Context Window
131K tokens
Input Price/1M
$0.30
Output Price/1M
$0.50
Parameters
—
Speed
54 tok/s
Latency (TTFT)
502ms
Grok 3 Mini results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 17.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 70.0 | 100.0 | Artificial Analysis official API |
| SciCode | 41.0 | 100.0 | — |
| AA Coding Index | 25.2 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 83.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 50.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 99.2 | 100.0 | Artificial Analysis official API |
| AIME 2025 | 85.0 | 100.0 | Artificial Analysis official API |
| AA Math Index | 84.7 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 32.1 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 82.8 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 79.0 | 100.0 | Artificial Analysis official API |
| IFBench | 46.0 | 100.0 | — |
| HLE | 11.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 90.0 | 100.0 | — |
Grok 3 Mini is an AI model developed by xAI, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via xAI's cloud API. With a context window of 131K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Grok 3 Mini is usage-based, priced at $0.3/1M input tokens and $0.5/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Grok 3 Mini was evaluated on 15 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show exceptional performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Grok 3 Mini is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
In the 2026 AI model ecosystem, Grok 3 Mini competes directly with similarly capable models. xAI competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Grok 3 Mini is an AI model developed by xAI. It is a language model (LLM).
Grok 3 Mini costs $0.3/1M input tokens and $0.5/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, Grok 3 Mini scored: Terminal-Bench Hard: 17/100, LiveCodeBench: 70/100, SciCode: 41/100. See the full table above for a detailed comparison.
No, Grok 3 Mini is a proprietary model from xAI. It is available via cloud API. For open source alternatives, check our open source model ranking.
Grok 3 Mini excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations.
Last updated: June 01, 2026 • View methodology →