xAI
Grok 4.6 — SpaceXAI with Imagine Image 2.0, Voice Transcribe 2.0, and 500K context
xAI (operating as SpaceXAI) builds the Grok model family. Grok 4.6 is the current flagship with a 500K token context window. The September 2026 platform includes Imagine Image 2.0, Imagine Video 1.5, Voice API (speech-to-speech, TTS, STT), and Grok Voice Transcribe 2.0. Available on Azure AI Foundry, Oracle OCI, and Google Cloud Vertex. Check x.ai/api for current rates.
Grok 4.6 combines frontier-tier intelligence with real-time X/Twitter grounding, a 500K context window, and a full multimodal platform (Imagine Image 2.0, Imagine Video 1.5, Voice API).
- Grok 4.6: competitive frontier pricing — check live table for current rates
- 500K token context window
- Real-time X/Twitter data and web search grounding
- Imagine Image 2.0 and Imagine Video 1.5 for multimodal generation
- Voice API: speech-to-speech, TTS, and STT under one key
- Available on Azure AI Foundry, Oracle OCI, and Google Cloud Vertex
- No open-weight models — full vendor lock-in
- Smaller ecosystem and fewer integrations than OpenAI
- Limited model selection compared to frontier competitors
xAI Models
| Model | Modality | Tier | Price | Cached /1M | TTFT | Throughput | Context | Intel. | Caps | |
|---|---|---|---|---|---|---|---|---|---|---|
grok-4-fast-reasoning Grok 4 | Chat | efficient | $0.20/ $0.50 in / out per 1M EST Jul 2026 | — | 800ms | 150 t/s | 2.0M | 84 | ||
grok-4-fast-non-reasoning Grok 4 | Chat | efficient | $0.20/ $0.50 in / out per 1M EST Jul 2026 | — | 400ms | 200 t/s | 2.0M | 82 | ||
grok-4-1-fast-reasoning Grok 4 | Chat | efficient | $0.20/ $0.50 in / out per 1M EST Jul 2026 | — | 750ms | 160 t/s | 2.0M | 85 | ||
grok-4-1-fast-non-reasoning Grok 4 | Chat | efficient | $0.20/ $0.50 in / out per 1M EST Jul 2026 | — | 380ms | 210 t/s | 2.0M | 83 | ||
grok-code-fast-1 Grok Code | Chat | efficient | $0.20/ $1.50 in / out per 1M EST Jul 2026 | — | 350ms | 190 t/s | 256K | 82 | ||
grok-3-mini Grok 3 | Chat | efficient | $0.30/ $0.50 in / out per 1M EST Jul 2026 | — | 350ms | 200 t/s | 131K | 62 | ||
grok-3-mini-fast Grok 3 | Chat | efficient | $0.60/ $4.00 in / out per 1M EST Jul 2026 | — | 180ms | 400 t/s | 131K | 62 | ||
grok-build-0.1 Grok Build | Chat | advanced | $1.00/ $2.00 in / out per 1M EST Oct 2026 | — | 400ms | 160 t/s | 200K | 88 | ||
grok-4.3 Grok 4 | Chat | advanced | $1.25/ $2.50 in / out per 1M EST Oct 2026 | — | 500ms | 140 t/s | 200K | 90 | ||
grok-4.20 Grok 4 | Chat | advanced | $1.25/ $2.50 in / out per 1M EST Oct 2026 | — | 480ms | 145 t/s | 200K | 91 | ||
grok-4-7 Grok 4 | Chat | frontier | $2.00/ $6.00 in / out per 1M EST Oct 2026 | $0.50 | 900ms | 90 t/s | 256K | 90 | ||
grok-4.5 Grok 4 | Chat | frontier | $2.00/ $6.00 in / out per 1M EST Jul 2026 | — | 700ms | 110 t/s | 500K | 90 | ||
grok-4.6 Grok 4 | Chat | frontier | $2.00/ $6.00 in / out per 1M EST Oct 2026 | — | 700ms | 110 t/s | 200K | 93 | ||
grok-3 Grok 3 | Chat | frontier | $3.00/ $15.00 in / out per 1M EST Jul 2026 | — | 800ms | 85 t/s | 131K | 80 | ||
grok-4-0709 Grok 4 | Chat | frontier | $3.00/ $15.00 in / out per 1M EST Jul 2026 | — | 1.2s | 70 t/s | 256K | 88 | ||
grok-3-fast Grok 3 | Chat | advanced | $5.00/ $25.00 in / out per 1M EST Jul 2026 | — | 400ms | 180 t/s | 131K | 80 |
xAI — Frequently Asked Questions (FAQs)
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Full comparison tablexAI LLM pricing overview
xAI is a proprietary AI lab that develops and hosts its own large language models. xAI (operating as SpaceXAI) builds the Grok model family. Grok 4.6 is the current flagship with a 500K token context window. The September 2026 platform includes Imagine Image 2.0, Imagine Video 1.5, Voice API (speech-to-speech, TTS, STT), and Grok Voice Transcribe 2.0. Available on Azure AI Foundry, Oracle OCI, and Google Cloud Vertex. Check x.ai/api for current rates. Common use cases include Real-time data, Reasoning, Vision, Image generation. Headquartered in San Francisco, CA, founded 2023. All models are accessible via a REST API compatible with standard OpenAI-style request formats, enabling drop-in integration with most LLM frameworks and orchestration tools.
xAI vs other LLM providers
xAI competes with OpenAI, Anthropic, Google, Groq, Together AI, Mistral, Cohere, and other inference API providers across dimensions of price, throughput, latency, context window, and model intelligence. Grok 4.6 combines frontier-tier intelligence with real-time X/Twitter grounding, a 500K context window, and a full multimodal platform (Imagine Image 2.0, Imagine Video 1.5, Voice API). Use the LLM provider comparison tool to see xAI token pricing, latency, and throughput side-by-side with any other provider. The full LLM pricing table shows all providers ranked by input token cost, output token cost, and throughput in a single sortable view.
Why choose xAI?
xAI stands out because: Grok 4.6 combines frontier-tier intelligence with real-time X/Twitter grounding, a 500K context window, and a full multimodal platform (Imagine Image 2.0, Imagine Video 1.5, Voice API).. The API currently offers 16 models, spanning 5 frontier, 4 advanced, 7 efficient tiers. For teams running high-volume inference workloads, prompt caching and batch API endpoints can reduce effective input token costs by 50–90% — check the context window cost guide for a full breakdown of caching economics.
Understanding xAI token pricing
xAI charges separately for input (prompt) and output (completion) tokens, priced per 1M tokens in USD. Output tokens are typically 3–5× more expensive than input tokens due to the compute cost of autoregressive generation. The cheapest {meta.name} input rate is currently $0.20/1M tokens. Prices shown are sourced from xAI's public pricing page and updated every 15 minutes. Need help estimating your spend? Read the LLM API cost calculator guide — it covers tokens, context windows, prompt caching, and batch discounts with worked examples for RAG, chat history, and document processing workloads.
xAI context window and model capabilities
Context window size directly affects both capability and cost — every token in the context window is charged as an input token. xAI's largest context window is 2.0M tokens. For RAG and document processing workloads, longer context windows enable richer retrieval but increase per-call costs proportionally. Prompt caching — where supported — stores the KV state of repeated prefixes and charges 75–90% less for cache hits, making it the most impactful cost optimization for applications with consistent system prompts or retrieved documents. See the LLM context window cost guide for a full analysis of how context length affects your API bill.
Self-hosted vs managed inference: when xAI makes sense
Managed inference APIs like xAI eliminate infrastructure overhead — no GPU provisioning, driver management, or model serving stack to maintain. The trade-off is cost at scale: a single H100 at ~$2.50/hr can serve ~500K tokens/min of Llama 3.3 70B, which at xAI API rates would cost significantly more per token. The break-even point depends on your request volume, latency requirements, and engineering capacity. For teams processing fewer than ~10M tokens/day, managed APIs are almost always cheaper when total cost of ownership is considered. Above that threshold, self-hosted inference on rented GPU compute typically wins on unit economics. Read the cheapest GPU cloud guide for a full break-even analysis. Historical xAI token price data is available in the LLM price history charts.
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