{ "data": { "a": { "slug": "mlx-lm", "name": "MLX LM", "vendor": "Apple Inc.", "vendorUrl": "https://opensource.apple.com/projects/mlx/", "kind": "http-api", "category": "local-ai", "summary": "Open-source Python package and command-line tools from Apple's MLX team for running, quantising and fine-tuning language models on Apple silicon. `mlx_lm.server` exposes a local HTTP API modelled on OpenAI's chat completions.", "url": "https://www.anchorterminal.com/tools/mlx-lm", "markdownUrl": "https://www.anchorterminal.com/tools/mlx-lm.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mlx-lm.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mlx-lm.json", "repo": "https://github.com/ml-explore/mlx-lm", "license": "MIT", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "mlx-lm" } ], "auth": "none", "authNotes": "No credential, and no option to add one. `mlx_lm.server` binds 127.0.0.1:8080 by default, and `--allowed-origins` defaults to `*`, so any origin's requests are answered. Access control is left to the network or a proxy in front (https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/SERVER.md).", "pricing": "free", "pricingNotes": "Free under MIT, with no account, key or card. Nothing is sold. The owner pays for the hardware and electricity.", "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": null, "popularity": { "githubStars": 7300, "npmWeekly": null, "pypiWeekly": 139915, "asOf": "2026-10-08" }, "docsUrl": "https://github.com/ml-explore/mlx-lm/blob/main/mlx_lm/SERVER.md", "capabilities": [ "inference.local", "inference.open-weights" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "openai-compatible", "python", "pre-1.0", "no-auth", "no-telemetry" ], "lastRelease": "2026-10-01", "graded": true, "anchor": { "graded": true, "score": 52.2, "grade": "D", "agentReady": false, "rank": 657, "ranked": true, "rankOf": 842, "categoryRank": 12, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 54, "maintenance": 61, "payments": 60, "reliability": 66, "schema": 37, "security": 32, "transparency": 66 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "MIT, with no telemetry found in the source, and the tests passed on the last eight pushes to main. `mlx_lm.server` has no API key option, answers any origin by default and loads whichever model a request names, and its own docs say it is not recommended for production.", "bestFor": "An owner with an Apple silicon Mac who wants MLX-format models, local fine-tuning and quantisation from Python or the command line, with a simple local chat completions server.", "strengths": [ "MIT, with no telemetry, analytics or update check found in the source", "Installs from PyPI (`mlx-lm` 0.32.0, Python 3.11 or later) and conda-forge, with releases published to PyPI by trusted publishing from a GitHub workflow", "The Build and Test workflow passed on the last eight pushes to main, with 21 test files run on a macOS runner", "`mlx_lm.server` binds 127.0.0.1:8080 by default, caps output at 512 tokens unless told otherwise and validates field types and ranges with a 400", "127 commits from 82 authors on main in the 90 days to 8 October 2026" ], "weaknesses": [ "`mlx_lm.server` has no API key or other credential option, and `--allowed-origins` defaults to `*`", "A request's `model` and `adapters` fields make the server download or load any Hugging Face repository or local path, with no allow-list (open issue #1892)", "The docs and a start-up warning say the server is not recommended for production because it has only basic security checks", "No OpenAPI file or llms.txt, and `SERVER.md` leaves out `tools`, `seed`, `/health` and the error responses", "One PyPI release in 90 days (0.32.0 on 1 October 2026, the first since 0.31.3 on 22 April), and the version is still 0.x" ], "agentNotes": [ "Keep `mlx_lm.server` on 127.0.0.1 and pass `--allowed-origins` with the origins you trust. There is no API key, and the default answers every origin", "Treat any caller as able to load any model. The `model` and `adapters` request fields accept any Hugging Face repository or local path", "Send `max_tokens` or `max_completion_tokens` when you need more than 512 tokens, the server default", "Read errors as `{\"error\": \"\u003ctext\u003e\"}` with 400 for a bad field and 404 for a model that failed to load. They are not OpenAI error objects", "Poll `GET /health` before the first request. It answers 503 with `unavailable` when the generation thread has stopped" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.2 } ], "editorialScores": { "ergonomics": 54, "maintenance": 61, "payments": 60, "reliability": 66, "schema": 37, "security": 32, "transparency": 65 }, "provenanceScore": 67 }, "connect": { "install": "pip install mlx-lm\nmlx_lm.server --model mlx-community/Mistral-7B-Instruct-v0.3-4bit # listens on 127.0.0.1:8080", "http": "curl localhost:8080/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"messages\": [{\"role\": \"user\", \"content\": \"Say this is a test!\"}],\n \"temperature\": 0.7\n }'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/mlx-lm" }, "area": "models", "provenance": { "legalEntity": "Apple Inc.", "domain": "apple.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/ml-explore/mlx-lm/releases", "securityTxt": "valid", "checked": "2026-10-08", "notes": [ "The `LICENSE` file reads Copyright 2023 Apple Inc., and the package author on PyPI is MLX Contributors at a group.apple.com address. The repository sits in GitHub's ml-explore organisation and has no website of its own.", "opensource.apple.com/projects/mlx describes the MLX framework and does not name MLX LM. Its footer links Apple's website terms and general privacy policy, which do not govern this software, so terms and privacy are left empty.", "www.apple.com/.well-known/security.txt is valid until 6 October 2027 and is Apple's corporate file. The repository's own policy takes reports through GitHub private vulnerability reporting.", "There is no shared hosted endpoint. The server runs on the owner's machine." ], "score": 67 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mlx-lm.json" }, "answer": "MLX LM scores 52.2 (D) on agent readiness against TextGen's 45.1 (E), and leads in 4 of 7 scored categories. TextGen leads on schema \u0026 documentation and security \u0026 auth.", "b": { "slug": "text-generation-webui", "name": "TextGen", "vendor": "oobabooga", "vendorUrl": "https://github.com/oobabooga", "kind": "platform", "category": "local-ai", "summary": "Open-source desktop and browser app for running language models on the owner's hardware, formerly text-generation-webui. With `--api` it serves an OpenAI and Anthropic-compatible local API with tool calling, vision, embeddings and image generation.", "url": "https://www.anchorterminal.com/tools/text-generation-webui", "markdownUrl": "https://www.anchorterminal.com/tools/text-generation-webui.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/text-generation-webui.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/text-generation-webui.json", "repo": "https://github.com/oobabooga/textgen", "license": "AGPL-3.0", "transports": [ "http" ], "packages": [], "auth": "api-key", "authNotes": "The API takes one optional key from `--api-key`, off by default, sent as `Authorization: Bearer` on the OpenAI routes and as `x-api-key` on `/v1/messages`. A second key from `--admin-key` guards model and LoRA loading, unloading and listing, and equals the API key when unset. Keys are set at launch, have no scopes and change only with a restart. Without `--listen` or `--public-api` the server binds 127.0.0.1, rejects other Host headers and limits CORS to localhost. The web UI has no login unless `--gradio-auth` is set.", "pricing": "free", "pricingNotes": "Free and AGPL-3.0, with no account, card or paid edition. Portable builds and source are on GitHub (checked 2026-10-08).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the README, the docs folder or the API source (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 47700, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://github.com/oobabooga/textgen/wiki", "capabilities": [ "inference.local", "inference.open-weights", "agent.mcp-client", "embed.text", "image.generate" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "account-free", "openai-compatible", "open-weights", "streaming", "mcp", "docker", "no-telemetry" ], "lastRelease": "2026-05-20", "graded": true, "anchor": { "graded": true, "score": 45.1, "grade": "E", "agentReady": false, "rank": 775, "ranked": true, "rankOf": 842, "categoryRank": 15, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 50, "maintenance": 24, "payments": 60, "reliability": 51, "schema": 61, "security": 40, "transparency": 49 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": -4, "negativeNotes": [ "2026-03-18. Two Critical advisories at 9.1. GHSA-jg96-p5p6-q3cv (CVE-2026-35050) let a user of the web UI write Python files through a path traversal in extension settings and run them, in 4.1 and earlier, fixed in 4.1.1. GHSA-4p45-76cc-7p62 let a caller write or delete files through a character name on instances started with `--listen`, fixed in 4.0. Both fixed and published, -2. https://github.com/oobabooga/textgen/security/advisories/GHSA-jg96-p5p6-q3cv", "2026-03-18. GHSA-fpwc-4mvr-7jpr (High, 7.1). `/v1/chat/completions` and `/v1/completions` fetched any `image_url` from the server side, so a caller could reach internal addresses, in 4.1 and earlier. Fixed in 4.1.1 and published, -1. https://github.com/oobabooga/textgen/security/advisories/GHSA-fpwc-4mvr-7jpr", "2025-10-13 to 2026-04-03. Seven more advisories in the year, four High and three Moderate, among them a file read through an uploaded symbolic link, four path traversals in preset, grammar, template and prompt loading, an SSRF in the superbooga extensions and a Gradio path-check bypass fixed in 4.3. All published with fixes, -1. https://github.com/oobabooga/textgen/security" ], "verdict": "AGPL-3.0 with no telemetry, and a local API on 127.0.0.1:5000 that checks the Host header, limits CORS to localhost and separates an admin key from the caller's key. No release since v4.9 on 20 May 2026, no code commits since 31 May, no test suite, and ten security advisories in the year, all fixed.", "bestFor": "A person who wants one app for several backends (llama.cpp, ExLlamaV3, Transformers) with an OpenAI and Anthropic-compatible endpoint, LoRA training and image generation.", "strengths": [ "AGPL-3.0, with analytics switched off in the source and a README that states zero telemetry", "One server answers `/v1/chat/completions`, `/v1/completions` and Anthropic's `/v1/messages`, with tool calling and streaming", "Since v4.9 the API rejects Host headers other than localhost and 127.0.0.1 and limits CORS to localhost unless `--listen` or `--public-api` is set", "A separate `--admin-key` guards model and LoRA loading, apart from the `--api-key` callers use", "Ten security advisories published on GitHub with patched versions named, the newest on 3 April 2026" ], "weaknesses": [ "No release since v4.9 on 20 May 2026 and no code commit on `main` or `dev` since 31 May 2026", "No test suite. The seven GitHub workflows only build release packages on manual dispatch", "807 open issues and 40 open pull requests, with no SECURITY.md or disclosure address", "Two Critical advisories (9.1) published on 18 March 2026, both path traversals in the web UI, fixed in 4.0 and 4.1.1", "The API key is off by default, set only at launch, and has no scopes or per-client keys", "No rate limits, error list or published OpenAPI file in the docs. The schema is served only by a running server at `/docs`" ], "agentNotes": [ "Ask the owner to launch with `--api`. Nothing listens on port 5000 without it, and a model must be loaded first", "Call `http://127.0.0.1:5000/v1`. Any Host header other than localhost or 127.0.0.1 gets 400 `Invalid host header` unless `--listen` is set", "Send the key as `Authorization: Bearer` on OpenAI routes and as `x-api-key` on `/v1/messages`. Model loading needs the admin key", "Read `http://127.0.0.1:5000/docs` or `modules/api/typing.py` for parameters. `max_tokens` defaults to 512 on chat completions", "Run tool calls yourself. The API returns `finish_reason: \"tool_calls\"` and executes nothing on the server", "Use the repository name `oobabooga/textgen`. The old `text-generation-webui` URL redirects" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 45.1 } ], "editorialScores": { "ergonomics": 50, "maintenance": 24, "payments": 60, "reliability": 51, "schema": 61, "security": 40, "transparency": 70 }, "provenanceScore": 27 }, "connect": { "install": "git clone https://github.com/oobabooga/textgen\ncd textgen\npython -m venv venv\nsource venv/bin/activate\npip install -r requirements/portable/requirements.txt --upgrade\npython server.py --portable --api --auto-launch", "http": "curl http://127.0.0.1:5000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"temperature\": 0.6, \"top_p\": 0.95, \"top_k\": 20}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/text-generation-webui" }, "area": "models", "provenance": { "legalEntity": "", "domain": "github.com/oobabooga", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/oobabooga/textgen/releases", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The project belongs to a developer who publishes as oobabooga. The LICENSE is the AGPL-3.0 text and names no legal entity, and the README acknowledges a grant from Andreessen Horowitz in August 2023.", "No vendor domain. The README links only the GitHub repository, its wiki, a subreddit, a Substack and a Hugging Face space.", "No terms of use and no privacy policy were found in the repository, the README or the wiki, so both fields are left out. The README states zero telemetry.", "No SECURITY.md (the Security tab says none is set up) and no security.txt of the project's own.", "There's no hosted endpoint. The API answers on the owner's machine, at 127.0.0.1:5000 by default." ], "score": 27 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/text-generation-webui.json" }, "facts": [ { "a": "HTTP API", "b": "Model platform", "name": "Kind" }, { "a": "Apple Inc.", "b": "oobabooga", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "MIT", "b": "AGPL-3.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-01", "b": "2026-05-20", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "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": "7.3k stars, 140k PyPI/wk", "b": "48k stars", "name": "Popularity" } ], "faq": [ { "answer": "MLX LM scores 52.2 (D) on agent readiness against TextGen's 45.1 (E), and leads in 4 of 7 scored categories. TextGen leads on schema \u0026 documentation and security \u0026 auth.", "question": "Which is better for AI agents, MLX LM or TextGen?" }, { "answer": "No hosted endpoint is listed for MLX LM. No hosted endpoint is listed for TextGen.", "question": "Can an agent call MLX LM and TextGen without installing anything?" }, { "answer": "Yes. MLX LM is open source (MIT). TextGen is open source (AGPL-3.0).", "question": "Are MLX LM and TextGen open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 66 against 51", "Maintenance \u0026 community, 61 against 24", "Transparency \u0026 trust, 66 against 49" ], "also": [ "No key needed to call it", "No incidents deducted, where TextGen loses 4 points for them" ], "goodFor": "An owner with an Apple silicon Mac who wants MLX-format models, local fine-tuning and quantisation from Python or the command line, with a simple local chat completions server.", "slug": "mlx-lm", "watchFor": "`mlx_lm.server` has no API key or other credential option, and `--allowed-origins` defaults to `*`" }, { "aheadOn": [ "Schema \u0026 documentation, 61 against 37", "Security \u0026 auth, 40 against 32" ], "also": null, "goodFor": "A person who wants one app for several backends (llama.cpp, ExLlamaV3, Transformers) with an OpenAI and Anthropic-compatible endpoint, LoRA training and image generation.", "slug": "text-generation-webui", "watchFor": "No release since v4.9 on 20 May 2026 and no code commit on `main` or `dev` since 31 May 2026" } ], "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm.json", "title": "AnythingLLM vs MLX LM", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-text-generation-webui.json", "title": "AnythingLLM vs TextGen", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm.json", "title": "Docker Model Runner vs MLX LM", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-text-generation-webui.json", "title": "Docker Model Runner vs TextGen", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm.json", "title": "Foundry Local vs MLX LM", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-text-generation-webui.json", "title": "Foundry Local vs TextGen", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-text-generation-webui" }, { "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-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/gpt4all-vs-mlx-lm.json", "title": "GPT4All vs MLX LM", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-text-generation-webui.json", "title": "GPT4All vs TextGen", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-mlx-lm.json", "title": "Jan vs MLX LM", "url": "https://www.anchorterminal.com/compare/jan-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-text-generation-webui.json", "title": "Jan vs TextGen", "url": "https://www.anchorterminal.com/compare/jan-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-mlx-lm.json", "title": "Khoj vs MLX LM", "url": "https://www.anchorterminal.com/compare/khoj-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-text-generation-webui.json", "title": "Khoj vs TextGen", "url": "https://www.anchorterminal.com/compare/khoj-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.json", "title": "KoboldCpp vs MLX LM", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-text-generation-webui.json", "title": "KoboldCpp vs TextGen", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-text-generation-webui" }, { "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-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-mlx-lm.json", "title": "llama.cpp vs MLX LM", "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/llama-cpp-vs-text-generation-webui.json", "title": "llama.cpp vs TextGen", "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-text-generation-webui" }, { "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-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/localai-vs-mlx-lm.json", "title": "LocalAI vs MLX LM", "url": "https://www.anchorterminal.com/compare/localai-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/localai-vs-text-generation-webui.json", "title": "LocalAI vs TextGen", "url": "https://www.anchorterminal.com/compare/localai-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-ollama.json", "title": "MLX LM vs Ollama", "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-open-webui.json", "title": "MLX LM vs Open WebUI", "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-screenpipe.json", "title": "MLX LM vs screenpipe", "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-text-generation-webui.json", "title": "Ollama vs TextGen", "url": "https://www.anchorterminal.com/compare/ollama-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/open-webui-vs-text-generation-webui.json", "title": "Open WebUI vs TextGen", "url": "https://www.anchorterminal.com/compare/open-webui-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/screenpipe-vs-text-generation-webui.json", "title": "screenpipe vs TextGen", "url": "https://www.anchorterminal.com/compare/screenpipe-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-underdog.json", "title": "MLX LM vs Underdog", "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-underdog" }, { "json": "https://www.anchorterminal.com/compare/text-generation-webui-vs-underdog.json", "title": "TextGen vs Underdog", "url": "https://www.anchorterminal.com/compare/text-generation-webui-vs-underdog" } ], "scores": [ { "by": 15, "edge": "mlx-lm", "key": "reliability", "mlx-lm": 66, "name": "Reliability", "text-generation-webui": 51, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 24, "edge": "text-generation-webui", "key": "schema", "mlx-lm": 37, "name": "Schema \u0026 documentation", "text-generation-webui": 61, "weight": 13 }, { "by": 4, "edge": "mlx-lm", "key": "ergonomics", "mlx-lm": 54, "name": "Agent ergonomics", "text-generation-webui": 50, "weight": 13 }, { "by": 8, "edge": "text-generation-webui", "key": "security", "mlx-lm": 32, "name": "Security \u0026 auth", "text-generation-webui": 40, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "mlx-lm": 60, "name": "Payments \u0026 pricing", "text-generation-webui": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 37, "edge": "mlx-lm", "key": "maintenance", "mlx-lm": 61, "name": "Maintenance \u0026 community", "text-generation-webui": 24, "weight": 7 }, { "by": 17, "edge": "mlx-lm", "key": "transparency", "mlx-lm": 66, "name": "Transparency \u0026 trust", "text-generation-webui": 49, "weight": 7 } ], "summary": "MLX LM scores 52.2 (D) on agent readiness against TextGen's 45.1 (E), and leads in 4 of 7 scored categories. TextGen leads on schema \u0026 documentation and security \u0026 auth. Both do local inference.", "verdicts": { "mlx-lm": "MIT, with no telemetry found in the source, and the tests passed on the last eight pushes to main. `mlx_lm.server` has no API key option, answers any origin by default and loads whichever model a request names, and its own docs say it is not recommended for production.", "text-generation-webui": "AGPL-3.0 with no telemetry, and a local API on 127.0.0.1:5000 that checks the Host header, limits CORS to localhost and separates an admin key from the caller's key. No release since v4.9 on 20 May 2026, no code commits since 31 May, no test suite, and ten security advisories in the year, all fixed." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui", "json": "https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.md", "slim": "https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.min.md" }, "markdown": "MLX LM scores 52.2 (D) on agent readiness against TextGen's 45.1 (E), and leads in 4 of 7 scored categories. TextGen leads on schema \u0026 documentation and security \u0026 auth. Both do local inference.\n\n- MLX LM: grade D, 52.2/100, rank #657 of 842. Markdown https://www.anchorterminal.com/tools/mlx-lm.md · JSON https://www.anchorterminal.com/api/v1/tools/mlx-lm.json\n- TextGen: grade E, 45.1/100, rank #775 of 842. Markdown https://www.anchorterminal.com/tools/text-generation-webui.md · JSON https://www.anchorterminal.com/api/v1/tools/text-generation-webui.json\n\n## Which one, for what\n\n### MLX LM (D)\n\nGood for: An owner with an Apple silicon Mac who wants MLX-format models, local fine-tuning and quantisation from Python or the command line, with a simple local chat completions server.\n\nAhead on:\n- Reliability, 66 against 51\n- Maintenance \u0026 community, 61 against 24\n- Transparency \u0026 trust, 66 against 49\n\nAlso in its favour:\n- No key needed to call it\n- No incidents deducted, where TextGen loses 4 points for them\n\nWatch for: `mlx_lm.server` has no API key or other credential option, and `--allowed-origins` defaults to `*`\n\n### TextGen (E)\n\nGood for: A person who wants one app for several backends (llama.cpp, ExLlamaV3, Transformers) with an OpenAI and Anthropic-compatible endpoint, LoRA training and image generation.\n\nAhead on:\n- Schema \u0026 documentation, 61 against 37\n- Security \u0026 auth, 40 against 32\n\nWatch for: No release since v4.9 on 20 May 2026 and no code commit on `main` or `dev` since 31 May 2026\n\n\n## Score by category\n\n| Category | Weight | MLX LM | TextGen | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 66 | 51 | MLX LM +15 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 37 | 61 | TextGen +24 |\n| Agent ergonomics | 13% (16.2 this run) | 54 | 50 | MLX LM +4 |\n| Security \u0026 auth | 14% (17.5 this run) | 32 | 40 | TextGen +8 |\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) | 61 | 24 | MLX LM +37 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 66 | 49 | MLX LM +17 |\n| Negative events | ≤15 | 0 | -4 | |\n| **Total** | | **52.2 · D** | **45.1 · E** | |\n\n## Facts side by side\n\n| Fact | MLX LM | TextGen |\n| --- | --- | --- |\n| Kind | HTTP API | Model platform |\n| Vendor | Apple Inc. | oobabooga |\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 | AGPL-3.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-01 | 2026-05-20 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\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 | 7.3k stars, 140k PyPI/wk | 48k stars |\n\n## Verdicts\n\n**MLX LM.** MIT, with no telemetry found in the source, and the tests passed on the last eight pushes to main. `mlx_lm.server` has no API key option, answers any origin by default and loads whichever model a request names, and its own docs say it is not recommended for production.\n\n**TextGen.** AGPL-3.0 with no telemetry, and a local API on 127.0.0.1:5000 that checks the Host header, limits CORS to localhost and separates an admin key from the caller's key. No release since v4.9 on 20 May 2026, no code commits since 31 May, no test suite, and ten security advisories in the year, all fixed.\n\n## Before you call either\n\n### MLX LM\n\n1. Keep `mlx_lm.server` on 127.0.0.1 and pass `--allowed-origins` with the origins you trust. There is no API key, and the default answers every origin\n2. Treat any caller as able to load any model. The `model` and `adapters` request fields accept any Hugging Face repository or local path\n3. Send `max_tokens` or `max_completion_tokens` when you need more than 512 tokens, the server default\n4. Read errors as `{\"error\": \"\u003ctext\u003e\"}` with 400 for a bad field and 404 for a model that failed to load. They are not OpenAI error objects\n5. Poll `GET /health` before the first request. It answers 503 with `unavailable` when the generation thread has stopped\n\n### TextGen\n\n1. Ask the owner to launch with `--api`. Nothing listens on port 5000 without it, and a model must be loaded first\n2. Call `http://127.0.0.1:5000/v1`. Any Host header other than localhost or 127.0.0.1 gets 400 `Invalid host header` unless `--listen` is set\n3. Send the key as `Authorization: Bearer` on OpenAI routes and as `x-api-key` on `/v1/messages`. Model loading needs the admin key\n4. Read `http://127.0.0.1:5000/docs` or `modules/api/typing.py` for parameters. `max_tokens` defaults to 512 on chat completions\n5. Run tool calls yourself. The API returns `finish_reason: \"tool_calls\"` and executes nothing on the server\n6. Use the repository name `oobabooga/textgen`. The old `text-generation-webui` URL redirects\n\n## Questions\n\n### Which is better for AI agents, MLX LM or TextGen?\n\nMLX LM scores 52.2 (D) on agent readiness against TextGen's 45.1 (E), and leads in 4 of 7 scored categories. TextGen leads on schema \u0026 documentation and security \u0026 auth.\n\n### Can an agent call MLX LM and TextGen without installing anything?\n\nNo hosted endpoint is listed for MLX LM. No hosted endpoint is listed for TextGen.\n\n### Are MLX LM and TextGen open source?\n\nYes. MLX LM is open source (MIT). TextGen is open source (AGPL-3.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"mlx-lm\", \"b\": \"text-generation-webui\"}`. From a terminal: `anchor compare mlx-lm text-generation-webui`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mlx-lm.json and https://www.anchorterminal.com/api/v1/tools/text-generation-webui.json\n\n## Other comparisons with MLX LM or TextGen\n\n- [AnythingLLM vs MLX LM](https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm.md)\n- [AnythingLLM vs TextGen](https://www.anchorterminal.com/compare/anythingllm-vs-text-generation-webui.md)\n- [Docker Model Runner vs MLX LM](https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm.md)\n- [Docker Model Runner vs TextGen](https://www.anchorterminal.com/compare/docker-model-runner-vs-text-generation-webui.md)\n- [Foundry Local vs MLX LM](https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm.md)\n- [Foundry Local vs TextGen](https://www.anchorterminal.com/compare/foundry-local-vs-text-generation-webui.md)\n- [Core vs MLX LM](https://www.anchorterminal.com/compare/ghost-core-vs-mlx-lm.md)\n- [Core vs TextGen](https://www.anchorterminal.com/compare/ghost-core-vs-text-generation-webui.md)\n- [GPT4All vs MLX LM](https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm.md)\n- [GPT4All vs TextGen](https://www.anchorterminal.com/compare/gpt4all-vs-text-generation-webui.md)\n- [Jan vs MLX LM](https://www.anchorterminal.com/compare/jan-vs-mlx-lm.md)\n- [Jan vs TextGen](https://www.anchorterminal.com/compare/jan-vs-text-generation-webui.md)\n- [Khoj vs MLX LM](https://www.anchorterminal.com/compare/khoj-vs-mlx-lm.md)\n- [Khoj vs TextGen](https://www.anchorterminal.com/compare/khoj-vs-text-generation-webui.md)\n- [KoboldCpp vs MLX LM](https://www.anchorterminal.com/compare/koboldcpp-vs-mlx-lm.md)\n- [KoboldCpp vs TextGen](https://www.anchorterminal.com/compare/koboldcpp-vs-text-generation-webui.md)\n- [Lemonade vs MLX LM](https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.md)\n- [Lemonade vs TextGen](https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui.md)\n- [llama.cpp vs MLX LM](https://www.anchorterminal.com/compare/llama-cpp-vs-mlx-lm.md)\n- [llama.cpp vs TextGen](https://www.anchorterminal.com/compare/llama-cpp-vs-text-generation-webui.md)\n- [LM Studio vs MLX LM](https://www.anchorterminal.com/compare/lm-studio-vs-mlx-lm.md)\n- [LM Studio vs TextGen](https://www.anchorterminal.com/compare/lm-studio-vs-text-generation-webui.md)\n- [LocalAI vs MLX LM](https://www.anchorterminal.com/compare/localai-vs-mlx-lm.md)\n- [LocalAI vs TextGen](https://www.anchorterminal.com/compare/localai-vs-text-generation-webui.md)\n- [MLX LM vs Ollama](https://www.anchorterminal.com/compare/mlx-lm-vs-ollama.md)\n- [MLX LM vs Open WebUI](https://www.anchorterminal.com/compare/mlx-lm-vs-open-webui.md)\n- [MLX LM vs screenpipe](https://www.anchorterminal.com/compare/mlx-lm-vs-screenpipe.md)\n- [Ollama vs TextGen](https://www.anchorterminal.com/compare/ollama-vs-text-generation-webui.md)\n- [Open WebUI vs TextGen](https://www.anchorterminal.com/compare/open-webui-vs-text-generation-webui.md)\n- [screenpipe vs TextGen](https://www.anchorterminal.com/compare/screenpipe-vs-text-generation-webui.md)\n- [MLX LM vs Underdog](https://www.anchorterminal.com/compare/mlx-lm-vs-underdog.md)\n- [TextGen vs Underdog](https://www.anchorterminal.com/compare/text-generation-webui-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": "MLX LM vs TextGen", "url": "" } ], "description": "MLX LM scores 52.2 (D) on agent readiness against TextGen's 45.1 (E), and leads in 4 of 7 scored categories. TextGen leads on schema \u0026 documentation and security \u0026 auth. Both do local inference. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "MLX LM D 52.2", "TextGen E 45.1", "scores" ], "h1": "MLX LM vs TextGen", "image": "https://www.anchorterminal.com/assets/og/compare-mlx-lm-vs-text-generation-webui.png", "path": "/compare/mlx-lm-vs-text-generation-webui", "published": "2026-10-01", "section": "tools", "title": "MLX LM vs TextGen for AI agents, D 52.2 vs E 45.1 | Anchor Terminal", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui" }, "tokens": { "markdown": 2500, "slim": 530 }, "version": 1 }