particle-1
Particle-1 is a token-efficient agentic coding model from Particle AI, post-trained on DeepSeek V4.1 Flash and suited for software engineering work such as terminal workflows and codebase changes.
Pricing: Input 12 credits / 1M tokens (≈ $0.06), Output 120 credits / 1M tokens (≈ $0.60).
Prices updated
How can I help you today?
This demo page does not include the full memory features of the client. For the complete experience, please use the client or the CLI.
Latest and popular AI models
Particle-1 API on ModelFold
Particle-1 is a token-efficient agentic coding model from Particle AI, post-trained on DeepSeek V4.1 Flash and suited for software engineering work such as terminal workflows and codebase changes. Try Particle-1 in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Particle-1 API
Particle-1 at a glance
Particle-1 is a chat model from Particle AI. It accepts text and images as input and returns text, with a context window of up to 1M tokens.
Use it without hosting anything
On ModelFold you call Particle-1 with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Particle-1
Up to 1M tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Understands images
Besides text, Particle-1 accepts images as input, so a single request can combine instructions with visual or other media.
Function calling
Particle-1 supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.
Adjustable reasoning effort
Choose a reasoning effort level (low, medium or high) per request to balance depth of thinking against speed and token usage.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Particle-1 on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Particle-1 responds before writing any code.
- 2
Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "particle-1" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Particle-1
AI coding assistants
Generate, explain, debug and refactor code, review pull requests and work through multi-file changes in developer tools and IDE plugins.
Autonomous agents
Build agents that plan multi-step tasks, call your tools and APIs, and keep working toward a goal across long sessions.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Tool-calling backends
Route requests, call functions and chain API calls as the worker model inside larger agent systems.
Frequently Asked Questions
What is Particle-1?⌄
Particle-1 is a token-efficient agentic coding model from Particle AI, post-trained on DeepSeek V4.1 Flash and suited for software engineering work such as terminal workflows and codebase changes.
Which inputs does Particle-1 support?⌄
Particle-1 accepts text and images and returns text. Through ModelFold you can send text and images (OpenAI-style image_url content); in the Playground you can also attach documents, which are converted to text.
How long is the context window of Particle-1?⌄
Up to 1M tokens, shared between your input and the model’s output.
Does Particle-1 support function calling?⌄
Yes. Particle-1 supports tools / function calling through the standard tools parameter of the chat completions API.
How is Particle-1 billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Particle-1 through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "particle-1", using your ModelFold API key as the Bearer token.
| Input | 12 credits 1M tokens≈ $0.06 |
| Output | 120 credits 1M tokens≈ $0.60 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"particle-1","messages":[{"role":"user","content":"Hello"}]}'

