Grok 4.3
xAI's frontier Grok model with strong reasoning, coding, and agentic tool use, plus vision and real-time knowledge from X.
Grok 4.3 is a cloud text model built by xAI. It is multimodal: alongside a text prompt it accepts images, then replies with generated text. Its context window handles up to 1.05M input tokens and up to 131K output tokens, and it supports adjustable reasoning effort for harder problems. Generation can be tuned with system instructions, temperature, and top-p sampling. It runs through Runware using your own API key, from $1.25 per million input tokens.
- Released
- 4 months ago (Apr 2026)
- Pricing
- $1.25 / 1M in · $2.50 / 1M out
- Inputs
- Text, Images
- Context window
- 1.05M in · 131K out
- Reasoning
- Adjustable effort
- Controls
- System prompt, Temperature, Top-p
Examples
Generated with Grok 4.3 via Runware. The same three prompts run against every text model in the catalog, shown verbatim — so the only thing that changes between two models’ answers is the model.
Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.
An API is a set of rules that lets one computer program request information or actions from another program. It defines how they exchange data in a structured way without revealing their internal details.
A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.
For a two-person startup, the clear recommendation is to use a hosted authentication provider. Building secure auth from scratch consumes months of engineering effort on a non-differentiating problem while exposing the company to serious security risks and compliance burdens that a tiny team cannot reliably manage. The single strongest argument against this recommendation is that hosted services create recurring per-user costs and potential vendor lock-in, which can become expensive and disruptive once the product scales or if the provider raises prices or alters its offering.
Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.
Predicting spending on artificial intelligence initiatives presents significant challenges for companies because several factors introduce variability that traditional budgeting processes struggle to accommodate. One major cause is the rapid advancement in AI models and tools, which often leads to sudden shifts in required infrastructure as newer more efficient or powerful options emerge unexpectedly from research labs. Another factor stems from usage patterns that prove difficult to forecast accurately since adoption rates within the organization can surge or fluctuate based on employee experimentation and project successes that are hard to anticipate in advance. Additionally integration efforts frequently uncover hidden expenses related to data cleaning security compliance and specialized personnel that were not apparent during initial planning stages. To address these uncertainties executives should establish flexible budget allocations with built-in contingency reserves and implement continuous monitoring systems that track expenditures in real time across all departments. Regular reviews involving cross-functional teams can help adjust projections promptly while piloting small-scale projects before any full deployment allows for better estimation of actual costs involved in scaling. This approach enables more responsive and accurate financial oversight without stifling valuable innovation efforts throughout the company as a whole.
xAI
xAI builds the Grok family — frontier reasoning LLMs plus Grok Imagine video and voice models, integrated with real-time knowledge from X.
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