Specifications
Context Window
1.0M tokens
Input Price/1M
$1.25
Output Price/1M
$2.50
Parameters
—
Speed
130 tok/s
Latency (TTFT)
22.7s
Benchmarks
Grok 4.3 results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Agentic
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 38.0 | 100.0 | — |
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SciCode | 47.0 | 100.0 | — |
| AA Coding Index | 41.0 | 100.0 | Artificial Analysis official API |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 65.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 53.2 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 90.0 | 100.0 | Artificial Analysis official API |
| IFBench | 83.0 | 100.0 | — |
| HLE | 35.0 | 100.0 | — |
Tool Use
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 98.0 | 100.0 | — |
Information
- Release date
- April 30, 2026
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Grok 4.3
What is Grok 4.3?
Grok 4.3 is an AI model developed by xAI, classified as a large language model (LLM). It is a multimodal model, capable of processing text, images, and potentially other media types. As a proprietary model, it is available via xAI's cloud API. With a context window of 1.0M tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
Grok 4.3 is usage-based, priced at $1.25/1M input tokens and $2.5/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The mid-range pricing balances quality and cost for most professional applications.
Benchmarks & Performance
Grok 4.3 was evaluated on 9 different benchmarks, covering categories like Agentic, Coding, Long Context, 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.
Recommended Use Cases
Grok 4.3 is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), multimodal processing combining text and images, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Grok 4.3 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.
Comparisons with Grok 4.3
Frequently Asked Questions
What is Grok 4.3?
Grok 4.3 is an AI model developed by xAI. It is a language model (LLM), with multimodal support (text, image and more).
How much does Grok 4.3 cost?
Grok 4.3 costs $1.25/1M input tokens and $2.5/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Grok 4.3 compare with other models?
In available benchmarks, Grok 4.3 scored: Terminal-Bench Hard: 38/100, SciCode: 47/100, AA Coding Index: 41/100. See the full table above for a detailed comparison.
Is Grok 4.3 open source?
No, Grok 4.3 is a proprietary model from xAI. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is Grok 4.3 best for?
Grok 4.3 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 →