{ "data": { "a": { "slug": "lemonade", "name": "Lemonade", "vendor": "AMD and the Lemonade community", "vendorUrl": "https://lemonade-server.ai", "kind": "http-api", "category": "local-ai", "summary": "Open-source local AI server from AMD and community contributors. It runs text, speech and image models on the owner's CPU, GPU or NPU behind OpenAI-, Anthropic- and Ollama-compatible APIs and an MCP endpoint on port 13305.", "url": "https://www.anchorterminal.com/tools/lemonade", "markdownUrl": "https://www.anchorterminal.com/tools/lemonade.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lemonade.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lemonade.json", "repo": "https://github.com/lemonade-sdk/lemonade", "license": "Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "ghcr.io/lemonade-sdk/lemonade-server" } ], "auth": "api-key", "authNotes": "Off by default. With no key set, every endpoint answers without authentication, on a default bind of localhost. `LEMONADE_API_KEY` sets one bearer key for the regular API (`/api/*`, `/v0/*`, `/v1/*`, `/mcp` and `/metrics`). `LEMONADE_ADMIN_API_KEY` sets a second key for the internal control endpoints (`/internal/*`), and without it the regular key reaches those too. Both are environment variables, so there are no per-user keys. The docs tell WebSocket clients to pass `?api_key=KEY` in the URL.", "pricing": "free", "pricingNotes": "Free and Apache 2.0 with nothing to buy and no account. You run it on your own hardware. Cloud Offload, which is optional and experimental, bills through the owner's own keys at whichever cloud provider they add.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-08).", "endpoints": [] }, "toolCount": 6, "popularity": { "githubStars": 5800, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://lemonade-server.ai/docs/", "capabilities": [ "inference.local", "inference.open-weights", "embed.text", "rerank", "speech.stt", "speech.tts", "image.generate" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "openai-compatible", "mcp", "streaming", "open-weights", "amd", "npu", "docker" ], "lastRelease": "2026-10-07", "graded": true, "anchor": { "graded": true, "score": 63.8, "grade": "B", "agentReady": false, "rank": 336, "ranked": true, "rankOf": 842, "categoryRank": 2, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 76, "payments": 60, "reliability": 75, "schema": 70, "security": 36, "transparency": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "Apache 2.0, with weekly releases, installers for Windows, macOS and five Linux routes, and a six-tool MCP endpoint whose descriptions steer a caller away from accidental multi-gigabyte downloads. Authentication is off by default, the repository has no security policy, and the docs tell WebSocket clients to pass the key in the URL.", "bestFor": "An owner with AMD hardware (Ryzen AI NPUs, Radeon or Strix Halo) who wants one local server for chat, speech and images that existing OpenAI, Anthropic or Ollama clients can call, and for MCP clients that want local models as tools.", "strengths": [ "Apache 2.0, with OpenAI, Anthropic Messages, Ollama and llama.cpp-compatible routes on one port (13305)", "`POST /mcp` exposes six tools over Streamable HTTP, and omitting `model` reuses a loaded or downloaded model before any download", "Every running server returns its own Markdown API reference at `GET /v1/docs` and through the `lemonade_docs` tool, so it matches the installed version", "Stable release v2026.41.1 on 7 October 2026 on a weekly cadence, each with a Breaking Changes section in its notes", "Telemetry is off by default and exports OTLP traces only to an endpoint the operator sets, with switches to redact prompts and outputs" ], "weaknesses": [ "No authentication by default. With no key set, every route answers, including `/internal/*` shutdown and configuration", "GitHub reports no `SECURITY.md`, and we found no security.txt, advisory or disclosure address", "The docs tell WebSocket clients to send the key as `?api_key=KEY` in the URL", "No OpenAPI file in the repository, and no `readOnlyHint` or `destructiveHint` on the MCP tools", "The main build and test workflow's badge read failing on main on 8 October 2026, with 411 issues open" ], "agentNotes": [ "Call `lemonade_list_models` (or `GET /v1/models`) before naming a model. A wrong name with `allow_download: true` can start a multi-gigabyte download", "Send `Authorization: Bearer \u003ckey\u003e` when the operator has set `LEMONADE_API_KEY`. `/internal/*` needs the admin key when one is set", "Use `POST /v1/chat/completions` for streamed tokens, embeddings and speech. The MCP endpoint ignores `stream` and has no embeddings or text-to-speech tool", "Pass `output_dir` to `lemonade_generate_image` and `lemonade_omni` to get file paths in place of inline base64. Writes stay inside the MCP media sandbox", "Read `GET /v1/docs` on the running server for the reference that matches its version. Weekly releases change behaviour" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 63.8 } ], "editorialScores": { "ergonomics": 70, "maintenance": 76, "payments": 60, "reliability": 75, "schema": 70, "security": 36, "transparency": 70 }, "provenanceScore": 57 }, "connect": { "install": "winget install --id AMD.LemonadeServer -e", "http": "curl http://localhost:13305/api/v1/chat/completions -H \"Content-Type: application/json\" -d '{\"model\": \"your-model-name\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello\"}]}'", "claudeCode": "lemonade launch claude" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/lemonade" }, "area": "models", "provenance": { "legalEntity": "Advanced Micro Devices, Inc.", "domain": "lemonade-server.ai", "domainRegistered": "2025-05-12", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/lemonade-sdk/lemonade/releases", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The website footer reads \"© 2026 AMD. Licensed under Apache 2.0\", and `contrib/debian/copyright` in the repository names Advanced Micro Devices, Inc. The code lives in the lemonade-sdk organisation on GitHub, and the README calls it a community project with optimisations by AMD engineers.", "We found no terms of service and no privacy policy for the software or the website. The home page and its footer link to neither, so both fields are empty.", "lemonade-server.ai/.well-known/security.txt, /security.txt and /llms.txt return 404.", "RDAP gives a registration date of 2025-05-12 for lemonade-server.ai, with Porkbun LLC as registrar and the registrant behind a privacy service.", "There's no hosted endpoint. Each instance answers on the owner's own machine, by default localhost port 13305." ], "score": 57 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/lemonade.json" }, "answer": "Lemonade scores 63.8 (B) on agent readiness against LM Studio's 57.8 (C), and leads in 5 of 7 scored categories. LM Studio leads on security \u0026 auth.", "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": 57.8, "grade": "C", "agentReady": false, "rank": 536, "ranked": true, "rankOf": 842, "categoryRank": 7, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 72, "payments": 60, "reliability": 34, "schema": 64, "security": 59, "transparency": 60 }, "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.", "bestFor": "A machine that serves open models to several agents and tools at once, in whichever API shape each client already speaks, and for headless serving on Linux with llmster.", "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": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 57.8 } ], "editorialScores": { "ergonomics": 69, "maintenance": 72, "payments": 60, "reliability": 34, "schema": 64, "security": 59, "transparency": 55 }, "provenanceScore": 64 }, "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": 64 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/lm-studio.json", "live": { "slug": "lm-studio", "versions": [ { "registry": "npm", "name": "@lmstudio/sdk", "version": "2.0.0", "seenAt": "2026-10-08T16:19:13.202632377Z" }, { "registry": "pypi", "name": "lmstudio", "version": "1.5.0", "released": "2025-08-22", "seenAt": "2026-10-08T16:19:15.693939311Z" } ], "githubStars": 1785, "npmWeekly": 68608, "pypiWeekly": 15573, "securityTxt": { "url": "https://lmstudio.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:49.288545624Z" }, "llmsTxt": { "url": "https://lmstudio.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-08T14:00:34.665371609Z" }, "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": "2026-10-08T18:21:42.054043981Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "861d11ad807a" }, { "url": "https://lmstudio.ai/app-privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:21:37.539449608Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "2be7166b913e" }, { "url": "https://lmstudio.ai/app-terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:21:40.28202344Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "90222f50fb4b" } ], "updatedAt": "2026-10-08T18:21:42.054043981Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "AMD and the Lemonade community", "b": "Element Labs, Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence", "b": "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", "name": "Licence" }, { "a": "6", "b": "none", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-07", "b": "2026-09-19", "name": "Last release" }, { "a": "no document linked", "b": "no date given", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-06-01", "name": "Privacy policy last updated" }, { "a": "", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "5.8k stars", "b": "69k npm/wk, 15k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "2.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Lemonade scores 63.8 (B) on agent readiness against LM Studio's 57.8 (C), and leads in 5 of 7 scored categories. LM Studio leads on security \u0026 auth.", "question": "Which is better for AI agents, Lemonade or LM Studio?" }, { "answer": "Both need an API key.", "question": "Do Lemonade and LM Studio need an API key?" }, { "answer": "No hosted endpoint is listed for Lemonade. No hosted endpoint is listed for LM Studio.", "question": "Can an agent call Lemonade and LM Studio without installing anything?" }, { "answer": "Lemonade is open source (Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence). No open-source release is listed for LM Studio.", "question": "Are Lemonade and LM Studio open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 75 against 34", "Schema \u0026 documentation, 70 against 64" ], "also": [ "Open source" ], "goodFor": "An owner with AMD hardware (Ryzen AI NPUs, Radeon or Strix Halo) who wants one local server for chat, speech and images that existing OpenAI, Anthropic or Ollama clients can call, and for MCP clients that want local models as tools.", "slug": "lemonade", "watchFor": "No authentication by default. With no key set, every route answers, including `/internal/*` shutdown and configuration" }, { "aheadOn": [ "Security \u0026 auth, 59 against 36" ], "also": null, "goodFor": "A machine that serves open models to several agents and tools at once, in whichever API shape each client already speaks, and for headless serving on Linux with llmster.", "slug": "lm-studio", "watchFor": "Authentication is off by default, so any local process can call the server" } ], "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-lemonade.json", "title": "AnythingLLM vs Lemonade", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-lm-studio.json", "title": "AnythingLLM vs LM Studio", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.json", "title": "Docker Model Runner vs Lemonade", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lm-studio.json", "title": "Docker Model Runner vs LM Studio", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-lemonade.json", "title": "Foundry Local vs Lemonade", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-lm-studio.json", "title": "Foundry Local vs LM Studio", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-lm-studio" }, { "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-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/gpt4all-vs-lemonade.json", "title": "GPT4All vs Lemonade", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.json", "title": "GPT4All vs LM Studio", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-lemonade.json", "title": "Jan vs Lemonade", "url": "https://www.anchorterminal.com/compare/jan-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-lm-studio.json", "title": "Jan vs LM Studio", "url": "https://www.anchorterminal.com/compare/jan-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-lemonade.json", "title": "Khoj vs Lemonade", "url": "https://www.anchorterminal.com/compare/khoj-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-lm-studio.json", "title": "Khoj vs LM Studio", "url": "https://www.anchorterminal.com/compare/khoj-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade.json", "title": "KoboldCpp vs Lemonade", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-lm-studio.json", "title": "KoboldCpp vs LM Studio", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-llama-cpp.json", "title": "Lemonade vs llama.cpp", "url": "https://www.anchorterminal.com/compare/lemonade-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-localai.json", "title": "Lemonade vs LocalAI", "url": "https://www.anchorterminal.com/compare/lemonade-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.json", "title": "Lemonade vs MLX LM", "url": "https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm" }, { "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-open-webui.json", "title": "Lemonade vs Open WebUI", "url": "https://www.anchorterminal.com/compare/lemonade-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-screenpipe.json", "title": "Lemonade vs screenpipe", "url": "https://www.anchorterminal.com/compare/lemonade-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui.json", "title": "Lemonade vs TextGen", "url": "https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/llama-cpp-vs-lm-studio.json", "title": "llama.cpp vs LM Studio", "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-localai.json", "title": "LM Studio vs LocalAI", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-mlx-lm.json", "title": "LM Studio vs MLX LM", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-mlx-lm" }, { "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-open-webui.json", "title": "LM Studio vs Open WebUI", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-screenpipe.json", "title": "LM Studio vs screenpipe", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-text-generation-webui.json", "title": "LM Studio vs TextGen", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-underdog.json", "title": "Lemonade vs Underdog", "url": "https://www.anchorterminal.com/compare/lemonade-vs-underdog" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-underdog.json", "title": "LM Studio vs Underdog", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-underdog" } ], "scores": [ { "by": 41, "edge": "lemonade", "key": "reliability", "lemonade": 75, "lm-studio": 34, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 6, "edge": "lemonade", "key": "schema", "lemonade": 70, "lm-studio": 64, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 1, "edge": "lemonade", "key": "ergonomics", "lemonade": 70, "lm-studio": 69, "name": "Agent ergonomics", "weight": 13 }, { "by": 23, "edge": "lm-studio", "key": "security", "lemonade": 36, "lm-studio": 59, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "lemonade": 60, "lm-studio": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 4, "edge": "lemonade", "key": "maintenance", "lemonade": 76, "lm-studio": 72, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 4, "edge": "lemonade", "key": "transparency", "lemonade": 64, "lm-studio": 60, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Lemonade scores 63.8 (B) on agent readiness against LM Studio's 57.8 (C), and leads in 5 of 7 scored categories. LM Studio leads on security \u0026 auth. Both do local inference.", "verdicts": { "lemonade": "Apache 2.0, with weekly releases, installers for Windows, macOS and five Linux routes, and a six-tool MCP endpoint whose descriptions steer a caller away from accidental multi-gigabyte downloads. Authentication is off by default, the repository has no security policy, and the docs tell WebSocket clients to pass the key in the URL.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/lemonade-vs-lm-studio", "json": "https://www.anchorterminal.com/compare/lemonade-vs-lm-studio.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/lemonade-vs-lm-studio.md", "slim": "https://www.anchorterminal.com/compare/lemonade-vs-lm-studio.min.md" }, "markdown": "Lemonade scores 63.8 (B) on agent readiness against LM Studio's 57.8 (C), and leads in 5 of 7 scored categories. LM Studio leads on security \u0026 auth. Both do local inference.\n\n- Lemonade: grade B, 63.8/100, rank #336 of 842. Markdown https://www.anchorterminal.com/tools/lemonade.md · JSON https://www.anchorterminal.com/api/v1/tools/lemonade.json\n- LM Studio: grade C, 57.8/100, rank #536 of 842. 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\n### Lemonade (B)\n\nGood for: An owner with AMD hardware (Ryzen AI NPUs, Radeon or Strix Halo) who wants one local server for chat, speech and images that existing OpenAI, Anthropic or Ollama clients can call, and for MCP clients that want local models as tools.\n\nAhead on:\n- Reliability, 75 against 34\n- Schema \u0026 documentation, 70 against 64\n\nAlso in its favour:\n- Open source\n\nWatch for: No authentication by default. With no key set, every route answers, including `/internal/*` shutdown and configuration\n\n### LM Studio (C)\n\nGood for: A machine that serves open models to several agents and tools at once, in whichever API shape each client already speaks, and for headless serving on Linux with llmster.\n\nAhead on:\n- Security \u0026 auth, 59 against 36\n\nWatch for: Authentication is off by default, so any local process can call the server\n\n\n## Score by category\n\n| Category | Weight | Lemonade | LM Studio | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 75 | 34 | Lemonade +41 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 70 | 64 | Lemonade +6 |\n| Agent ergonomics | 13% (16.2 this run) | 70 | 69 | Lemonade +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 36 | 59 | LM Studio +23 |\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) | 76 | 72 | Lemonade +4 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 60 | Lemonade +4 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **63.8 · B** | **57.8 · C** | |\n\n## Facts side by side\n\n| Fact | Lemonade | LM Studio |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | AMD and the Lemonade community | Element Labs, Inc. |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence | 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 | 6 | none |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-07 | 2026-09-19 |\n| Terms last updated | no document linked | no date given |\n| Privacy policy last updated | no document linked | 2026-06-01 |\n| Customer content may train models | | not found in the text |\n| Terms restrict automated access | | not found in the text |\n| Terms restrict benchmarking | | not found in the text |\n| Terms or service can change without notice | | not found in the text |\n| Arbitration or class-action waiver | | not found in the text |\n| Popularity | 5.8k stars | 69k npm/wk, 15k PyPI/wk |\n| Agent reviews | none | 2.5/5 (2) |\n\n## Verdicts\n\n**Lemonade.** Apache 2.0, with weekly releases, installers for Windows, macOS and five Linux routes, and a six-tool MCP endpoint whose descriptions steer a caller away from accidental multi-gigabyte downloads. Authentication is off by default, the repository has no security policy, and the docs tell WebSocket clients to pass the key in the URL.\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### Lemonade\n\n1. Call `lemonade_list_models` (or `GET /v1/models`) before naming a model. A wrong name with `allow_download: true` can start a multi-gigabyte download\n2. Send `Authorization: Bearer \u003ckey\u003e` when the operator has set `LEMONADE_API_KEY`. `/internal/*` needs the admin key when one is set\n3. Use `POST /v1/chat/completions` for streamed tokens, embeddings and speech. The MCP endpoint ignores `stream` and has no embeddings or text-to-speech tool\n4. Pass `output_dir` to `lemonade_generate_image` and `lemonade_omni` to get file paths in place of inline base64. Writes stay inside the MCP media sandbox\n5. Read `GET /v1/docs` on the running server for the reference that matches its version. Weekly releases change behaviour\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## Questions\n\n### Which is better for AI agents, Lemonade or LM Studio?\n\nLemonade scores 63.8 (B) on agent readiness against LM Studio's 57.8 (C), and leads in 5 of 7 scored categories. LM Studio leads on security \u0026 auth.\n\n### Do Lemonade and LM Studio need an API key?\n\nBoth need an API key.\n\n### Can an agent call Lemonade and LM Studio without installing anything?\n\nNo hosted endpoint is listed for Lemonade. No hosted endpoint is listed for LM Studio.\n\n### Are Lemonade and LM Studio open source?\n\nLemonade is open source (Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence). No open-source release is listed for LM Studio.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/lemonade-vs-lm-studio.json, and with the fewest tokens: https://www.anchorterminal.com/compare/lemonade-vs-lm-studio.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"lemonade\", \"b\": \"lm-studio\"}`. From a terminal: `anchor compare lemonade lm-studio`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/lemonade.json and https://www.anchorterminal.com/api/v1/tools/lm-studio.json\n\n## Other comparisons with Lemonade or LM Studio\n\n- [AnythingLLM vs Lemonade](https://www.anchorterminal.com/compare/anythingllm-vs-lemonade.md)\n- [AnythingLLM vs LM Studio](https://www.anchorterminal.com/compare/anythingllm-vs-lm-studio.md)\n- [Docker Model Runner vs Lemonade](https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.md)\n- [Docker Model Runner vs LM Studio](https://www.anchorterminal.com/compare/docker-model-runner-vs-lm-studio.md)\n- [Foundry Local vs Lemonade](https://www.anchorterminal.com/compare/foundry-local-vs-lemonade.md)\n- [Foundry Local vs LM Studio](https://www.anchorterminal.com/compare/foundry-local-vs-lm-studio.md)\n- [Core vs Lemonade](https://www.anchorterminal.com/compare/ghost-core-vs-lemonade.md)\n- [Core vs LM Studio](https://www.anchorterminal.com/compare/ghost-core-vs-lm-studio.md)\n- [GPT4All vs Lemonade](https://www.anchorterminal.com/compare/gpt4all-vs-lemonade.md)\n- [GPT4All vs LM Studio](https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.md)\n- [Jan vs Lemonade](https://www.anchorterminal.com/compare/jan-vs-lemonade.md)\n- [Jan vs LM Studio](https://www.anchorterminal.com/compare/jan-vs-lm-studio.md)\n- [Khoj vs Lemonade](https://www.anchorterminal.com/compare/khoj-vs-lemonade.md)\n- [Khoj vs LM Studio](https://www.anchorterminal.com/compare/khoj-vs-lm-studio.md)\n- [KoboldCpp vs Lemonade](https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade.md)\n- [KoboldCpp vs LM Studio](https://www.anchorterminal.com/compare/koboldcpp-vs-lm-studio.md)\n- [Lemonade vs llama.cpp](https://www.anchorterminal.com/compare/lemonade-vs-llama-cpp.md)\n- [Lemonade vs LocalAI](https://www.anchorterminal.com/compare/lemonade-vs-localai.md)\n- [Lemonade vs MLX LM](https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.md)\n- [Lemonade vs Ollama](https://www.anchorterminal.com/compare/lemonade-vs-ollama.md)\n- [Lemonade vs Open WebUI](https://www.anchorterminal.com/compare/lemonade-vs-open-webui.md)\n- [Lemonade vs screenpipe](https://www.anchorterminal.com/compare/lemonade-vs-screenpipe.md)\n- [Lemonade vs TextGen](https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui.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 MLX LM](https://www.anchorterminal.com/compare/lm-studio-vs-mlx-lm.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- [LM Studio vs TextGen](https://www.anchorterminal.com/compare/lm-studio-vs-text-generation-webui.md)\n- [Lemonade vs Underdog](https://www.anchorterminal.com/compare/lemonade-vs-underdog.md)\n- [LM Studio vs Underdog](https://www.anchorterminal.com/compare/lm-studio-vs-underdog.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "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": "Lemonade vs LM Studio", "url": "" } ], "description": "Lemonade scores 63.8 (B) on agent readiness against LM Studio's 57.8 (C), and leads in 5 of 7 scored categories. LM Studio leads on security \u0026 auth. Both do local inference. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Lemonade B 63.8", "LM Studio C 57.8", "scores" ], "h1": "Lemonade vs LM Studio", "image": "https://www.anchorterminal.com/assets/og/compare-lemonade-vs-lm-studio.png", "path": "/compare/lemonade-vs-lm-studio", "published": "2026-10-01", "section": "tools", "title": "Lemonade vs LM Studio for AI agents, B 63.8 vs C 57.8", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/lemonade-vs-lm-studio" }, "tokens": { "markdown": 2650, "slim": 730 }, "version": 1 }