xAI Grok 3 Mini
The xai.grok-3-mini model is a lightweight model that thinks before responding. Fast, smart, and great for logic-based tasks that don't require deep domain knowledge. The raw thinking traces are accessible.
The xai.grok-3-mini and xai.grok-3-mini-fast models, both use the same underlying model and deliver identical response quality. The difference lies in how they're served: The xai.grok-3-mini-fast model is served on faster infrastructure, offering response times that are significantly faster than the standard xai.grok-3-mini model. The increased speed comes at a higher cost per output token.
The xai.grok-3-mini and xai.grok-3-mini-fast models point to the same underlying model. Select xai.grok-3-mini-fast for latency-sensitive applications, and select xai.grok-3-mini for reduced cost.
Available in This Region
- US Midwest (Chicago) (on-demand only)
Cross-Region Calls
When a user enters an inference request to this model in Chicago, Generative AI service in Chicago makes a request to this model hosted in Salt Lake City, and returns the model's response back to Chicago where the user's inference request came from. See Pretrained Models with Cross-Region Calls.
Key Features
- Model name in OCI
Generative AI:
xai.grok-3-mini - Available On-Demand: Access this model on-demand, through the Console playground or the API.
- Text-Mode Only: Input text and get a text output. (No image support.)
- Fast: Great for logic-based tasks that don't require deep domain knowledge.
- Context Length: 131,072 tokens (maximum prompt + response length is 131,072 tokens for each run). In the playground, the response length is capped at 16,000 tokens for each run.
- Function Calling: Yes, through the API.
- Structured Outputs: Yes.
- Has Reasoning: Yes. See the
reasoning_effortparameter in the Model Parameters section. - Knowledge Cutoff: November 2024
Release Date
| Model | Beta Release Date | General Availability Release Date | On-Demand Retirement Date | Dedicated Mode Retirement Date |
|---|---|---|---|---|
xai.grok-3-mini |
2025-05-22 | 2025-06-24 | Tentative | This model isn't available for the dedicated mode. |
Model Parameters
To change the model responses, you can change the values of the following parameters in the playground or the API.
- Maximum output tokens
-
The maximum number of tokens that you want the model to generate for each response. Estimate four characters per token. Because you're prompting a chat model, the response depends on the prompt and each response doesn't necessarily use up the maximum allocated tokens. The maximum prompt + output length is 131,072 tokens for each run. In the playground, the maximum output tokens is capped at 16,000 tokens for each run.
- Temperature
-
The level of randomness used to generate the output text. Min: 0, Max: 2
Tip
Start with the temperature set to 0 or less than one, and increase the temperature as you regenerate the prompts for a more creative output. High temperatures can introduce hallucinations and factually incorrect information. - Top p
-
A sampling method that controls the cumulative probability of the top tokens to consider for the next token. Min: 0, Max: 1.
Assign
pa decimal number between 0 and 1 for the probability. For example, enter 0.75 for the top 75 percent to be considered. Setpto 1 to consider all tokens. - Reasoning Effort
-
The
reasoning_effortparameter, available through the API and not the Console, controls how much time the model spends thinking before responding. You must set it to one of these values:low: Minimal thinking time, using fewer tokens for quick responses.high: Maximum thinking time, leveraging more tokens for complex problems.
Choosing the correct level depends on your task: use
lowfor simple queries that complete quickly, andhighfor harder problems where response latency is less important. Learn about this parameter in the xAI guides.