{ "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": "llama-cpp", "name": "llama.cpp", "vendor": "ggml.ai (Hugging Face)", "vendorUrl": "https://llama.app", "kind": "http-api", "category": "local-ai", "summary": "Open-source C/C++ engine for running GGUF models locally, with a web interface and compatible model APIs.", "url": "https://www.anchorterminal.com/tools/llama-cpp", "markdownUrl": "https://www.anchorterminal.com/tools/llama-cpp.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/llama-cpp.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/llama-cpp.json", "repo": "https://github.com/ggml-org/llama.cpp", "license": "MIT", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "ghcr.io/ggml-org/llama.cpp" }, { "registry": "pypi", "name": "gguf" } ], "auth": "none", "authNotes": "No credential by default. `--api-key` (one key or a comma-separated list) or `--api-key-file` (one key a line) turns on a check for every route but /health and the web UI's files, with the key sent as `Authorization: Bearer` or `X-Api-Key`, never in the query string. Keys have no scopes and change only with a restart. TLS is built in with `--ssl-key-file` and `--ssl-cert-file`. The server binds 127.0.0.1:8080 by default, and CORS reflects any Origin with credentials allowed unless built-in tools, MCP servers or `--agent` are on, when it narrows to localhost (https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md).", "pricing": "free", "pricingNotes": "Free under MIT, with no account, key or card. Nothing is sold. You pay for your own hardware and electricity.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-03).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 130200, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-03" }, "docsUrl": "https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md", "capabilities": [ "inference.local", "inference.open-weights", "embed.text", "rerank", "inference.decision", "agent.mcp-client" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "openai-compatible", "docker", "pre-1.0", "no-telemetry" ], "lastRelease": "2026-09-23", "graded": true, "anchor": { "graded": true, "score": 60.2, "grade": "C", "agentReady": false, "rank": 253, "ranked": true, "rankOf": 452, "categoryRank": 3, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 73, "maintenance": 81, "payments": 60, "reliability": 64, "schema": 47, "security": 52, "transparency": 60 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-03" }, "negative": -1, "negativeNotes": [ "2026-03-26. GHSA-j8rj-fmpv-wcxw (CVE-2026-34159, 9.8 at NVD), unauthenticated code execution through a GRAPH_COMPUTE bypass in the RPC backend, the most serious of four advisories published between January and March 2026 (the others a llama-server out-of-bounds write through a negative `n_discard` and two GGUF integer overflows). All were fixed in named builds and published as advisories, SECURITY.md says not to expose the RPC server or llama-server to untrusted networks, and the newest is more than six months old, -1. https://github.com/ggml-org/llama.cpp/security/advisories/GHSA-j8rj-fmpv-wcxw; https://github.com/ggml-org/llama.cpp/security" ], "verdict": "MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads. API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost.", "strengths": [ "MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads", "OpenAI chat completions, responses and embeddings, Anthropic messages, reranking and /v1/systemone from one server", "`response_fields`, `json_schema` and `grammar` control the size and shape of output, and errors carry an OpenAI-style type and code", "1,005 nightly builds and eight semver releases in 90 days, with 37 workflows running on every push to master", "Ten published GitHub advisories with CVEs and fixed builds, and SECURITY.md guidance on untrusted models and inputs" ], "weaknesses": [ "API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost", "No OpenAPI file of its own, and the REST API changelog stops at b4599", "Private security disclosure disabled since 1 June 2026, with fixes asked for as public pull requests", "Pre-1.0 (0.5.0), and semver releases are bare tags with no notes", "No official client library, and `n_predict` defaults to unlimited" ], "agentNotes": [ "Start the server with `--api-key` and `--cors-origins localhost` before anything else can reach the port. Both are off by default", "Pass `n_predict` or `max_tokens`. Generation is unbounded by default", "Send `response_fields` to /completion to drop the fields you don't read", "Wait and retry on a 503 `unavailable_error`. The model is still loading", "Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry" ], "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": 60.2 } ], "editorialScores": { "ergonomics": 73, "maintenance": 81, "payments": 60, "reliability": 64, "schema": 47, "security": 52, "transparency": 66 }, "provenanceScore": 53 }, "connect": { "install": "curl -LsSf https://llama.app/install.sh | sh # or: brew install llama.cpp; winget install llama.cpp\nllama serve -hf ggml-org/Qwen3.5-0.8B-GGUF # listens on 127.0.0.1:8080", "http": "curl --request POST \\\n --url http://localhost:8080/completion \\\n --header \"Content-Type: application/json\" \\\n --data '{\"prompt\": \"Building a website can be done in 10 simple steps:\",\"n_predict\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/llama-cpp" }, "area": "models", "provenance": { "legalEntity": "ggml.ai, part of Hugging Face since 2026", "domain": "llama.app", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/ggml-org/llama.cpp/releases", "securityTxt": "none", "checked": "2026-10-03", "notes": [ "The repository's About link is llama.app, which says it's by the llama.cpp team and Hugging Face and links no terms, privacy or security page. ggml.ai says the company was acquired by Hugging Face in 2026 and names no address.", "The `LICENSE` file reads Copyright (c) 2023-2026 The ggml authors.", "llama.app/.well-known/security.txt and llama.app/llms.txt return 404. SECURITY.md points to GitHub private advisories while saying private disclosure is disabled.", "There's no shared hosted endpoint. The server runs on the owner's machine." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/llama-cpp.json", "live": { "slug": "llama-cpp", "versions": [ { "registry": "github", "name": "ggml-org/llama.cpp", "version": "v0.5.0", "released": "2026-09-23", "seenAt": "2026-10-04T16:31:53.040249174Z" }, { "registry": "pypi", "name": "gguf", "version": "0.19.0", "released": "2026-05-06", "seenAt": "2026-10-04T16:31:52.933067593Z" } ], "githubStars": 130286, "securityTxt": { "url": "https://llama.app/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-04T15:16:00.86400098Z" }, "domain": { "domain": "llama.app", "registered": "2018-07-18", "source": "https://pubapi.registry.google/rdap/domain/llama.app", "checkedAt": "2026-10-04T13:04:03.05886804Z" }, "updatedAt": "2026-10-04T16:31:53.040249174Z" } }, "summary": "llama.cpp has a score of 60.2 (C) against GPT4All's 36.3 (F). Both do local inference. The largest gap is maintenance \u0026 community, 75 points." }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp", "json": "https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.md", "slim": "https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.min.md" }, "markdown": "llama.cpp has a score of 60.2 (C) against GPT4All's 36.3 (F). Both do local inference. The largest gap is maintenance \u0026 community, 75 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- llama.cpp: grade C, 60.2/100, rank #253 of 452. Markdown https://www.anchorterminal.com/tools/llama-cpp.md · JSON https://www.anchorterminal.com/api/v1/tools/llama-cpp.json\n\n## Which one, for what\n\nPick GPT4All for nothing in particular (no category where it leads by five points or more).\n\nPick llama.cpp for reliability (+8), schema \u0026 documentation (+7), agent ergonomics (+32), security \u0026 auth (+24), maintenance \u0026 community (+75).\n\n## Score by category\n\n| Category | Weight | GPT4All | llama.cpp | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 56 | 64 | llama.cpp +8 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 40 | 47 | llama.cpp +7 |\n| Agent ergonomics | 13% (16.2 this run) | 41 | 73 | llama.cpp +32 |\n| Security \u0026 auth | 14% (17.5 this run) | 28 | 52 | llama.cpp +24 |\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 | 81 | llama.cpp +75 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 57 | 60 | llama.cpp +3 |\n| Negative events | ≤15 | -6 | -1 | |\n| **Total** | | **36.3 · F** | **60.2 · C** | |\n\n## Facts side by side\n\n| Fact | GPT4All | llama.cpp |\n| --- | --- | --- |\n| Kind | Model platform | HTTP API |\n| Vendor | Nomic, Inc. | ggml.ai (Hugging Face) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | MIT (app, backend and bindings). Models downloaded through the app carry their own licences | 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 | no |\n| MCP registry | not listed | not listed |\n| Last release | 2025-02-24 | 2026-09-23 |\n| Popularity | 77k stars, 11k PyPI/wk | 130k stars |\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**llama.cpp.** MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads. API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost.\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### llama.cpp\n\n1. Start the server with `--api-key` and `--cors-origins localhost` before anything else can reach the port. Both are off by default\n2. Pass `n_predict` or `max_tokens`. Generation is unbounded by default\n3. Send `response_fields` to /completion to drop the fields you don't read\n4. Wait and retry on a 503 `unavailable_error`. The model is still loading\n5. Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry\n\n## Other comparisons with GPT4All or llama.cpp\n\n- [AnythingLLM vs GPT4All](https://www.anchorterminal.com/compare/anythingllm-vs-gpt4all.md)\n- [AnythingLLM vs llama.cpp](https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.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 LM Studio](https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.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 llama.cpp](https://www.anchorterminal.com/compare/jan-vs-llama-cpp.md)\n- [Khoj vs llama.cpp](https://www.anchorterminal.com/compare/khoj-vs-llama-cpp.md)\n- [llama.cpp vs LM Studio](https://www.anchorterminal.com/compare/llama-cpp-vs-lm-studio.md)\n- [llama.cpp vs LocalAI](https://www.anchorterminal.com/compare/llama-cpp-vs-localai.md)\n- [llama.cpp vs Ollama](https://www.anchorterminal.com/compare/llama-cpp-vs-ollama.md)\n- [llama.cpp vs Open WebUI](https://www.anchorterminal.com/compare/llama-cpp-vs-open-webui.md)\n- [llama.cpp vs screenpipe](https://www.anchorterminal.com/compare/llama-cpp-vs-screenpipe.md)\n- [GPT4All vs Underdog](https://www.anchorterminal.com/compare/gpt4all-vs-underdog.md)\n- [llama.cpp vs Underdog](https://www.anchorterminal.com/compare/llama-cpp-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 llama.cpp", "url": "" } ], "description": "llama.cpp has a score of 60.2 (C) against GPT4All's 36.3 (F). Both do local inference. The largest gap is maintenance \u0026 community, 75 points. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "GPT4All F 36.3", "llama.cpp C 60.2", "scores" ], "h1": "GPT4All vs llama.cpp", "image": "https://www.anchorterminal.com/assets/og/compare-gpt4all-vs-llama-cpp.png", "path": "/compare/gpt4all-vs-llama-cpp", "published": "2026-10-01", "section": "tools", "title": "GPT4All vs llama.cpp for AI agents, F 36.3 vs C 60.2 | Anchor Terminal", "toc": null, "updated": "2026-10-05", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp" }, "tokens": { "markdown": 1600, "slim": 330 }, "version": 1 }