vs Open WebUI](https://www.anchorterminal.com/compare/hyperqwen-vs-open-webui.md)\n- [HyperQwen vs screenpipe](https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe.md)\n- [HyperQwen vs TextGen](https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui.md)\n- [HyperQwen vs vLLM](https://www.anchorterminal.com/compare/hyperqwen-vs-vllm.md)\n- [Core vs LocalGhost](https://www.anchorterminal.com/compare/ghost-core-vs-localghost.md)\n- [Core vs Underdog](https://www.anchorterminal.com/compare/ghost-core-vs-underdog.md)\n- [HyperQwen vs Underdog](https://www.anchorterminal.com/compare/hyperqwen-vs-underdog.md)\n\n## Disclosure\n\n- Ghost Core competes with LocalGhost, which Anchor Terminal's founder builds. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.\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": "2026-10-31", "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": "Core vs HyperQwen", "url": "" } ], "description": "HyperQwen scores 56.9 (C) to Core's 7.4 (F) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Core F 7.4", "HyperQwen C 56.9", "scores" ], "h1": "Core vs HyperQwen", "image": "https://www.anchorterminal.com/assets/og/compare-ghost-core-vs-hyperqwen.png", "path": "/compare/ghost-core-vs-hyperqwen", "published": "2026-10-01", "section": "tools", "title": "Core vs HyperQwen for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-30", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen" }, "tokens": { "markdown": 2850, "slim": 630 }, "version": 1 }