{ "data": { "a": { "slug": "gpt4all", "name": "GPT4All", "vendor": "Nomic, Inc.", "vendorUrl": "https://www.nomic.ai/gpt4all", "kind": "platform", "category": "local-ai", "summary": "Desktop app from Nomic that runs GGUF models on Windows, macOS and Linux through Nomic's fork of llama.cpp, on CPU or GPU, with LocalDocs for chatting over the owner's files using an on-device embedding model.", "url": "https://www.anchorterminal.com/tools/gpt4all", "markdownUrl": "https://www.anchorterminal.com/tools/gpt4all.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gpt4all.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gpt4all.json", "repo": "https://github.com/nomic-ai/gpt4all", "license": "MIT (app, backend and bindings). Models downloaded through the app carry their own licences", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "gpt4all" } ], "auth": "none", "authNotes": "The local API server has no authentication. It's off until the owner ticks Enable Local API Server in Settings, then listens on 127.0.0.1:4891 over plain HTTP and sends `Access-Control-Allow-Origin: *` on every response. Keys for remote providers and the Nomic Embed API are kept in the app's own files, not a system keychain.", "pricing": "free", "pricingNotes": "Free and MIT with nothing to buy. Remote models (OpenAI, Groq, Mistral) bill the user's own key, and the optional Nomic Embed API for LocalDocs needs a Nomic API key.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-03).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 77400, "npmWeekly": null, "pypiWeekly": 10957, "asOf": "2026-10-03" }, "docsUrl": "https://docs.gpt4all.io", "capabilities": [ "inference.local", "inference.open-weights", "memory.search", "embed.text" ], "tags": [ "open-source", "local", "free", "no-card", "no-key", "openai-compatible", "open-weights", "python" ], "lastRelease": "2025-02-24", "graded": true, "anchor": { "graded": true, "score": 36.3, "grade": "F", "agentReady": false, "rank": 438, "ranked": true, "rankOf": 452, "categoryRank": 11, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 41, "maintenance": 6, "payments": 60, "reliability": 56, "schema": 40, "security": 28, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-03" }, "negative": -6, "negativeNotes": [ "2026-06-26. Two security reports filed as public issues, unanswered, with no release since. #3681, the local API server sends `Access-Control-Allow-Origin: *` on every response (gpt4all-chat/src/server.cpp line 614) and has no authentication, so a web page open in the user's browser can call /v1/chat/completions while the server is on and read the answers, including LocalDocs snippets from the owner's files. #3682, the model catalogue and the fallback model download use plain http://gpt4all.io, and the app turns TLS certificate checks off on nine request sites. A host-header fix has sat unmerged on the mitigate-dns-rebind branch since 27 May 2025. Unfixed, with the server off by default, -6. https://github.com/nomic-ai/gpt4all/issues/3681; https://github.com/nomic-ai/gpt4all/issues/3682" ], "verdict": "MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware. No release since 24 February 2025 and no commit to main since 27 May 2025.", "strengths": [ "MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware", "Usage analytics and the Datalake stay off until the user opts in at first start, with the terms shown", "LocalDocs indexes local files with an on-device embedding model, and the API returns the snippets it used", "The local server listens on 127.0.0.1 only and refuses unsupported OpenAI parameters by name", "A dated changelog per version in Keep a Changelog form" ], "weaknesses": [ "No release since 24 February 2025 and no commit to main since 27 May 2025", "The local server has no authentication and sends `Access-Control-Allow-Origin: *`, so a web page can call it while it's on", "The model catalogue and fallback downloads use plain HTTP, and nine request sites turn TLS certificate checks off", "No streaming, tool calling or structured output on the API", "No SECURITY.md or security.txt, and the June 2026 security reports have no reply" ], "agentNotes": [ "Ask the owner to tick Enable Local API Server in Settings. Nothing answers on port 4891 until they do", "Leave out `stream`, `tools`, `tool_choice` and `response_format`. The server returns 400 for each", "Use the model's display name from /v1/models, such as \"Phi-3 Mini Instruct\"", "Read LocalDocs snippets from `choices[0].references`. Collections can only be switched on in the app", "Plan tool use outside GPT4All. Its API can't call tools" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 1, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "F", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 36.3 } ], "editorialScores": { "ergonomics": 41, "maintenance": 6, "payments": 60, "reliability": 56, "schema": 40, "security": 28, "transparency": 54 }, "provenanceScore": 59 }, "connect": { "install": "pip install gpt4all # Python SDK. The desktop app, which runs the API server, installs from https://gpt4all.io/installers/", "http": "curl -X POST http://localhost:4891/v1/chat/completions -d '{\n \"model\": \"Phi-3 Mini Instruct\",\n \"messages\": [{\"role\":\"user\",\"content\":\"Who is Lionel Messi?\"}],\n \"max_tokens\": 50,\n \"temperature\": 0.28\n}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/gpt4all" }, "area": "models", "provenance": { "legalEntity": "Nomic, Inc.", "domain": "nomic.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://www.nomic.ai/privacy", "statusPage": "", "changelog": "https://github.com/nomic-ai/gpt4all/blob/main/gpt4all-chat/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-03", "notes": [ "`LICENSE.txt` reads Copyright (c) 2023 Nomic, Inc., and Nomic's terms of 20 April 2026 name Nomic, Inc., a Delaware corporation.", "Nomic's terms at nomic.ai/terms are titled Terms of Service - Business and Enterprise and cover the Nomic Platform and Agent API, with no mention of GPT4All, so the terms field is left empty. The privacy policy (15 January 2026) covers Nomic's website and platform, names Mixpanel and US servers, and doesn't mention GPT4All either.", "nomic.ai/.well-known/security.txt returns 404, and the repository has no SECURITY.md.", "Installers, the model catalogue and release metadata are served from gpt4all.io, and docs from docs.gpt4all.io. There's no hosted endpoint, and the API server runs on the owner's machine." ], "score": 59 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gpt4all.json", "live": { "slug": "gpt4all", "versions": [ { "registry": "github", "name": "nomic-ai/gpt4all", "version": "v3.10.0", "released": "2025-02-25", "seenAt": "2026-10-04T16:29:09.461389939Z" }, { "registry": "pypi", "name": "gpt4all", "version": "2.8.2", "released": "2024-08-14", "seenAt": "2026-10-04T16:29:09.272667442Z" } ], "githubStars": 77389, "pypiWeekly": 11066, "securityTxt": { "url": "https://nomic.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-04T15:16:05.081218945Z" }, "domain": { "domain": "nomic.ai", "registered": "2021-10-22", "source": "https://rdap.identitydigital.services/rdap/domain/nomic.ai", "checkedAt": "2026-10-04T13:09:16.171290345Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/nomic-ai/gpt4all/main/gpt4all-chat/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-10-04T15:47:47.23724269Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "5e4e4d883d6e" }, { "url": "https://www.nomic.ai/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-04T15:51:26.446741226Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "f695eccff4e0" } ], "updatedAt": "2026-10-04T16:29:09.461389939Z" } }, "b": { "slug": "lm-studio", "name": "LM Studio", "vendor": "Element Labs, Inc.", "vendorUrl": "https://lmstudio.ai", "kind": "http-api", "category": "local-ai", "summary": "Desktop app and headless daemon from Element Labs for running open-weight models on the owner's machine with llama.cpp and MLX, plus the Splash engine on Apple silicon M3 or newer since 0.4.25.", "url": "https://www.anchorterminal.com/tools/lm-studio", "markdownUrl": "https://www.anchorterminal.com/tools/lm-studio.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lm-studio.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lm-studio.json", "repo": "https://github.com/lmstudio-ai/lmstudio-js", "license": "Proprietary. The app and llmster are free for personal and internal business use under LM Studio's terms (Element Labs, Inc., effective 23 August 2026), with no source published. The `lms` CLI and the TypeScript and Python SDKs are MIT", "transports": [ "http" ], "packages": [ { "registry": "npm", "name": "@lmstudio/sdk" }, { "registry": "pypi", "name": "lmstudio" } ], "auth": "api-key", "authNotes": "No authentication by default. With Require Authentication on (Developer page, Server Settings, LM Studio 0.4.0 or later), every request needs an API token (`sk-lm-` prefix) as `Authorization: Bearer`, or `x-api-key` on the Anthropic-compatible endpoint. Tokens are named, carry permissions picked at creation, are shown once and can be edited or deleted. Calling the owner's mcp.json servers through the API needs authentication on. The server binds to localhost unless Serve on Local Network is on or `lms server start --bind 0.0.0.0` is used.", "pricing": "free", "pricingNotes": "The LM Studio app, llmster and the local server are free for personal and work use with no account or card (free at work since 8 July 2025, and the terms of 23 August 2026 cover internal business use). Element Labs sells cloud model plans for Bionic, its separate agent app, at $20 (Bionic+) and $100 (Pro) a month, which local use of LM Studio doesn't need (checked 2026-10-03).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the pricing page or the SDK source (checked 2026-10-03).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 69495, "pypiWeekly": 15195, "asOf": "2026-10-03" }, "docsUrl": "https://lmstudio.ai/docs/developer", "llmsTxt": "https://lmstudio.ai/llms.txt", "capabilities": [ "inference.local", "inference.open-weights", "agent.mcp-client", "embed.text" ], "tags": [ "local", "closed-source", "free", "no-card", "account-free", "openai-compatible", "llms-txt", "typescript", "python", "streaming", "pre-1.0" ], "lastRelease": "2026-09-19", "graded": true, "anchor": { "graded": true, "score": 57.9, "grade": "C", "agentReady": false, "rank": 287, "ranked": true, "rankOf": 452, "categoryRank": 4, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 72, "payments": 60, "reliability": 34, "schema": 64, "security": 59, "transparency": 61 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-03" }, "negative": 0, "verdict": "OpenAI-compatible chat completions, responses, completions and embeddings, Anthropic-compatible /v1/messages and a native /api/v1, all on one port. Authentication is off by default, so any local process can call the server.", "strengths": [ "OpenAI-compatible chat completions, responses, completions and embeddings, Anthropic-compatible /v1/messages and a native /api/v1, all on one port", "llmster, a headless daemon installed with one command, with a documented systemd setup for Linux servers", "Named API tokens with permissions, and API access to MCP servers behind two switches, one of which also needs authentication on", "Stateful chats with `previous_response_id`, `allowed_tools` per MCP integration and typed error objects", "Seven releases in the 90 days to 3 October 2026, each with dated notes" ], "weaknesses": [ "Authentication is off by default, so any local process can call the server", "Closed-source app and daemon with no public CI or test suite", "The Python SDK's last stable release (1.5.0, 22 August 2025) can't send API tokens, and the docs name an environment variable no release reads", "No OpenAPI file, and the llms.txt we read covers the 0.3 app, not the v1 REST API, tokens, llmster or MCP", "1.7k open issues in the public bug tracker" ], "agentNotes": [ "Send `Authorization: Bearer $LM_API_TOKEN` when the owner gives you a token. With Require Authentication on, every request needs it", "Pass `previous_response_id` to /api/v1/chat instead of resending the history, and `store: false` for one-off calls", "List models with `GET /api/v1/models` before naming one. A named model that's downloaded loads just in time", "Install the Python SDK pre-release (1.6.0b1) and pass `api_token` directly. It reads `LMSTUDIO_API_TOKEN`, not the `LM_API_TOKEN` the docs name", "Set `allowed_tools` on every MCP integration. Without it the model sees every tool on the server" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 57.9 } ], "editorialScores": { "ergonomics": 69, "maintenance": 72, "payments": 60, "reliability": 34, "schema": 64, "security": 59, "transparency": 55 }, "provenanceScore": 67 }, "connect": { "install": "curl -fsSL https://lmstudio.ai/install.sh | bash # llmster, the headless daemon. Windows: irm https://lmstudio.ai/install.ps1 | iex", "http": "curl http://localhost:1234/api/v1/chat \\\n -H \"Authorization: Bearer $LM_API_TOKEN\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"ibm/granite-4-micro\", \"input\": \"Write a short haiku about sunrise.\"}'", "claudeCode": "export ANTHROPIC_BASE_URL=http://localhost:1234\nexport ANTHROPIC_AUTH_TOKEN=lmstudio\nexport CLAUDE_CODE_ATTRIBUTION_HEADER=0\nclaude --model openai/gpt-oss-20b" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/lm-studio" }, "area": "models", "provenance": { "legalEntity": "Element Labs, Inc.", "domain": "lmstudio.ai", "domainRegistered": "2023-05-03", "endpointOnVendorDomain": null, "terms": "https://lmstudio.ai/app-terms", "privacy": "https://lmstudio.ai/app-privacy", "statusPage": "", "changelog": "https://lmstudio.ai/changelog/lmstudio", "securityTxt": "none", "checked": "2026-10-03", "notes": [ "The terms (effective 23 August 2026) and the privacy policy (effective June 2026) name Element Labs, Inc., a Delaware corporation at 251 Little Falls Drive, Wilmington.", "There's no hosted endpoint. The server answers on the owner's machine, at localhost:1234 by default.", "lmstudio.ai/.well-known/security.txt returns a Hub web page rather than a security.txt, and we found no security page or SECURITY.md in the public repositories.", "RDAP for lmstudio.ai gives a registration date of 2023-05-03.", "lmstudio.ai/changelog opens on Bionic, the separate agent app. LM Studio's releases are at /changelog/lmstudio." ], "score": 67 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/lm-studio.json", "live": { "slug": "lm-studio", "versions": [ { "registry": "npm", "name": "@lmstudio/sdk", "version": "2.0.0", "seenAt": "2026-10-04T16:31:57.979163993Z" }, { "registry": "pypi", "name": "lmstudio", "version": "1.5.0", "released": "2025-08-22", "seenAt": "2026-10-04T16:32:00.101781677Z" } ], "githubStars": 1786, "npmWeekly": 61084, "pypiWeekly": 14795, "securityTxt": { "url": "https://lmstudio.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-04T15:15:43.57855822Z" }, "llmsTxt": { "url": "https://lmstudio.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-04T15:17:57.079569518Z" }, "domain": { "domain": "lmstudio.ai", "registered": "2023-05-03", "source": "https://rdap.identitydigital.services/rdap/domain/lmstudio.ai", "checkedAt": "2026-10-04T13:08:39.466212979Z" }, "pages": [ { "url": "https://lmstudio.ai/changelog/lmstudio", "kind": "changelog", "status": 200, "checkedAt": "2026-10-04T15:45:43.124111793Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "861d11ad807a" }, { "url": "https://lmstudio.ai/app-privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-04T15:45:38.584198725Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "2be7166b913e" }, { "url": "https://lmstudio.ai/app-terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-04T15:45:40.97136456Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "90222f50fb4b" } ], "updatedAt": "2026-10-04T16:32:00.291286961Z" } }, "summary": "LM Studio has a score of 57.9 (C) against GPT4All's 36.3 (F). Both do local inference. The largest gap is maintenance \u0026 community, 66 points." }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio", "json": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.md", "slim": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.min.md" }, "markdown": "LM Studio has a score of 57.9 (C) against GPT4All's 36.3 (F). Both do local inference. The largest gap is maintenance \u0026 community, 66 points.\n\n- GPT4All: grade F, 36.3/100, rank #438 of 452. Markdown https://www.anchorterminal.com/tools/gpt4all.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt4all.json\n- LM Studio: grade C, 57.9/100, rank #287 of 452. Markdown https://www.anchorterminal.com/tools/lm-studio.md · JSON https://www.anchorterminal.com/api/v1/tools/lm-studio.json\n\n## Which one, for what\n\nPick GPT4All for reliability (+22).\n\nPick LM Studio for schema \u0026 documentation (+24), agent ergonomics (+28), security \u0026 auth (+31), maintenance \u0026 community (+66).\n\n## Score by category\n\n| Category | Weight | GPT4All | LM Studio | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 56 | 34 | GPT4All +22 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 40 | 64 | LM Studio +24 |\n| Agent ergonomics | 13% (16.2 this run) | 41 | 69 | LM Studio +28 |\n| Security \u0026 auth | 14% (17.5 this run) | 28 | 59 | LM Studio +31 |\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) | 6 | 72 | LM Studio +66 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 57 | 61 | LM Studio +4 |\n| Negative events | ≤15 | -6 | 0 | |\n| **Total** | | **36.3 · F** | **57.9 · C** | |\n\n## Facts side by side\n\n| Fact | GPT4All | LM Studio |\n| --- | --- | --- |\n| Kind | Model platform | HTTP API |\n| Vendor | Nomic, Inc. | Element Labs, Inc. |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | MIT (app, backend and bindings). Models downloaded through the app carry their own licences | Proprietary. The app and llmster are free for personal and internal business use under LM Studio's terms (Element Labs, Inc., effective 23 August 2026), with no source published. The `lms` CLI and the TypeScript and Python SDKs are MIT |\n| Tools exposed | none | none |\n| Context cost (tools/list) | n/a | n/a |\n| p95 latency | not measured yet | not measured yet |\n| Availability (30d) | not measured yet | not measured yet |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| MCP registry | not listed | not listed |\n| Last release | 2025-02-24 | 2026-09-19 |\n| Popularity | 77k stars, 11k PyPI/wk | 69k npm/wk, 15k PyPI/wk |\n| Agent reviews | 1/5 (2) | 2.5/5 (2) |\n\n## Verdicts\n\n**GPT4All.** MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware. No release since 24 February 2025 and no commit to main since 27 May 2025.\n\n**LM Studio.** OpenAI-compatible chat completions, responses, completions and embeddings, Anthropic-compatible /v1/messages and a native /api/v1, all on one port. Authentication is off by default, so any local process can call the server.\n\n## Before you call either\n\n### GPT4All\n\n1. Ask the owner to tick Enable Local API Server in Settings. Nothing answers on port 4891 until they do\n2. Leave out `stream`, `tools`, `tool_choice` and `response_format`. The server returns 400 for each\n3. Use the model's display name from /v1/models, such as \"Phi-3 Mini Instruct\"\n4. Read LocalDocs snippets from `choices[0].references`. Collections can only be switched on in the app\n5. Plan tool use outside GPT4All. Its API can't call tools\n\n### LM Studio\n\n1. Send `Authorization: Bearer $LM_API_TOKEN` when the owner gives you a token. With Require Authentication on, every request needs it\n2. Pass `previous_response_id` to /api/v1/chat instead of resending the history, and `store: false` for one-off calls\n3. List models with `GET /api/v1/models` before naming one. A named model that's downloaded loads just in time\n4. Install the Python SDK pre-release (1.6.0b1) and pass `api_token` directly. It reads `LMSTUDIO_API_TOKEN`, not the `LM_API_TOKEN` the docs name\n5. Set `allowed_tools` on every MCP integration. Without it the model sees every tool on the server\n\n## Other comparisons with GPT4All or LM Studio\n\n- [AnythingLLM vs GPT4All](https://www.anchorterminal.com/compare/anythingllm-vs-gpt4all.md)\n- [AnythingLLM vs LM Studio](https://www.anchorterminal.com/compare/anythingllm-vs-lm-studio.md)\n- [GPT4All vs Jan](https://www.anchorterminal.com/compare/gpt4all-vs-jan.md)\n- [GPT4All vs Khoj](https://www.anchorterminal.com/compare/gpt4all-vs-khoj.md)\n- [GPT4All vs llama.cpp](https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.md)\n- [GPT4All vs LocalAI](https://www.anchorterminal.com/compare/gpt4all-vs-localai.md)\n- [GPT4All vs Ollama](https://www.anchorterminal.com/compare/gpt4all-vs-ollama.md)\n- [GPT4All vs Open WebUI](https://www.anchorterminal.com/compare/gpt4all-vs-open-webui.md)\n- [GPT4All vs screenpipe](https://www.anchorterminal.com/compare/gpt4all-vs-screenpipe.md)\n- [Jan vs LM Studio](https://www.anchorterminal.com/compare/jan-vs-lm-studio.md)\n- [Khoj vs LM Studio](https://www.anchorterminal.com/compare/khoj-vs-lm-studio.md)\n- [llama.cpp vs LM Studio](https://www.anchorterminal.com/compare/llama-cpp-vs-lm-studio.md)\n- [LM Studio vs LocalAI](https://www.anchorterminal.com/compare/lm-studio-vs-localai.md)\n- [LM Studio vs Ollama](https://www.anchorterminal.com/compare/lm-studio-vs-ollama.md)\n- [LM Studio vs Open WebUI](https://www.anchorterminal.com/compare/lm-studio-vs-open-webui.md)\n- [LM Studio vs screenpipe](https://www.anchorterminal.com/compare/lm-studio-vs-screenpipe.md)\n- [GPT4All vs Underdog](https://www.anchorterminal.com/compare/gpt4all-vs-underdog.md)\n- [LM Studio vs Underdog](https://www.anchorterminal.com/compare/lm-studio-vs-underdog.md)\n- [GPT4All vs LocalGhost](https://www.anchorterminal.com/compare/gpt4all-vs-localghost.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-05", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.3", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "GPT4All vs LM Studio", "url": "" } ], "description": "LM Studio has a score of 57.9 (C) against GPT4All's 36.3 (F). Both do local inference. The largest gap is maintenance \u0026 community, 66 points. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "GPT4All F 36.3", "LM Studio C 57.9", "scores" ], "h1": "GPT4All vs LM Studio", "image": "https://www.anchorterminal.com/assets/og/compare-gpt4all-vs-lm-studio.png", "path": "/compare/gpt4all-vs-lm-studio", "published": "2026-10-01", "section": "tools", "title": "GPT4All vs LM Studio for AI agents, F 36.3 vs C 57.9 | Anchor Terminal", "toc": null, "updated": "2026-10-05", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio" }, "tokens": { "markdown": 1650, "slim": 330 }, "version": 1 }