Chat apps

Add Pareto to your chat app as a custom OpenAI-compatible provider. The app uses your Pareto endpoint and key. Each successful test sent a chat message in the app and received a streamed answer. Results apply to the tested versions and settings, not every app feature.

App	Version tested	Result
Open WebUI	0.11.4	Streamed chat, model list, and titles passed on September 23, 2026.
NextChat	2.16.1	Streamed chat and titles passed with the server settings below on September 23, 2026.
AnythingLLM	1.16.2	Streamed chat and model list passed with Max Tokens raised on September 23, 2026.
Cherry Studio	2.1.2	Streamed chat, model sync, and titles passed on September 23, 2026.
LibreChat	0.8.7	Streamed chat, model list, and titles passed with `dropParams` on September 23, 2026.
Chatbox	1.23.4	Streamed chat, model fetch, and titles passed on September 23, 2026.
SillyTavern	1.19.0	Streamed chat and model list passed with Max Response Length raised on September 23, 2026.

Setting names can differ in other app versions.

Connection values

Setting	Value
API format	OpenAI Chat Completions
Base URL	`https://api.paretoinference.com/v1`
API key	Your Pareto API key
Model ID	`z-ai/glm-5.3-flash`

Get your key from the Pareto dashboard. Get prepaid credits before you continue. Most apps show the model reasoning in a separate block above the answer. The model reasoning counts toward the response token limit. If an app sets a low limit, the reasoning can use all of it and the answer is empty. Some apps also send requests for titles, tags, or suggestions. These requests use Pareto credits and count toward your concurrent request limit.

Open WebUI

Use the Open WebUI guide to install Open WebUI.

Add Pareto

Open Admin Panel → Settings → Connections.
In OpenAI API, select + to add a connection.
Enter these values.

Field	Value
URL	`https://api.paretoinference.com/v1`
Key	Your Pareto key
API Type	`Chat Completions`
Model IDs	Keep empty, or add `z-ai/glm-5.3-flash`

Save the connection.
Select z-ai/glm-5.3-flash in the model menu of a new chat.

Do not set API Type to Responses. Pareto serves Chat Completions only.

Docker

You can also add Pareto when you start Open WebUI for the first time.

docker run -d -p 3000:8080 \
  -e OPENAI_API_BASE_URLS="https://api.paretoinference.com/v1" \
  -e OPENAI_API_KEYS="$PARETO_API_KEY" \
  -e ENABLE_OLLAMA_API=False \
  -v open-webui:/app/backend/data --name open-webui \
  ghcr.io/open-webui/open-webui:v0.11.4

Open WebUI reads these variables only on the first start. After that, change the connection in the Admin Panel. Open WebUI sends title, tag, and follow-up requests after the first message. To send fewer requests, turn off tag and follow-up generation in Admin Panel → Settings → Interface.

NextChat

Use the NextChat guide to deploy NextChat. Pareto works when the NextChat server holds your key.

Add Pareto

Start NextChat with these environment variables.

docker run -d -p 3000:3000 \
  -e OPENAI_API_KEY="$PARETO_API_KEY" \
  -e BASE_URL="https://api.paretoinference.com" \
  -e CUSTOM_MODELS="-all,+z-ai/glm-5.3-flash@OpenAI" \
  -e DEFAULT_MODEL="z-ai/glm-5.3-flash@OpenAI" \
  yidadaa/chatgpt-next-web:v2.16.1

BASE_URL has no /v1. NextChat adds the API path. NextChat does not read the Pareto model list, so CUSTOM_MODELS adds the model. Do not use the Custom Endpoint setting in the NextChat browser settings. In that mode, the browser calls Pareto directly, and the request fails. Anyone who can open your NextChat page uses your Pareto key. Protect the page before other people can open it. See the NextChat guide. NextChat shows the model reasoning in the answer text. NextChat also sends title and history summary requests. To send fewer requests, turn off Auto Generate Title in the NextChat settings.

AnythingLLM

Use the AnythingLLM guide to install AnythingLLM.

Add Pareto

Start AnythingLLM with the Generic OpenAI provider.

docker run -d -p 3001:3001 --cap-add SYS_ADMIN \
  -v anythingllm_storage:/app/server/storage \
  -e STORAGE_DIR=/app/server/storage \
  -e LLM_PROVIDER=generic-openai \
  -e GENERIC_OPEN_AI_BASE_PATH=https://api.paretoinference.com/v1 \
  -e GENERIC_OPEN_AI_API_KEY="$PARETO_API_KEY" \
  -e GENERIC_OPEN_AI_MODEL_PREF=z-ai/glm-5.3-flash \
  -e GENERIC_OPEN_AI_MAX_TOKENS=8192 \
  mintplexlabs/anythingllm:1.16.2

Keep GENERIC_OPEN_AI_MAX_TOKENS at 8192 or more. The default is 1024. With the default, a long answer can use all tokens for reasoning, and no answer shows. Keep the default AnythingLLM embedder. Pareto does not serve embeddings.

Cherry Studio

Use the Cherry Studio downloads to install Cherry Studio.

Add Pareto

Open Settings → Model Provider.
Select Add Provider.
Enter these values.

Field	Value
Provider Name	`Pareto Inference`
API Key	Your Pareto key
OpenAI endpoint URL	`https://api.paretoinference.com`

Keep the OpenAI Responses and Anthropic endpoint fields empty.
Turn on the provider.
Select Sync models, then add z-ai/glm-5.3-flash.
Open Settings → Default Model.
Set Default Assistant Model and Quick Model to the Pareto model.
Select the Pareto model in the model menu of a chat.

Cherry Studio adds /v1 to the endpoint URL. https://api.paretoinference.com/v1 also works. Do not end the URL with #.

Set the Quick Model to the Pareto model. Cherry Studio uses the Quick Model for chat titles. With the default Quick Model, Cherry Studio sends your conversation text to its own service to make titles.

LibreChat

Use the LibreChat guide to install LibreChat.

Add Pareto

Add PARETO_API_KEY to the LibreChat .env file. Set it to your Pareto key.
Add this endpoint to librechat.yaml.

endpoints:
  custom:
    - name: "Pareto"
      apiKey: ${PARETO_API_KEY}
      baseURL: "https://api.paretoinference.com/v1"
      models:
        default: ["z-ai/glm-5.3-flash"]
        fetch: true
      titleConvo: true
      titleModel: "current_model"
      modelDisplayLabel: "Pareto"
      dropParams: ["user"]

For Docker, mount librechat.yaml in docker-compose.override.yml.

services:
  api:
    volumes:
      - type: bind
        source: ./librechat.yaml
        target: /app/librechat.yaml

Restart LibreChat.
In the model menu, select Pareto → z-ai/glm-5.3-flash.

Keep dropParams: ["user"]. LibreChat sends a user field by default. Pareto rejects this field with HTTP 400.

Chatbox

Use the Chatbox downloads to install Chatbox.

Add Pareto

Open Settings → Model Provider.
Select Add → Add Custom Provider.
Enter the name Pareto Inference.
Set API Mode to OpenAI API Compatible.
Select Add.
Enter these values on the provider page.

Field	Value
API Key	Your Pareto key
API Host	`https://api.paretoinference.com/v1`
API Path	Keep empty

Make sure the preview shows https://api.paretoinference.com/v1/chat/completions.
In Model, select Fetch and add z-ai/glm-5.3-flash.
Select z-ai/glm-5.3-flash in the model menu below the chat box.

Do not use OpenAI Responses API Compatible. Pareto serves Chat Completions only.

SillyTavern

Use the SillyTavern guide to install SillyTavern.

Add Pareto

Open API Connections.
Enter these values.

Field	Value
API	`Chat Completion`
Chat Completion Source	`Custom (OpenAI-compatible)`
Custom Endpoint (Base URL)	`https://api.paretoinference.com/v1`
Custom API Key	Your Pareto key
Model ID	`z-ai/glm-5.3-flash`

Select Connect. Make sure the status shows Valid.
Open AI Response Configuration.
Set Max Response Length (tokens) to 2048 or more.
Keep Context Size (tokens) larger than Max Response Length.
Keep Multiple swipes per generation at 1.

The base URL includes /v1. With the default Max Response Length of 300, the reasoning can use all tokens, and the answer is empty. If Multiple swipes per generation is more than 1, Pareto rejects the request with HTTP 400. Do not use a Logit Bias preset. Pareto rejects logit_bias with HTTP 400.

Check the connection

Send a short message in a new chat. The answer uses Pareto credits. Pareto returns HTTP 429 when the account has no credits for the request, or when too many requests arrive at the same time. Pareto returns HTTP 503 when it is at capacity or temporarily unavailable, and HTTP 502 when a model request fails. See Troubleshooting for Pareto errors.

Get started

Integrations

Reference

Connection values

Open WebUI

Add Pareto

Docker

NextChat

Add Pareto

AnythingLLM

Add Pareto

Cherry Studio

Add Pareto

LibreChat

Add Pareto

Chatbox

Add Pareto

SillyTavern

Add Pareto

Check the connection

​Connection values

​Open WebUI

​Add Pareto

​Docker

​NextChat

​Add Pareto

​AnythingLLM

​Add Pareto

​Cherry Studio

​Add Pareto

​LibreChat

​Add Pareto

​Chatbox

​Add Pareto

​SillyTavern

​Add Pareto

​Check the connection

Connection values

Open WebUI

Add Pareto

Docker

NextChat

Add Pareto

AnythingLLM

Add Pareto

Cherry Studio

Add Pareto

LibreChat

Add Pareto

Chatbox

Add Pareto

SillyTavern

Add Pareto

Check the connection