Where can you use open-weight AI for free? Five API services

With a free open-weight model API¹, you can send questions or code to a publicly released model and receive answers generated on the provider's servers. Before preparing a large GPU² or downloading model files, you can review public code or summarize a short document. This guide helps you choose a service and understand its free-access terms.

For example, OpenCode offers access to the MIT-licensed DeepSeek V4.1 Flash, while Groq hosts GPT-OSS, whose weights use Apache 2.0. Downloaded weights are governed by their model license; using an API also brings the service's usage and data policies into scope.

Start with OpenCode for a coding-tool workflow, or OpenRouter to try multiple models through one API format. Groq publishes request and token³ limits per model, NVIDIA offers developer free endpoints for new Nemotron models, and Mistral enables limited API use in account Free mode.

As of October 16, 2026. Check the service's model list and your account limits when availability or free-access policies change.

Hugging Face Inference⁴ Providers currently includes no monthly credits for ordinary Free accounts, so it is excluded from this free API list. Downloading publicly released model files remains a separate option.

OpenRouter permits up to 20 free-model requests per minute. Accounts with less than $10 in total purchases have a daily limit of 50 requests; accounts that have purchased at least $10 get 1,000 per day. Start with the default free allowance rather than purchasing credits just to raise it.

Groq's public Free Plan table lists both GPT-OSS models at 30 requests per minute, 1,000 per day, 8,000 tokens per minute and 200,000 tokens per day. A single long document can exceed the minute token limit even while requests remain. Check your actual per-model limits in the account's Limits page and adjust input length and request spacing.

An agent can exchange multiple requests while reading files, checking results and revising one task. Start with one short code review and inspect call counts and token usage in the usage history. If you receive 429, stop automatic repetition and follow the response's retry guidance.

Pin the model ID to a free entry and check whether your application switches models after an error. To compare open-weight models on OpenRouter, specify the chosen model's :free ID. The free router selects a model for each request, so use an individual ID when comparing the same open-weight model consistently. Choose deepseek-v4.1-flash-free on OpenCode. Leaving paid models out of fallback lists helps prevent a failed free request from triggering an unexpected paid call.

Keep account auto-recharge off as well. Coding tools such as OpenCode can use another model for auxiliary tasks such as session titles. Inspect model IDs and costs in the full usage history; use the direct API examples in each guide to isolate a single request.

Begin with a public example stripped of secrets and personal data. OpenCode's free DeepSeek provider states zero retention and no training use, while NVIDIA free endpoints are for development and testing and may log session information for security and product improvement. NVIDIA instructs users not to submit personal or confidential information.

Inputs and outputs in Mistral Free mode may be used for training. Check Anonymous improvement data under Admin → Privacy and disable it before use if you do not want that training use. On OpenRouter, terms vary with the provider actually handling the request, so also read the data policy on the model page.

For comparison, send the same code and question, then record whether each model identifies the issue and whether its proposed fix passes your tests. The Python examples in these guides print the answer after receiving it in full, so compare total response time. Measuring time to the first token requires a separate streaming configuration. Free API response times also include server queues and network latency. Compare your GPU's speed separately by running the same model locally.

If you work with public material occasionally, first see whether the free allowance is enough. If quotas repeatedly interrupt a growing workload, or the material must stay on your machine, follow the local LLM agent starter guide. Once you choose a model, use the hardware finder and speed comparison to explore local configurations.