- Text Generation
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Zonos v0.1 Hybrid
- Text Generation
Zonos v0.1 Hybrid is an open-weight text-to-speech model from Zyphra that uses a hybrid SSM–transformer backbone to generate high‑quality, expressive 44 kHz speech from text. It supports multiple English accents and voice types and is competitive with leading commercial TTS systems.
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 Zonos v0.1 Hybrid?
Zonos v0.1 Hybrid is an Apache-2.0 licensed hybrid-SSM text-to-speech model that predicts DAC tokens from phonemized text to produce natural-sounding speech. It is mainly used for high-fidelity voice cloning from short reference clips and for controllable speech generation where speaking rate, pitch variation, and emotions (e.g., sadness, anger, happiness) must be specified. It also targets production TTS applications needing diverse American and British English voices across male and female speakers with open-weight deployability. Zonos v0.1 Hybrid is part of Zyphra’s Zonos v0.1 family of models, alongside the transformer-only variant and later successors such as ZONOS2.
Model capabilities
5 Core Capabilities
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Text-to-Speech
Converts English and several other languages from text into natural, high-quality speech using a hybrid neural TTS architecture.
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Voice Cloning
Generates high-fidelity voice clones from short audio samples, preserving speaker identity, tone, and style in synthesized speech.
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Multilingual Support
Supports speech generation in multiple languages, including English, Japanese, Chinese, French, and German, with controllable speaking style.
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Expressive Prosody
Allows fine-grained control over speech speed, pitch, quality, and emotion for expressive, context-appropriate audio output.
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Real-Time Inference
Delivers low-latency, real-time speech generation suitable for interactive applications on modern GPUs like the RTX 4090.
Use cases
6 Most Valuable Use Cases
- Voice Cloning Narration
- Audiobook Production
- Virtual Assistants Speech
- Real-Time Dubbing
- Accessibility Voiceovers
- Emotion-Rich TTS
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and highest performance access to Zonos-class models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 80ms | 120 tps | 99.99% | $0.20 | $0.20 | 128K |
| Zyphra (direct) | Global | ~140ms | ~60 tps | ~99.9% | ~$0.35 | ~$0.35 | ~64K |
| Replicate | US East | ~160ms | ~40 tps | ~99.5% | ~$0.40 | ~$0.40 | ~32K |
| Together AI | US West | ~150ms | ~70 tps | ~99.9% | ~$0.30 | ~$0.30 | ~64K |
| Fireworks AI | Global | ~130ms | ~80 tps | ~99.9% | ~$0.28 | ~$0.28 | ~64K |
Performance benchmarks
Technical Specifications
| Metric | Zonos v0.1 Hybrid | GPT-4.1 Mini | Claude 3.5 Haiku |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~250ms |
| Context Window | 128K | 128K | 200K |
| Input Price ($/1M tokens) | $0.10 | $0.15 | $0.20 |
| Output Price ($/1M tokens) | $0.20 | $0.60 | $0.80 |
| Max Output Tokens | 4K | 4K | 4K |
| Throughput | 120 tps | 100 tps | 90 tps |
| Uptime | 99.5% | 99.9% | 99.9% |
30-day usage via LLM API
- 1.9B
- Prompt tokens processed (last 30 days)
- 320M
- Completion tokens generated (last 30 days)
- 4.6M
- API requests served (last 30 days)
- 41.3K
- Unique developers using this model (last 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 optimal model based on cost, latency, and quality. One API, any provider, no per-vendor integration work.
Smart model selection -
Cost-Aware Orchestration
Tune requests by budget and quality with fine-grained controls over models, tokens, and retry strategies. Reduce AI spend without rewriting your application.
Lower spend, same output -
Resilient Fallback Flows
Define automatic fallbacks when a provider is slow or unavailable. Keep your product responsive and reliable even during provider outages and rate limits.
Never drop a request -
Full-Stack Observability
Trace every call across providers with logs, metrics, and structured events. Debug failures faster and optimize prompts with real production traffic data.
See every token -
Task-Native Abstractions
Call tasks like chat, tools, RAG, and embeddings through one consistent interface. Swap models or vendors without changing how your code defines work.
APIs that match tasks -
High-Throughput Batch APIs
Run large batches of generations, embeddings, and evaluations with one request. Maximize throughput, minimize overhead, and keep provider-specific limits abstracted away.
Scale jobs, not scripts.
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a cost-efficient hybrid model that balances performance and affordability for production.
- You need solid general-purpose language understanding for chatbots, assistants, or basic agents.
- Your use case involves moderate-length context processing without extremely long documents or transcripts.
- Your use case involves typical enterprise NLP tasks like classification, extraction, and summarization.
- You need a model suitable for experimentation, prototyping, and iterating on AI product ideas.
Avoid if...
- You need cutting-edge reasoning performance rivaling the very top-tier frontier foundation models.
- Your workload requires extremely long context handling, such as entire book-scale inputs.
- You need state-of-the-art performance on specialized domains like complex math or formal proof.
- Your workload requires rigorous, battle-tested safety, compliance, and governance in regulated industries.
- You need guaranteed ultra-low latency and global-scale reliability for mission-critical real-time systems.
FAQ
Frequently Asked Questions
-
What is Zonos v0.1 Hybrid?
Zonos v0.1 Hybrid is a Zyphra foundation model accessible through LLM.API, designed for general-purpose text generation and reasoning workloads.
-
What is Zonos v0.1 Hybrid best suited for?
Zonos v0.1 Hybrid is best for chatbots, agents, code assistance, and knowledge tasks where balanced capability and cost matter.
-
How is Zonos v0.1 Hybrid priced on LLM.API?
Pricing for Zonos v0.1 Hybrid is usage-based per 1,000 tokens; check your LLM.API dashboard or pricing page for current rates.
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What is the context window of Zonos v0.1 Hybrid?
Zonos v0.1 Hybrid supports a context window of up to 32,000 tokens via LLM.API.
-
What latency should I expect from Zonos v0.1 Hybrid?
Typical latency is a few hundred milliseconds to first token, varying with prompt length, output size, and LLM.API region.
-
Which modalities does Zonos v0.1 Hybrid support?
Zonos v0.1 Hybrid currently supports text input and text output only through LLM.API.
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How do I call Zonos v0.1 Hybrid through LLM.API?
Use the LLM.API chat or completion endpoint and set the model parameter to "zyphra/zonos-v0.1-hybrid" in your request.
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How does Zonos v0.1 Hybrid compare to similar LLMs?
Zonos v0.1 Hybrid targets competitive quality with strong cost efficiency, making it attractive versus similarly sized general-purpose open models.
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Does Zonos v0.1 Hybrid support streaming responses?
Yes, Zonos v0.1 Hybrid supports server-sent events streaming when you enable streaming in your LLM.API request.
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What are the main limitations of Zonos v0.1 Hybrid?
Zonos v0.1 Hybrid can hallucinate, lacks real-time knowledge, and should not be solely relied on for safety-critical or legally binding decisions.
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