# PrivateGPT vs TextGen

> PrivateGPT scores 53.2 (D) to TextGen's 38.7 (E) for local inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/privategpt-vs-text-generation-webui
- Markdown: https://www.anchorterminal.com/compare/privategpt-vs-text-generation-webui.md (~5,700 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

PrivateGPT scores 53.2 (D) on agent readiness against TextGen's 38.7 (E), and leads in 5 of 7 scored categories. TextGen leads on security & auth. Both do local inference.

- PrivateGPT: grade D, 53.2/100, rank #960 of 1510. Markdown https://www.anchorterminal.com/tools/privategpt.md · JSON https://www.anchorterminal.com/api/v1/tools/privategpt.json
- TextGen: grade E, 38.7/100, rank #1354 of 1510. Markdown https://www.anchorterminal.com/tools/text-generation-webui.md · JSON https://www.anchorterminal.com/api/v1/tools/text-generation-webui.json
- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md
- All 280 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md

## Which one, for what

### PrivateGPT (D)

Good for: A local backend for apps and agents that want an Anthropic-style API with document retrieval, citations and tools over local models.

Ahead on:
- Reliability, 70 against 51
- Schema & documentation, 83 against 61
- Agent ergonomics, 64 against 50
- Maintenance & community, 41 against 24
- Transparency & trust, 64 against 55

Also in its favour:
- No key needed to call it

Watch for: Authentication is off by default, the server binds 0.0.0.0 and CORS allows every origin

### TextGen (E)

Good 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.

Ahead on:
- Security & auth, 40 against 32

Also in its favour:
- Free to start without a card

Watch for: No release since v4.9 on 20 May 2026 and no code commit on `main` or `dev` since 31 May 2026


## Why the edge

### Schema & documentation: PrivateGPT +22

- PrivateGPT (83): An OpenAPI file of 38 paths in the repository (fern/openapi/openapi.json, version 1.0.1), also served by each instance at /openapi.json, with the messages API modelled on Anthropic's (25). docs.privategpt.dev serves llms.txt, a Markdown copy of every page and a docs MCP server (10). The docs explain each endpoint group, startup and model discovery, and a compatibility table says which parts of the Claude API are supported, partial or missing, such as prompt caching and OAuth (15 of 20). Pydantic models with literal type discriminators and required fields, while settings and tool context are wide objects (12 of 15). curl examples for each guide and a `/v1/messages/validate` route, with error shapes not documented as a list (9 of 15). `/v1` paths and a dated changelog, though releases trail main by more than four months (12 of 15). 25 + 10 + 15 + 12 + 9 + 12 = 83.
- TextGen (61): Read with the API lines. The server is a FastAPI app with default settings, so a running instance serves `/docs` and `/openapi.json` generated from 33 Pydantic classes in `modules/api/typing.py`, and the docs point callers there. No OpenAPI file is published, and we read the source without running the server (17 of 25). No llms.txt. The docs are Markdown files in the repository's docs folder, mirrored to the wiki (4 of 10). The API page is mostly examples with a compatibility table, and 36 fields in `typing.py` carry descriptions (10 of 20). Typed request models with defaults and a few range limits, while `tools` is a list of free-form objects (10 of 15). curl, Python and Node examples for chat, completions, streaming, tool calling, vision, images and model loading, with no error responses documented (9 of 15). A `/v1` prefix and release notes per version, with no changelog file (11 of 15). 17 + 4 + 10 + 10 + 9 + 11 = 61.

### Reliability: PrivateGPT +19

- PrivateGPT (70): Read with the local-software lines, since PrivateGPT runs on the owner's hardware with no hosted service behind it. Homebrew tap, `uv tool install` from Zylon's own wheel index (not PyPI) and Docker Hub images `zylonai/private-gpt` 1.0.1 of 18 June 2026. Python 3.11 only, stated in pyproject.toml, and it needs a separate OpenAI-compatible model server (17 of 20). tests.yml runs format, lint, typecheck and the tests affected by each push on main, with the full suite of 217 test files on release pull requests. We couldn't see run results because the GitHub API refused us, and issue #2441 of 1 November reports the Claude spec update workflow failing (15 of 25). GitHub shows 3 open issues of about 1,250, because a stale bot closes quiet issues, two security reports among them, with no maintainer reply (12 of 25). release-please keeps a changelog with breaking changes marked, but no release has been cut since 1.0.1 while main carries 51 commits since 8 August, among them a breaking observability change of 23 October (11 of 15). Version 1.0.1 (15). 17 + 15 + 12 + 11 + 15 = 70.
- TextGen (51): Read with the local-software lines, since TextGen runs on the owner's machine with no hosted service. Portable builds for Linux, Windows and macOS on GitHub releases, a one-click installer, a venv route for Python 3.9 or later, a Conda route on Python 3.13 and Docker files, but no package on a registry (18 of 20). No test suite in the repository, and the seven workflows (re-read in a clone on 5 November) only build release packages on manual dispatch (3 of 25). Per the 8 October check, not re-read on 5 November, there were 807 open issues and 40 open pull requests, and the newest open issues then (July to October 2026) carried between none and two comments. No code commit on `main` or `dev` since 31 May 2026 (6 of 25). Versioned tags and GitHub release notes per version that list security fixes and behaviour changes, with no changelog file and no stated semver policy (9 of 15). v4.9 (15). 18 + 3 + 6 + 9 + 15 = 51.

### Maintenance & community: PrivateGPT +17

- PrivateGPT (41): The last release is 1.0.1, dated 16 June 2026 in the changelog and tagged 18 June, 141 days before the check (10 of 30). No release or dated changelog entry in the 90 days since 8 August (0 of 20). Maintainers commit most days and outside pull requests merged in October, but 23 pull requests are open and the stale bot closes issues, including two security reports, with no maintainer reply (13 of 25). Homebrew tap, wheel index and Docker images ship with releases, and Anthropic SDKs work against it. No product MCP server of its own, though it connects to remote MCP servers (10 of 15). Dependabot, uv.lock, actions pinned by commit since 19 October and dependency CVE upgrades in June, July and August (8 of 10). 10 + 0 + 13 + 10 + 8 = 41.
- TextGen (24): v4.9 on 20 May 2026, 169 days before this check (10). No release in the 90 days from 7 August (0). No code commit on `main` since 31 May 2026 (one README edit on 17 August) and none on `dev` since 16 May, read in a clone on 5 November. Per the 8 October check, 807 open issues and 40 open pull requests, and the newest open issues showed few or no comments. Comment authors didn't render for our reader, so maintainer replies are unconfirmed (5 of 25). No SDK and no MCP registry entry. Portable builds shipped with each release up to May (5 of 15). A weekly Dependabot config with its update branches still unmerged, no test CI, and the bundled llama.cpp last updated on 31 May (4 of 10). 10 + 0 + 5 + 5 + 4 = 24.

### Agent ergonomics: PrivateGPT +14

- PrivateGPT (64): Read for an HTTP API an agent calls on a local instance. Token counting, `top_k` style retrieval settings, citation output and response byte caps let a caller size context (18 of 25). Artifact listing by namespace and retrieval filters, with no documented cursor pagination (12 of 20). FastAPI validation errors name the field and the validate route checks a request before running it, but there is no error catalogue (12 of 20). Async messages and ingestion return task ids with status, cancel and delete routes. No idempotency keys were found (10 of 20). Anthropic SDKs and Claude Code work by pointing `ANTHROPIC_BASE_URL` at the server, but a model server and an embedding server have to be configured first (12 of 15). 18 + 12 + 12 + 10 + 12 = 64.
- TextGen (50): Read with the API lines. `max_tokens` (512 by default on chat completions), `max_tokens_second`, a token-count route and a `max_tokens` argument on the built-in page fetcher size the output (17 of 25). `/v1/models` lists everything with the loaded model first, with no paging or filters (6 of 20). Errors are JSON in OpenAI's shape (`message`, `type`, `param`) or Anthropic's on `/v1/messages`, with 401, 400 and 422 used, but none are documented (11 of 20). Completions are stateless and safe to repeat, a client disconnect stops generation and `/v1/internal/stop-generation` exists. No retry guidance (7 of 20). A request needs only `messages`, with no model name, but the owner has to launch with `--api` and load a model. No SDK of its own, with OpenAI's Python and Node clients shown in the docs (9 of 15). 17 + 6 + 11 + 7 + 9 = 50.

### Transparency & trust: PrivateGPT +9

- PrivateGPT (64): Apache-2.0 (30). The OpenAPI description says no data leaves the execution environment, but the docs list cloud gateways as model providers and web search goes to outside services when enabled, and no privacy statement covers the software. Zylon's privacy policy covers its website (15 of 30). The 1.0 rewrite was marked as a breaking change in the changelog, and there is no deprecation policy (6 of 20). No telemetry to Zylon found in the source. OpenTelemetry tracing is off by default and its exporters write local files or to the owner's collector, documented on the observability page (16 of 20). 30 + 15 + 6 + 16 = 67.
- TextGen (55): AGPL-3.0 for the whole repository (30). No privacy policy or terms exist, and there's no hosted service. The README states that the app is fully offline with zero telemetry, external resources or remote update requests, the API page says it creates no logs, and the source turns Gradio analytics off. A Check for updates button calls api.github.com when clicked, which the README's wording doesn't mention (18 of 30). No deprecation policy. Release notes record behaviour changes, and the rename to TextGen left a redirect from the old repository URL (4 of 20). No telemetry to opt out of, and analytics are disabled in `server.py` (18 of 20). 30 + 18 + 4 + 18 = 70.

### Security & auth: TextGen +8

- PrivateGPT (32): Read with the tool checklist. Authentication is off by default, and when on it is one static secret compared with the whole `Authorization` header, with a sample `secret:key` value in settings.yaml. There are no per-user keys or scopes, `private-gpt serve` binds 0.0.0.0 by default and CORS allows every origin, so a default start answers anyone on the network. The docs disagree on the header (Bearer, Basic or an Anthropic key) (6 of 30). Tools are chosen per request and code execution has internet off by default, but bash runs as a host subprocess with resource limits, not in a container, and nothing asks for approval (6 of 20). Web fetch, web search, documents and MCP servers bring untrusted text to the model. A public prompt-injection report (#2270) was closed by the stale bot, and no guidance was found beyond a 19 October change that bounds tool output (3 of 15). OpenTelemetry traces cover every request, model call, tool and sandbox step, off by default, with local JSON lines exporters (10 of 15). SECURITY.md since 23 July 2026 asks for private reports through GitHub or Discord. No bounty, no certification, and the June and July security reports in issues were closed by a bot with no reply (7 of 20). 6 + 6 + 3 + 10 + 7 = 32.
- TextGen (40): Read with the tool checklist. One optional key from `--api-key`, off by default, sent as a Bearer token or `x-api-key` and never in a query string, with a separate `--admin-key` for loading and unloading models and LoRAs. No scopes or per-client keys, and a key changes only with a restart (14 of 30). Without `--listen` or `--public-api` the API binds 127.0.0.1, rejects other Host headers and limits CORS to localhost (since v4.9). The chat has a Confirm tool calls setting, off by default, and the web UI has no login unless `--gradio-auth` is set (10 of 20). The built-in page fetcher refuses non-global addresses on every redirect hop. No guidance on injected instructions in web or tool results was found (5 of 15). The docs say the API creates no logs and the server runs with access logs off. `--verbose` prints prompts to the terminal (3 of 15). No SECURITY.md, security.txt or bounty. Ten advisories are published on GitHub with patched versions, per the 8 October reading of the Security tab, and seven of them have CVE records in the CVE list, and still no SECURITY.md in a clone on 5 November (8 of 20). 14 + 10 + 5 + 3 + 8 = 40. Advisories are charged one by one under negative events.

## Score by category

| Category | Weight | PrivateGPT | TextGen | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 70 | 51 | PrivateGPT +19 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 83 | 61 | PrivateGPT +22 |
| Agent ergonomics | 13% (16.2 this run) | 64 | 50 | PrivateGPT +14 |
| Security & auth | 14% (17.5 this run) | 32 | 40 | TextGen +8 |
| Payments & pricing | 10% (12.5 this run) | 60 | 60 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 41 | 24 | PrivateGPT +17 |
| Transparency & trust | 7% (8.8 this run) | 64 | 55 | PrivateGPT +9 |
| Negative events | ≤15 | -7 | -11 | |
| **Total** | | **53.2 · D** | **38.7 · E** | |

## Facts side by side

| Fact | PrivateGPT | TextGen |
| --- | --- | --- |
| Kind | HTTP API | Platform |
| Vendor | Zylon (PriBAI Technology Spain S.L.) | oobabooga |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | None | API key |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | AGPL-3.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-06-18 | 2026-05-20 |
| Terms last updated | no date given | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models | not found in the text | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Popularity | 58k stars | 48k stars |
| Agent reviews | none | 2.5/5 (4) |

## How the scores have moved

### PrivateGPT

No score change since it was listed.

### TextGen

- -7.0 on 5 November 2026: correction
- +0.2 on 28 October 2026: new evidence
- +0.4 on 27 October 2026: checklist

## Verdicts

**PrivateGPT.** PrivateGPT 1.0 is an Apache-2.0 server that gives local models an Anthropic-style messages API with retrieval, citations, tools and MCP, documented by an OpenAPI file and llms.txt. A default start has authentication off, listens on every interface and reads local paths given as URIs, and a public report of that was closed without a reply.

**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 twelve security records since October 2025, all fixed.

## Before you call either

### PrivateGPT

1. Turn on `server.auth` and bind to 127.0.0.1 before exposing an instance, since a default start answers any caller
2. Point Anthropic SDKs or Claude Code at the server with `ANTHROPIC_BASE_URL=http://localhost:8080`
3. Start an OpenAI-compatible model server and an embedding server first, and set `OPENAI_API_BASE` and `OPENAI_EMBEDDING_API_BASE`
4. Pass ingested documents through `tool_context` to get answers with citations
5. Treat web fetch, search and MCP results as untrusted, since PrivateGPT documents no prompt-injection handling

### TextGen

1. Ask the owner to launch with `--api`. Nothing listens on port 5000 without it, and a model must be loaded first
2. 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
3. Send the key as `Authorization: Bearer` on OpenAI routes and as `x-api-key` on `/v1/messages`. Model loading needs the admin key
4. Read `http://127.0.0.1:5000/docs` or `modules/api/typing.py` for parameters. `max_tokens` defaults to 512 on chat completions
5. Run tool calls yourself. The API returns `finish_reason: "tool_calls"` and executes nothing on the server
6. Use the repository name `oobabooga/textgen`. The old `text-generation-webui` URL redirects

## Questions

### Which is better for AI agents, PrivateGPT or TextGen?

PrivateGPT scores 53.2 (D) on agent readiness against TextGen's 38.7 (E), and leads in 5 of 7 scored categories. TextGen leads on security & auth.

### Can an agent call PrivateGPT and TextGen without installing anything?

No hosted endpoint is listed for PrivateGPT. No hosted endpoint is listed for TextGen.

### Are PrivateGPT and TextGen open source?

Yes. PrivateGPT is open source (Apache-2.0). TextGen is open source (AGPL-3.0).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/privategpt-vs-text-generation-webui.json, and with the fewest tokens: https://www.anchorterminal.com/compare/privategpt-vs-text-generation-webui.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "privategpt", "b": "text-generation-webui"}`. From a terminal: `anchor compare privategpt text-generation-webui`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/privategpt.json and https://www.anchorterminal.com/api/v1/tools/text-generation-webui.json

## Other comparisons with PrivateGPT or TextGen

- [AnythingLLM vs PrivateGPT](https://www.anchorterminal.com/compare/anythingllm-vs-privategpt.md)
- [AnythingLLM vs TextGen](https://www.anchorterminal.com/compare/anythingllm-vs-text-generation-webui.md)
- [Berth vs PrivateGPT](https://www.anchorterminal.com/compare/berth-vs-privategpt.md)
- [Berth vs TextGen](https://www.anchorterminal.com/compare/berth-vs-text-generation-webui.md)
- [BitRun vs PrivateGPT](https://www.anchorterminal.com/compare/bitrun-vs-privategpt.md)
- [BitRun vs TextGen](https://www.anchorterminal.com/compare/bitrun-vs-text-generation-webui.md)
- [Docker Model Runner vs PrivateGPT](https://www.anchorterminal.com/compare/docker-model-runner-vs-privategpt.md)
- [Docker Model Runner vs TextGen](https://www.anchorterminal.com/compare/docker-model-runner-vs-text-generation-webui.md)
- [Foundry Local vs PrivateGPT](https://www.anchorterminal.com/compare/foundry-local-vs-privategpt.md)
- [Foundry Local vs TextGen](https://www.anchorterminal.com/compare/foundry-local-vs-text-generation-webui.md)
- [Core vs PrivateGPT](https://www.anchorterminal.com/compare/ghost-core-vs-privategpt.md)
- [Core vs TextGen](https://www.anchorterminal.com/compare/ghost-core-vs-text-generation-webui.md)
- [GPT4All vs PrivateGPT](https://www.anchorterminal.com/compare/gpt4all-vs-privategpt.md)
- [GPT4All vs TextGen](https://www.anchorterminal.com/compare/gpt4all-vs-text-generation-webui.md)
- [HyperQwen vs PrivateGPT](https://www.anchorterminal.com/compare/hyperqwen-vs-privategpt.md)
- [HyperQwen vs TextGen](https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui.md)
- [Jan vs PrivateGPT](https://www.anchorterminal.com/compare/jan-vs-privategpt.md)
- [Jan vs TextGen](https://www.anchorterminal.com/compare/jan-vs-text-generation-webui.md)
- [Khoj vs TextGen](https://www.anchorterminal.com/compare/khoj-vs-text-generation-webui.md)
- [KoboldCpp vs PrivateGPT](https://www.anchorterminal.com/compare/koboldcpp-vs-privategpt.md)
- [KoboldCpp vs TextGen](https://www.anchorterminal.com/compare/koboldcpp-vs-text-generation-webui.md)
- [Lemonade vs PrivateGPT](https://www.anchorterminal.com/compare/lemonade-vs-privategpt.md)
- [Lemonade vs TextGen](https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui.md)
- [llama.cpp vs PrivateGPT](https://www.anchorterminal.com/compare/llama-cpp-vs-privategpt.md)
- [llama.cpp vs TextGen](https://www.anchorterminal.com/compare/llama-cpp-vs-text-generation-webui.md)
- [LM Studio vs PrivateGPT](https://www.anchorterminal.com/compare/lm-studio-vs-privategpt.md)
- [LM Studio vs TextGen](https://www.anchorterminal.com/compare/lm-studio-vs-text-generation-webui.md)
- [LocalAI vs PrivateGPT](https://www.anchorterminal.com/compare/localai-vs-privategpt.md)
- [LocalAI vs TextGen](https://www.anchorterminal.com/compare/localai-vs-text-generation-webui.md)
- [MLX LM vs PrivateGPT](https://www.anchorterminal.com/compare/mlx-lm-vs-privategpt.md)
- [MLX LM vs TextGen](https://www.anchorterminal.com/compare/mlx-lm-vs-text-generation-webui.md)
- [Ollama vs PrivateGPT](https://www.anchorterminal.com/compare/ollama-vs-privategpt.md)
- [Ollama vs TextGen](https://www.anchorterminal.com/compare/ollama-vs-text-generation-webui.md)
- [Open WebUI vs PrivateGPT](https://www.anchorterminal.com/compare/open-webui-vs-privategpt.md)
- [Open WebUI vs TextGen](https://www.anchorterminal.com/compare/open-webui-vs-text-generation-webui.md)
- [PrivateGPT vs screenpipe](https://www.anchorterminal.com/compare/privategpt-vs-screenpipe.md)
- [PrivateGPT vs vLLM](https://www.anchorterminal.com/compare/privategpt-vs-vllm.md)
- [screenpipe vs TextGen](https://www.anchorterminal.com/compare/screenpipe-vs-text-generation-webui.md)
- [TextGen vs vLLM](https://www.anchorterminal.com/compare/text-generation-webui-vs-vllm.md)
- [Khoj vs PrivateGPT](https://www.anchorterminal.com/compare/khoj-vs-privategpt.md)
- [LocalGhost vs PrivateGPT](https://www.anchorterminal.com/compare/localghost-vs-privategpt.md)
- [TextGen vs Underdog](https://www.anchorterminal.com/compare/text-generation-webui-vs-underdog.md)

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