Best Free LLM APIs for Developers: Build AI Apps, Chatbots & More (2025 Guide)

Building an AI-powered application doesn't have to start with a credit card. There are several excellent free LLM APIs available right now that can help developers validate ideas, prototype features, and launch projects without upfront costs.

I've been testing the free OpenRouter LLM API over the past few weeks, which provides unified access to multiple top-tier AI models. Here are the ones that stand out for different use cases. Each has its strengths, and I'll share what I've learned from actually using them.

Top Free LLM APIs for General Purpose Development

These models excel at a wide range of tasks and are great starting points for most AI applications.

DeepSeek: DeepSeek V3 0324 - The Flagship Generalist

This is the latest iteration of DeepSeek's flagship chat model family. As a 685B-parameter Mixture-of-Experts (MoE) model, it represents their current state-of-the-art for general-purpose tasks.

While many models specialize, DeepSeek V3 aims for strong, broad performance across a variety of domains. If you're starting a new project and aren't sure about the specific type of intelligence you'll need, this is a safe and powerful bet. It's a good baseline for testing as it performs well on many different benchmarks.

TNG: DeepSeek R1T Chimera - Balanced Reasoning and Efficiency

This model is a "chimera," created by merging two different models to get the best of both worlds: the strong reasoning from DeepSeek-R1 and the token efficiency of DeepSeek-V3.

In practice, this translates to a model that's good at thinking through problems without being sluggish. It's a solid generalist. If your application requires a mix of content generation and logical reasoning, but you can't afford the latency of a pure reasoning-focused model, this is an excellent compromise. It's a great choice for building features that need to be both smart and reasonably fast.

Best Free LLM APIs for Conversational AI & Chat Applications

These models are particularly well-suited for building conversational AI applications that require natural dialogue, context awareness, and responsive interactions.

Z.AI: GLM 4.5 Air - Flexible Inference for Chatbots

What caught my attention about GLM 4.5 Air is its hybrid inference approach. You can switch between a "thinking mode" for complex reasoning and a "non-thinking mode" for faster, real-time interactions.

This flexibility is genuinely useful. For a chatbot, you could use the thinking mode for the initial, context-heavy user query, then switch to the faster non-thinking mode for subsequent conversational turns. With a 131K context window, it's well-suited for building sophisticated conversational agents that need to balance depth with responsiveness. The ability to control this behavior via a simple boolean flag (reasoning_enabled) makes it very developer-friendly.

Best Free LLM APIs for Coding and Agentic Tasks

These models excel at code generation, debugging, and complex engineering workflows, making them ideal for development tools and automation.

Kwaipilot: KAT-Coder-Pro V1 - A Specialist for Agentic Coding

This is a new and interesting model specifically designed for agentic coding. It's not just another general-purpose model; it's been fine-tuned for real-world software engineering tasks. Its high solve rate (73.4%) on the SWE-Bench benchmark is a strong signal of its capabilities.

For developers, this means it's optimized for tool-use, multi-turn interactions, and following complex instructions—all critical for building reliable coding agents. If you're working on a project that involves code generation, automated debugging, or any multi-step engineering workflow, KAT-Coder-Pro V1 should be at the top of your list to try. The 256K context window is also a huge plus for repository-level understanding.

DeepSeek: R1 0528 - For Transparent, Open-Source Reasoning

The key feature of DeepSeek R1 is its commitment to open-source reasoning. The model, which aims for performance on par with OpenAI's o1, provides fully open reasoning tokens.

This is a big deal for developers who want to understand how a model arrives at an answer, not just what the answer is. It's invaluable for debugging complex prompts or building applications where explainability is important. While it's a massive 671B parameter model, it only activates 37B during an inference pass, keeping it manageable. If you value transparency and control, this is the model for you.

Qwen: Qwen3 Coder 480B A35B - A Powerhouse for Code Generation

The Qwen3 Coder is another specialist, but it's a beast. It's a 480B-parameter MoE model (35B active) optimized for agentic coding tasks like function calling, tool use, and long-context reasoning over entire code repositories.

Its 262K context window is massive and genuinely useful for tasks that require understanding a large codebase. I've found it particularly effective for complex refactoring or when generating code that depends on many other files. A practical tip: the provider notes that pricing can change for requests over 128k tokens, so it's something to keep in mind for very large inputs, even on the free tier.

OpenAI: gpt-oss-20b - Lightweight and Deployable

It's not every day that OpenAI releases an open-weight model. This 21B parameter MoE model is designed for efficiency, with only 3.6B active parameters per pass.

The most significant advantage here is its deployability. It's optimized for lower-latency inference and can run on consumer-grade or single-GPU hardware. This makes it a fantastic option for indie developers or small teams who want to self-host or run a model on-premise without breaking the bank on infrastructure. It supports agentic features like function calling and tool use, making it a versatile choice.

Choosing the Right Free LLM API for Your Project

With these excellent free options, the choice depends entirely on your project's needs. Here’s a quick guide to help you decide:

For Agentic Coding: Start with Kwaipilot: KAT-Coder-Pro V1 for its specialized skills or Qwen3 Coder for large codebase analysis.
For Transparent Reasoning: DeepSeek: R1 0528 is the clear winner if you need to see the model's thought process.
For conversational AI and chatbots: Z.AI: GLM 4.5 Air offers a great balance of speed and intelligence with its dual modes.
For Self-Hosting/Efficiency: OpenAI: gpt-oss-20b is designed for deployment on accessible hardware.
For a Strong Generalist: TNG: DeepSeek R1T Chimera provides a good balance of reasoning and speed, while DeepSeek V3 is a powerful, safe bet for any new project.

When Free Isn't Enough

These free APIs are invaluable for getting started and validating ideas. But we all know that successful projects grow, and at some point, you might face a decision: Should you invest in a paid LLM API that offers better performance and reliability? How much would that change your pricing?

At that point, the question shifts from "how do I build this?" to "can this be profitable?" Different API pricing varies dramatically, and when you add in server costs, database expenses, and other infrastructure, the math gets complicated quickly.

This is the challenge every AI SaaS founder faces:

💸 Unclear costs: How much will monthly LLM API calls actually cost?
🤔 Pricing confusion: $19/month or $29/month? Subscription or credit-based? How do you ensure profitability?
📊 Financial planning difficulty: How many users do you need to break even?

Before making that decision, I'd suggest spending a few minutes doing a quick "sandbox" analysis of your business model. We built a free tool called Muon specifically for this—it helps you:

⚡ Quickly estimate costs: Input LLM API prices and usage, get accurate cost predictions immediately
💰 Develop pricing strategies: Compare subscription, credit-based, and fixed revenue models to find the best fit
📈 Predict profitability: Visualize cost, revenue, and profit curves at different user scales

It's lightweight, completely free, stores all data locally, and requires no registration. It supports JSON import/export, making it easy to share your assumptions and discuss pricing strategies with your team. I hope it helps: Muon Website