AI Chat Models

OpenCompany supports 12 providers (11 dedicated model nodes, plus xAI through the OpenAI-compatible path), with models fetched dynamically from each provider’s API (and, for the local nodes, from your running server). The backend uses a hybrid architecture: a native SDK layer in server/services/llm/ for direct chat completions, and a LangChain + LangGraph path for agent tool-calling.

Available Chat-Model Nodes

Node	Models	Best For
OpenAI	GPT-5.5/5.4/5.2, GPT-4.1/4.1-mini/nano, o3, o4-mini, GPT-4o/4o-mini	General purpose, reasoning
Anthropic	Claude Fable 5, Opus 4.8/4.7, Sonnet 4.6, Haiku 4.5	Coding, analysis, extended thinking
Google Gemini	Gemini 3.5-flash, 3.1-pro/flash-lite, 3-flash, 2.5-pro/flash/flash-lite	Multimodal, long context (1M)
OpenRouter	200+ models	Access multiple providers via single API
xAI	Grok models	Direct chat via the OpenAI-compatible xAI API
Groq	Llama 3.3-70b, Llama 3.1-8b, GPT-OSS-120b/20b, Qwen3-32b	Ultra-fast inference (LPU)
Cerebras	GPT-OSS-120b, Qwen-3-235b, GLM-4.7	Ultra-fast on wafer-scale hardware
DeepSeek	deepseek-v4-flash, deepseek-v4-pro	V4 with reasoning modes, up to 1M context
Kimi	kimi-k2.6, kimi-k2.5, kimi-k2.7-code	256K context, thinking on by default
Mistral	mistral-large/medium/small-latest, codestral-latest	Up to 256K context
Ollama	Whatever you’ve pulled locally	Local models, no API key
LM Studio	Whatever you’ve loaded locally	Local models, no API key

xAI (Grok) is native-chat-only: it runs through the shared OpenAI-compatible provider with base_url=https://api.x.ai/v1 and is not wired as an agent provider. Ollama and LM Studio connect to a local server running on your machine.

Adding API Keys

Click the key icon in the toolbar
Select the provider
Enter your API key
Click Validate to test

API keys are encrypted and stored locally. They’re never sent to OpenCompany servers.

OpenAI Chat Model

Models

Model	Best For
gpt-5.5	Most capable, up to ~1M context
gpt-5.4	High capability, long context
gpt-5.2	Capable, 400K context
gpt-4.1 / 4.1-mini / 4.1-nano	Fast, 1M context
o3	Advanced reasoning
o4-mini	Fast, efficient reasoning
gpt-4o / gpt-4o-mini	Multimodal, cost-effective

Parameters

select

required

The model to use

string

required

The message to send. Supports template variables.

slider

default:"0.7"

Randomness (0 = deterministic, 1 = creative)

number

default:"1000"

Maximum response length

select

default:"text"

Output format: text or json_object

select

default:"medium"

For o-series and GPT-5 hybrid reasoning: low, medium, high (GPT-5 also supports xhigh)

Output

{
  "response": "The AI's response text",
  "model": "gpt-5.5",
  "thinking": "Reasoning process (o-series / GPT-5 only)",
  "usage": {
    "prompt_tokens": 50,
    "completion_tokens": 100,
    "total_tokens": 150
  }
}

Anthropic Claude Model

Models

Model	Best For
claude-opus-4-8	Most capable, detailed analysis, 1M context
claude-opus-4-7	High capability, 1M context
claude-sonnet-4-6	Best for coding and complex tasks, 1M context
claude-fable-5	Capable, 1M context
claude-haiku-4-5	Fast responses, simple tasks, 200K context

Parameters

select

required

Claude model to use

string

required

The message to send

string

System instructions for the model

slider

default:"0.7"

Randomness (0-1)

number

default:"1000"

Maximum response length

boolean

default:"false"

Enable extended thinking mode (all Claude 4.x models)

number

default:"2048"

Token budget for thinking (1024-16000). Shown when thinkingEnabled is true.

Extended Thinking

Claude’s extended thinking mode shows the model’s reasoning process:

{
  "response": "Claude's final response",
  "thinking": "Let me analyze this step by step...",
  "model": "claude-opus-4-8",
  "stop_reason": "end_turn"
}

Anthropic model IDs use hyphens, not dots (claude-sonnet-4-6, not claude-sonnet-4.6).

When thinking is enabled, max_tokens must be greater than thinkingBudget. Temperature is automatically set to 1.

Google Gemini Model

Models

Model	Best For
gemini-3.5-flash	Fast, frontier performance, 1M context
gemini-3.1-pro-preview	Most intelligent, complex tasks
gemini-3.1-flash-lite	Fast, cost-effective
gemini-3-flash-preview	Fast, multimodal
gemini-2.5-pro	Complex tasks, thinking support
gemini-2.5-flash / 2.5-flash-lite	Fast, thinking support

Parameters

select

required

Gemini model to use

string

required

The message to send

slider

default:"0.7"

Randomness (0-1)

number

default:"1000"

Maximum response length

select

default:"default"

Content safety level

boolean

default:"false"

Enable thinking mode (Gemini 3.x and 2.5 models)

Output

{
  "response": "Gemini's response",
  "thinking": "Reasoning process (when enabled)",
  "model": "gemini-3.5-flash"
}

OpenRouter Model

OpenRouter provides access to 200+ models from multiple providers through a single API.

Features

Unified API: One API key for OpenAI, Anthropic, Google, Meta, Mistral, and more
Free Models: Some models available at no cost (marked with [FREE] prefix)
Fallback: Automatic model fallback if primary is unavailable

Models

Models are grouped by cost in the dropdown:

Free models: [FREE] prefix, no cost
Paid models: Standard pricing per provider

Popular models include:

openai/gpt-5.5
anthropic/claude-sonnet-4.6 (the OpenRouter default)
google/gemini-3.5-flash
meta-llama/llama-3.3-70b-instruct
mistralai/mistral-large-latest

Parameters

select

required

Model in format: provider/model-name

string

required

The message to send

slider

default:"0.7"

Randomness (0-1)

number

default:"1000"

Maximum response length

Output

{
  "response": "Model's response",
  "model": "openai/gpt-5.5",
  "provider": "openrouter"
}

Groq Model

Groq provides ultra-fast inference on custom LPU (Language Processing Unit) hardware.

Models

Model	Best For
llama-3.3-70b-versatile	General purpose, fast
llama-3.1-8b-instant	Ultra-fast, simple tasks
openai/gpt-oss-120b	Large open model, long output
openai/gpt-oss-20b	Fast open model
qwen/qwen3-32b	Reasoning with parsed/hidden output

Parameters

select

required

Groq model to use

string

required

The message to send

slider

default:"0.7"

Randomness (0-1)

number

default:"1000"

Maximum response length

select

default:"parsed"

For Qwen3 models: “parsed” returns reasoning, “hidden” returns only final answer

Reasoning Output

Qwen3-32b supports reasoning output:

{
  "response": "The final answer",
  "thinking": "Step-by-step reasoning process",
  "model": "qwen/qwen3-32b"
}

Cerebras Model

Cerebras provides ultra-fast inference on custom wafer-scale AI hardware.

Models

Model	Best For
gpt-oss-120b	Capable, balanced (the default)
qwen-3-235b	Reasoning tasks (budget thinking)
zai-glm-4.7	General purpose

Parameters

select

required

Cerebras model to use

string

required

The message to send

slider

default:"0.7"

Randomness (0-1)

number

default:"1000"

Maximum response length

Output

{
  "response": "Cerebras model response",
  "model": "gpt-oss-120b"
}

DeepSeek

DeepSeek V4 models with reasoning support and long context.

Models

Model	Best For
deepseek-v4-flash	General purpose, fast, up to 1M context, up to 64K output
deepseek-v4-pro	Higher capability, up to 1M context, up to 64K output

The legacy deepseek-chat and deepseek-reasoner aliases still resolve (scheduled for deprecation 2026-07-24). deepseek-reasoner returns always-on reasoning in the thinking field.

Parameters

select

required

DeepSeek model

string

required

The message to send

slider

default:"0.7"

Randomness (0-2)

number

default:"8192"

Maximum response length (up to 64K)

Reasoning Output

DeepSeek’s reasoning is mapped to the standard thinking field:

{
  "response": "The final answer",
  "thinking": "Step-by-step reasoning",
  "model": "deepseek-v4-pro"
}

Kimi (Moonshot AI)

Moonshot’s Kimi models with 256K context window and thinking on by default.

Models

Model	Best For
kimi-k2.6	General purpose, 256K context, 32K output
kimi-k2.5	General purpose, 256K context, 96K output
kimi-k2.7-code	Code tasks, 256K context, 96K output

Parameters

select

required

Kimi model

string

required

The message to send

number

default:"4096"

Maximum response length (up to 96K)

Kimi models use a fixed temperature of 0.6. User-set temperature is ignored. Thinking is on by default but explicitly disabled in tool-calling agent mode for compatibility.

Output

{
  "response": "Kimi response",
  "thinking": "Reasoning (when thinking is active)",
  "model": "kimi-k2.6"
}

Mistral

Mistral AI models including Large, Small, and Codestral for code tasks.

Models

Model	Best For
mistral-large-latest	Most capable, general purpose, 256K context
mistral-medium-latest	Balanced, 256K context
mistral-small-latest	Fast, cost-effective
codestral-latest	Code generation and completion, 256K context

Parameters

select

required

Mistral model

string

required

The message to send

slider

default:"0.7"

Randomness (0-1.5)

number

default:"8192"

Maximum response length (up to 131K)

Output

{
  "response": "Mistral response",
  "model": "mistral-large-latest"
}

Mistral models support up to 256K context but do not have a thinking mode. Temperature range is 0-1.5 (not 0-2).

Ollama (Local)

Run models locally through an Ollama server. No API key is needed; instead you point OpenCompany at your running server’s URL in the Credentials Modal (default http://localhost:11434/v1).

Models

The dropdown reflects whatever you have pulled into Ollama (e.g. qwen2.5, llama3.x, phi-3, deepseek-r1). OpenCompany probes your running server via the official Ollama Python SDK and reads per-model context length directly. When the server is offline the list is empty, cueing you to start it.

Parameters

select

required

A model loaded in your local Ollama server

string

required

The message to send

slider

default:"0.7"

Randomness (0-2)

number

default:"4096"

Maximum response length (per-model, roughly context / 4, capped at 4096)

Traffic stays on your machine. OpenCompany sends requests to your local server URL, never to a cloud API.

LM Studio (Local)

Run models locally through the LM Studio server. Like Ollama, no API key is required; you set your local server URL in the Credentials Modal (default http://localhost:1234/v1).

Models

The dropdown reflects whatever you have loaded in the LM Studio UI. OpenCompany probes the running server via the official LM Studio Python SDK and reads typed model info (context length, tool-use support, vision).

Parameters

select

required

A model loaded in your LM Studio server

string

required

The message to send

slider

default:"0.7"

Randomness (0-2)

number

default:"4096"

Maximum response length (per-model, roughly context / 4, capped at 4096)

Native SDK vs LangChain Path

OpenCompany uses a hybrid architecture for LLM access:

Native SDK path (server/services/llm/): Used by execute_chat() for direct chat completions. Returns a normalized LLMResponse across providers. This path also serves the OpenAI-compatible providers including DeepSeek, Kimi, Mistral, xAI, Ollama, and LM Studio.
LangChain path: Used by execute_agent() and execute_chat_agent() for tool-calling agents via LangGraph. All chat-model providers are supported (Groq and Cerebras use this path for direct chat too).

OpenAI-compatible providers (DeepSeek, Kimi, Mistral, xAI, Ollama, LM Studio) reuse the OpenAIProvider class with base_url read from server/config/llm_defaults.json. For the local nodes (Ollama, LM Studio) the base_url resolves to your machine’s server URL, so traffic never leaves your host. Adding a new OpenAI-compatible provider is largely a config change.

Thinking/Reasoning Modes

Several providers support extended thinking or reasoning modes that show the model’s internal reasoning process.

Provider	Models	Parameter
Claude	Claude 4.x models	thinkingBudget (tokens)
Gemini	Gemini 3.x, 2.5 Pro/Flash	thinkingBudget (tokens)
OpenAI	o3, o4-mini, GPT-5.x hybrid	reasoningEffort (low/medium/high; GPT-5 also xhigh)
Groq	Qwen3-32b	reasoningFormat (parsed/hidden)
Cerebras	Qwen-3-235b	budget thinking
DeepSeek	deepseek-v4 (legacy reasoner alias)	reasoning modes
Kimi	kimi-k2.6 / k2.5 / k2.7-code	On by default (off in agent mode)

Using Thinking Output

The thinking field is available in the node output for downstream nodes:

{{openaiChatModel.thinking}}
{{anthropicChatModel.thinking}}

Comparing Providers

Feature	OpenAI	Claude	Gemini	OpenRouter	Groq	Cerebras	DeepSeek	Kimi	Mistral
Speed	Fast	Medium	Fast	Varies	Ultra-fast	Ultra-fast	Fast	Fast	Fast
Reasoning	o-series, GPT-5	Extended thinking	Thinking mode	Model-dependent	Qwen3	Qwen-3	v4 reasoning	On by default	-
Context Window	128K-1M	200K-1M	1M	Varies	131K	131K	up to 1M	256K	up to 256K
Multimodal	Yes	Yes	Yes	Model-dependent	No	No	No	No	No
JSON Mode	Yes	No	No	Model-dependent	No	No	Yes	Yes	Yes

Ollama and LM Studio are local nodes: capabilities depend entirely on the model you have pulled/loaded.

Common Use Cases

Text Generation

Prompt: Write a product description for: {{input.product_name}}
Temperature: 0.8

Data Extraction

Prompt: Extract the email and phone from: {{input.text}}
Response Format: json_object
Temperature: 0

Complex Reasoning (with thinking)

Model: claude-sonnet-4-6
Thinking Enabled: true
Thinking Budget: 4096
Prompt: Analyze this code and explain the bug: {{input.code}}

Tips

Use temperature 0 for deterministic outputs like data extraction.

Use temperature 0.7-0.9 for creative writing tasks.

Enable thinking mode for complex reasoning tasks that benefit from step-by-step analysis.

Use OpenRouter to experiment with different models without managing multiple API keys.

API calls cost money. Monitor your usage in your provider’s dashboard.

Error Handling

Error	Cause	Solution
401 Unauthorized	Invalid API key	Check/update API key
429 Rate Limited	Too many requests	Add delay, reduce frequency
500 Server Error	Provider issue	Retry later

AI Agent

Use models with memory and tools

AI Skills

Extend Chat Agent capabilities

AI Tools

Tool nodes for AI agents

AI Tutorial

Build an AI-powered workflow

​AI Chat Models

​Available Chat-Model Nodes

​Adding API Keys

​OpenAI Chat Model

​Models

​Parameters

​Output

​Anthropic Claude Model

​Models

​Parameters

​Extended Thinking

​Google Gemini Model

​Models

​Parameters

​Output

​OpenRouter Model

​Features

​Models

​Parameters

​Output

​Groq Model

​Models

​Parameters

​Reasoning Output

​Cerebras Model

​Models

​Parameters

​Output

​DeepSeek

​Models

​Parameters

​Reasoning Output

​Kimi (Moonshot AI)

​Models

​Parameters

​Output

​Mistral

​Models

​Parameters

​Output

​Ollama (Local)

​Models

​Parameters

​LM Studio (Local)

​Models

​Parameters

​Native SDK vs LangChain Path

​Thinking/Reasoning Modes

​Using Thinking Output

​Comparing Providers

​Common Use Cases

​Text Generation

​Data Extraction

​Complex Reasoning (with thinking)

​Tips

​Error Handling

​Related

AI Agent

AI Skills

AI Tools

AI Tutorial

AI Chat Models

Available Chat-Model Nodes

Adding API Keys

OpenAI Chat Model

Models

Parameters

Output

Anthropic Claude Model

Models

Parameters

Extended Thinking

Google Gemini Model

Models

Parameters

Output

OpenRouter Model

Features

Models

Parameters

Output

Groq Model

Models

Parameters

Reasoning Output

Cerebras Model

Models

Parameters

Output

DeepSeek

Models

Parameters

Reasoning Output

Kimi (Moonshot AI)

Models

Parameters

Output

Mistral

Models

Parameters

Output

Ollama (Local)

Models

Parameters

LM Studio (Local)

Models

Parameters

Native SDK vs LangChain Path

Thinking/Reasoning Modes

Using Thinking Output

Comparing Providers

Common Use Cases

Text Generation

Data Extraction

Complex Reasoning (with thinking)

Tips

Error Handling

Related