- Text-to-Speech
Voxtral Mini TTS is Mistral’s 4B-parameter text-to-speech model that generates expressive, low-latency speech and supports multilingual, zero-shot voice cloning. It is available via the Mistral API…
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Grok Voice TTS 1.0
- Text-to-Speech
Grok Voice TTS 1.0 is xAI’s text-to-speech model that turns Grok’s language outputs into natural-sounding, expressive audio with multilingual support and fine-grained control over delivery. It is designed for real-time agents, content narration, and applications that need Grok’s reasoning paired with a lifelike voice.
Providers Comparison
Speed
Output tokens per second · Higher is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
End-to-End Response Time
Seconds · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
Price
USD per 1M tokens (blended) · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
About the model
What is Grok Voice TTS 1.0?
Grok Voice TTS 1.0 is a text-to-speech model from xAI that converts written text and Grok responses into high-quality synthetic speech with expressive control. It is primarily used to power real-time conversational agents, customer support or sales flows, and interactive applications that need fast, low-latency spoken replies. It is also used for generating narrated content like podcasts, videos, and accessibility audio from scripts or documents, often in multiple languages. It is part of xAI’s Grok voice and TTS stack that extends the Grok model family from text-only interaction into multimodal, voice-native experiences.
Model capabilities
5 Core Capabilities
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Natural Speech Synthesis
Generates natural‑sounding speech from text, capturing human‑like prosody, rhythm, and clarity for use in interactive and media applications.
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Conversational Output
Produces spoken responses suitable for real‑time assistants, enabling fluid back‑and‑forth dialogue when paired with a language understanding model.
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Expressive Voice Delivery
Conveys different speaking styles and emphasis, allowing more engaging, context‑appropriate audio responses than monotone or robotic TTS systems.
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Multilingual Speech Rendering
Reads out text in multiple languages supported by the underlying system, giving users localized spoken output where available.
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On‑Device Integration
Can be integrated into applications or devices to transform textual content into audio, improving accessibility and hands‑free interaction.
Use cases
6 Most Valuable Use Cases
- Audiobook Production
- Voice-Enabled Assistants
- Accessibility Screen Reading
- Customer Service IVR
- Voice Content Creation
- Developer TTS Integration
Transparent pricing
Cost Comparison
LLM API offers the lowest TTS prices with the fastest latency and highest reliability across providers.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 80ms | 120 req/s | 99.99% | $0.30/1M chars | $0.30/1M chars | ~30 min audio |
| xAI | Global | ~150ms | ~60 req/s | ~99.9% | ~$0.60/1M chars | ~$0.60/1M chars | ~20 min audio |
| OpenAI | Global | ~180ms | ~80 req/s | 99.9% | ~$0.75/1M chars | ~$0.75/1M chars | ~30 min audio |
| Google Cloud | Global | ~200ms | ~50 req/s | 99.9% | ~$1.20/1M chars | ~$1.20/1M chars | ~30 min audio |
| Amazon Web Services | Global | ~220ms | ~40 req/s | 99.9% | ~$1.00/1M chars | ~$1.00/1M chars | ~30 min audio |
Performance benchmarks
Technical Specifications
| Metric | Grok Voice TTS 1.0 (xAI) | OpenAI Realtime TTS (gpt-4o mini audio) | Google Gemini TTS (live audio) |
|---|---|---|---|
| Avg Latency (short sentence) | ~180ms | ~220ms | ~250ms |
| Max Utterance Duration | ~5 min | ~5 min | ~4 min |
| Streaming Support | Bidirectional, low-latency | Bidirectional, low-latency | Bidirectional, low-latency |
| Voices / Styles | ~10 voices | ~8 voices | ~10 voices |
| Languages Supported | ~20+ | ~30+ | ~25+ |
| Price per 1M chars (TTS) | ~$3.00 | ~$3.75 | ~$4.00 |
| Audio Sample Rate | 24 kHz | 24 kHz | 24 kHz |
| Service Uptime | ~99.9% | ~99.9% | ~99.9% |
30-day usage via LLM API
- 620M
- Characters synthesized (30 days)
- 7.8M
- API requests served (30 days)
- 180K
- Unique developer apps (30 days)
- 99.8%
- Avg service uptime (30 days)
Architecture & Integration
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
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Unified AI Routing
Automatically route each request to the best model for latency, quality, and reliability across providers, without changing your integration or redeploying code.
One endpoint, every model. -
Cost-Aware Orchestration
Optimize spend by dynamically selecting cheaper equivalents, enforcing budgets, and mixing premium and economy models per request, not per integration.
More IQ, less OPEX. -
Resilient Fallback Flows
Define automatic failovers when a provider degrades or times out, so critical paths keep working without manual incident playbooks or hotfixes.
Failures auto-heal. -
Deep LLM Observability
Trace every call across providers with unified logs, metrics, and structured payloads, making debugging, performance tuning, and governance actually manageable.
See every token. -
Task-Level Abstractions
Describe tasks—chat, extraction, classification, tools—once, and let LLM.API translate them into each provider’s schema and quirks for you.
Tasks, not providers. -
High-Throughput Batch Runs
Ship thousands of LLM jobs in one request with automatic chunking, retries, and aggregation, keeping queues fast without writing bespoke batching logic.
Batch at any scale.
Decision guide
When to Use — When NOT to Use
Use it if...
- You need to convert short text prompts into natural-sounding spoken audio responses.
- You need a TTS model aligned with xAI’s Grok ecosystem and tooling.
- Your use case involves quickly prototyping voice interfaces on platforms already using Grok.
- Your use case involves generating spoken replies for chatbots or conversational agents.
- You need TTS for English-centric applications where accents and languages can be limited.
- Your use case involves moderate-length messages rather than hours-long continuous narration.
Avoid if...
- You need ultra-realistic, cloned voices that are indistinguishable from specific human speakers.
- Your workload requires broad multilingual TTS coverage beyond English and a few variants.
- You need finely controllable prosody, emotional styles, and phoneme-level editing for production audio.
- Your workload requires guaranteed on-device inference without relying on remote xAI services.
- You need a long-track-record TTS system with extensive third-party integrations and ecosystem tools.
- Your workload requires highly optimized TTS for very low-bandwidth or embedded hardware environments.
FAQ
Frequently Asked Questions
-
What is Grok Voice TTS 1.0?
Grok Voice TTS 1.0 is xAI’s text-to-speech model available through LLM.API for converting text into natural-sounding audio.
-
What is Grok Voice TTS 1.0 best suited for?
It is best for real-time voice responses, voice-enabling chatbots, and generating narration or audio prompts from text.
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How is Grok Voice TTS 1.0 priced on LLM.API?
Pricing is per generated audio unit (e.g., characters or tokens), with exact rates defined in the LLM.API Grok Voice TTS 1.0 pricing table.
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What is the context window of Grok Voice TTS 1.0?
Grok Voice TTS 1.0 supports long text inputs typical for TTS, with the exact maximum input length documented in the LLM.API reference.
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How fast is Grok Voice TTS 1.0 in terms of latency?
It is optimized for low latency streaming playback so applications can start playing audio shortly after sending text.
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What modalities does Grok Voice TTS 1.0 support?
It accepts text as input and outputs synthesized audio, optionally with configurable voices and audio formats depending on LLM.API settings.
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How do I call Grok Voice TTS 1.0 through LLM.API?
Use the LLM.API text-to-speech endpoint with the model name "grok-voice-tts-1.0" and include your LLM.API key in the authorization header.
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How does Grok Voice TTS 1.0 compare to other TTS models on LLM.API?
Compared with generic TTS models, it focuses on natural prosody and responsiveness, though exact quality and speed trade-offs depend on your configuration.
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What are the main limitations of Grok Voice TTS 1.0?
It may mispronounce rare names or domain-specific jargon and might require preprocessing or SSML-style hints for perfect prosody.
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Can I stream audio output from Grok Voice TTS 1.0?
Yes, LLM.API supports streaming responses so your application can begin playing Grok Voice TTS 1.0 audio as it’s generated.
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