クレジットカード不要で使える無料LLM APIプロバイダまとめ（2026年版）

📝 Originally published (in Japanese) at forge.workstyle.tech.

Introduction

As the use of Large Language Models (LLMs) continues to grow, developers often face the need to “minimize API costs” and “easily experiment with multiple models” during development and prototyping. However, many commercial API services typically require credit card registration, which can be a barrier.

In this article, we’ve compiled a list of LLM API providers that offer free tiers without requiring credit card registration. We also share practical insights on how to combine these providers to build robust systems.

Note: Free tiers and available models frequently change, so always verify the latest information on each provider’s official website before implementation.

Major Providers with Free Tiers (No Credit Card Required)

Below is a summary of providers with relatively accessible free tiers:

Provider Access Method Free Tier Estimate Key Features Google Gemini AI Studio Model-specific RPM/daily limits High-quality models available. Caution: Prompts may be used for training. Groq Console RPM/RPD limits by model Ultra-fast inference powered by LPU technology. Cerebras Cloud 1M tokens/day Large daily token capacity. OpenRouter Website :free models: 20 RPM / 50–1000 RPD Single API key for switching between multiple models. NVIDIA NIM Build Free credits/tier Runs numerous open models at high speed. GitHub Models Marketplace Depends on Copilot plan Access GPT-like models with just a GitHub account. Cohere Dashboard Trial tier (~20 RPM) Models suitable for trial purposes. SambaNova Cloud Permanent free tier + initial credits High-speed inference performance. Mistral Console Experiment tier (large capacity) Allows extensive token usage (with authentication conditions).

Critical Design Guidelines for Production Use

While free-tier APIs are powerful, integrating them into commercial applications requires specific considerations.

1. Implement Fallback Strategies

The biggest challenge with free-tier APIs is service disruption due to rate limits or daily quotas. To mitigate this, manage multiple providers as a single “pool” and implement fallback mechanisms to automatically route requests to another provider when one reaches its limit.

For example, use multi-provider routers like LiteLLM to group models, ensuring application availability even if a specific provider fails.

2. Agent Use Cases: Inference Model Compatibility

When building AI agents, pay attention to model output formats. Models that output reasoning_content (thought processes) are emerging, but inconsistencies in this format across models can break context in multi-turn conversations. For agent use cases with free tiers, choose models with consistent behavior.

3. Security and Privacy

Many free-tier services include terms allowing input data to be used for model training. Never include confidential or personal information in prompts. For sensitive tasks, always use paid plans or enterprise models that do not use data for training.

Conclusion

Free-tier API providers are powerful tools for prototyping and small-scale automation tasks. Instead of using them in isolation, combine multiple providers to optimize for “availability” and “speed”—a key mindset for engineers in production environments.

• Prototyping & One-Off Generation: Free tiers are sufficient.
• Interactive Agents & High-Frequency Communication: Consider paid subscriptions for capacity, speed, and privacy.
• Design Focus: Implement fallbacks and carefully handle data usage (training considerations).