Text Generation
Generate human-quality text, code, and creative content at scale. WaveSpeed unifies leading open-source Large Language Models (LLMs) into a single, high-performance API. From simple chatbots to complex reasoning engines, deploy text generation with zero infrastructure overhead.
Comprehensive Text Generation Capabilities
WaveSpeed supports a diverse range of text generation tasks, optimized for speed and context handling.
Chat & Conversation
Build responsive chatbots and virtual assistants that understand context and nuance. Recommended models include Llama 3.1 Instruct, Qwen-Chat, and DeepSeek-V3 for natural, multi-turn dialogue.
Code Generation
Generate, debug, and explain code in languages like Python, JavaScript, and Ruby. Specialized models such as DeepSeek-Coder and CodeLlama are optimized for syntax accuracy, refactoring, and inline documentation.
Reasoning & Analysis
Process complex documents, summarize long articles, or perform structured reasoning tasks with large context windows. Use models like Qwen-Long and Llama 3.1 70B to handle extended inputs and multi-step analysis.
How to Use AI Text Generation
See how developers and businesses automate workflows using our text generation API.
📝Content & Marketing
| Use Case | What You Generate | How |
|---|---|---|
| SEO Blog Writing | Full-length articles optimized for specific keywords, structured with headings and bullet points. | Text Generation (Llama 3.1 70B) + Prompt Engineering |
| Social Media Captions | Engaging hooks and descriptions for Instagram, LinkedIn, or Twitter posts tailored to your brand voice. | Text Generation (Mistral, Gemma) |
| Ad Copy Variations | Hundreds of headlines and body copy options for A/B testing marketing campaigns. | Batch API + Structured JSON Output |
💻Development & Data
| Use Case | What You Generate | How |
|---|---|---|
| Code Assistant | Boilerplate code, unit tests, or documentation comments generated directly in your IDE. | Code Generation (DeepSeek-Coder) |
| Data Extraction | Structured JSON data extracted from unstructured emails, PDFs, or customer support tickets. | Text Generation + JSON Mode |
| Translation | Accurate translation of documentation or user interfaces between multiple languages. | Text Generation (Qwen, Polyglot Models) |
💬Customer Support
| Use Case | What You Generate | How |
|---|---|---|
| Automated Replies | Instant, empathetic responses to common customer inquiries based on your knowledge base. | RAG (Retrieval-Augmented Generation) |
| Ticket Summarization | Concise summaries of long chat logs for human agents to review quickly. | Text Generation (Summarization Task) |
Frequently Asked Questions
What is AI Text Generation?
AI Text Generation involves using Large Language Models (LLMs) to predict and generate text based on an input prompt. It can be used for writing, coding, translation, and data analysis.
Which LLMs are available on WaveSpeed?
We host a curated selection of the best open-source models, including the Llama 3 series (8B, 70B), DeepSeek-V3, Qwen 2.5, and Mistral. We continuously update our catalog as new high-performance models are released.
What is the context window limit?
Context windows vary by model. Standard models typically support 8k to 32k tokens, while specialized models like Qwen-Long can handle up to 128k or more tokens, allowing for the processing of entire books or large codebases in a single prompt.
Can I use these models for coding?
Yes. We offer models specifically trained on code repositories (like DeepSeek-Coder) that excel at writing, debugging, and explaining code in various programming languages.
Is the API compatible with OpenAI's SDK?
Yes. WaveSpeed provides an OpenAI-compatible API endpoint. This means you can easily switch your existing applications to WaveSpeed by simply changing the base URL and API key, with minimal code changes.
How is text generation priced?
Pricing is based on token usage (input tokens + output tokens). Different models have different rates per million tokens. You only pay for what you use.
Is my data used to train the models?
No. We prioritize data privacy. Data sent through our API is not used to train or improve our public models.