Lightning v3.1 Pro | Smallest AI Docs

Latest Release

Lightning v3.1 Pro is a premium 44.1 kHz text-to-speech pool with improved naturalness and a curated voice catalog. Runs on dedicated inference capacity, isolated from general traffic. Concurrency, latency, and rate limits are identical to standard Lightning v3.1; the difference is voice quality and the catalog.

44.1 kHz

Native sample rate

200ms

TTFB at 40 concurrent requests

English + Hindi

Indian voices code-switch; British and American voices English-only

3.3x

Real-time factor (faster than playback)

Model Overview


Developed by	Smallest AI
Model type	Text-to-Speech / Speech Synthesis
Languages	English (`en`), Hindi (`hi`), `auto`
License	Proprietary
Version	v3.1 Pro
Model ID	`lightning_v3.1_pro`
Native sample rate	44,100 Hz

Key Capabilities

Real-Time Optimized

Ultra-low latency architecture designed for conversational AI and live streaming.

Streaming

HTTP, SSE, and WebSocket support for real-time applications.

Multi-Language

Indian voices speak English + Hindi with automatic code-switching. British and American voices speak English.

High Fidelity

Broadcast-quality 44.1 kHz audio with natural prosody, intonation, and conversational rhythm.

Curated Voice Catalog

Premium voices across American, British, and Indian accents.

Pronunciation Control

Custom pronunciation dictionaries for specialized vocabulary, brand names, and domain-specific terms.

How to use it

Pro is selected via the model body parameter on the unified TTS routes — no separate endpoint to call.

$ curl -X POST "https://api.smallest.ai/waves/v1/tts" \
>   -H "Authorization: Bearer $SMALLEST_API_KEY" \
>   -H "Content-Type: application/json" \
>   -H "Accept: audio/wav" \
>   -d '{
>     "text": "Hello from the Lightning v3.1 Pro pool.",
>     "voice_id": "meher",
>     "model": "lightning_v3.1_pro",
>     "language": "en",
>     "sample_rate": 24000,
>     "output_format": "wav"
>   }' --output speech.wav

The same "model": "lightning_v3.1_pro" body field also routes to the Pro pool on the WebSocket and SSE endpoints.

On Atoms voice agents, open the agent’s voice picker and pick a Pro voice from the Pro filter chip. Atoms transparently routes to the Pro pool — no code change required.

Performance & Benchmarks

Pro improves on standard Lightning v3.1 across accuracy, expressiveness, delivery, and MOS quality. Tables below pair Pro with v3.1 Standard and the same competitor set documented on the Lightning v3.1 model card — open the accordion under each category to see what each metric measures.

Naturalness — higher is better

Metric	Lightning v3.1 Pro	Lightning v3.1	GPT-4o-mini	ElevenLabs Turbo v2.5	ElevenLabs Multilingual v2	Sonic-3	Gemini 2.5 Pro	Gemini 2.5 Flash	MAI-Voice-1	Inworld 1.5	S2 Pro
Overall	3.16	3.25	3.13	3.16	3.17	3.20	3.07	3.28	3.17	3.06	3.02
Naturalness	2.55	2.61	2.41	2.52	2.55	2.57	2.42	2.58	2.57	2.41	2.37
Intonation	3.06	3.22	3.06	3.07	3.06	3.12	2.90	3.28	3.04	2.91	2.86
Prosody	2.81	3.01	2.73	2.82	2.86	2.83	2.65	3.09	2.76	2.61	2.58

What each Naturalness metric measures

Overall — Holistic listener rating of how natural the voice sounds end-to-end.
Naturalness — How human-like the voice sounds; penalizes robotic or synthetic quality.
Intonation — Whether pitch rises and falls appropriately for the sentence type (question, statement, exclamation).
Prosody — The broader umbrella of rhythm, stress, and melody, how well the voice “reads” the sentence as a human would.

Expressiveness — higher is better

Metric	Lightning v3.1 Pro	Lightning v3.1	GPT-4o-mini	ElevenLabs Turbo v2.5	ElevenLabs Multilingual v2	Sonic-3	Gemini 2.5 Pro	Gemini 2.5 Flash	MAI-Voice-1	Inworld 1.5	S2 Pro
Overall	3.55	3.45	3.45	3.44	3.46	3.38	3.49	3.54	3.50	3.37	3.41
Paralinguistics	3.64	3.61	3.60	3.59	3.61	3.56	3.60	3.64	3.58	3.55	3.58
Emotions	3.47	3.29	3.30	3.28	3.31	3.19	3.38	3.44	3.41	3.19	3.23

What each Expressiveness metric measures

Overall — Holistic listener rating of how expressive the voice sounds given the context of the sentence.
Paralinguistics — Non-verbal vocal elements like laughter, sighs, or filler sounds (“um”, “uh”) and whether they’re rendered appropriately.
Emotions — How accurately the voice conveys the intended emotional tone (neutral, warm, urgent, etc.).

Delivery — higher is better

Metric	Lightning v3.1 Pro	Lightning v3.1	GPT-4o-mini	ElevenLabs Turbo v2.5	ElevenLabs Multilingual v2	Sonic-3	Gemini 2.5 Pro	Gemini 2.5 Flash	MAI-Voice-1	Inworld 1.5	S2 Pro
Boundary Consistency	4.96	4.94	4.94	4.93	4.95	4.93	4.88	4.99	4.77	4.90	4.88
Pronunciation Style	4.98	4.94	4.96	4.95	4.96	4.96	4.93	4.99	4.91	4.94	4.89
Natural Pace	4.72	4.47	4.57	4.51	4.51	4.01	4.23	4.66	4.47	4.33	3.74
Pause Placement	4.66	4.46	4.54	4.49	4.51	4.28	4.34	4.59	4.41	4.38	4.09
Breathing Naturalness	3.82	3.82	3.06	3.14	3.14	2.79	2.88	3.43	3.28	2.77	2.42

What each Delivery metric measures

Boundary Consistency — Whether phrase and sentence boundaries are marked consistently with pauses or pitch shifts, without arbitrary breaks mid-phrase.
Pronunciation Style — Not just correctness, but stylistic choices i.e., formal vs. casual register, regional accent consistency, honorific handling.
Natural Pace — Whether the speaking rate feels comfortable and appropriate for the content type, neither rushed nor dragging.
Pause Placement — Whether silences appear at semantically correct points (after commas, between clauses) rather than mid-word or mid-phrase.
Breathing Naturalness — Whether breath sounds occur at realistic points and with realistic frequency, not absent entirely or inserted randomly.

Accuracy

Mixed direction — WER, CER, Hallucination, and Deletion are lower is better; Pronunciation % is higher is better.

Whisper jiwer

Metric	Direction	Lightning v3.1 Pro	Lightning v3.1	GPT-4o-mini	ElevenLabs Turbo v2.5	ElevenLabs Multilingual v2	Sonic-3	Gemini 2.5 Pro	Gemini 2.5 Flash	MAI-Voice-1	Inworld 1.5	S2 Pro
WER	lower	1.36%	1.57%	1.26%	1.35%	1.33%	1.43%	1.26%	1.37%	1.25%	1.10%	2.83%
CER	lower	0.40%	0.67%	0.52%	0.60%	0.54%	0.59%	0.62%	0.61%	0.50%	0.47%	1.16%
Hallucination	lower	0.00%	0.03%	0.07%	0.08%	0.01%	0.06%	0.04%	0.01%	0.06%	0.00%	0.22%
Deletion	lower	0.00%	—	0.14%	0.17%	0.18%	0.16%	0.24%	0.18%	0.15%	0.12%	0.33%
Pronunciation % _{Whisper jiwer}	higher	98.68%	98.61%	98.94%	98.90%	98.87%	98.79%	99.02%	98.82%	98.95%	99.02%	97.72%

Whisper LLM

Metric	Direction	Lightning v3.1 Pro	GPT-4o-mini	ElevenLabs Turbo v2.5	ElevenLabs Multilingual v2	Sonic-3	Gemini 2.5 Pro	Gemini 2.5 Flash	MAI-Voice-1	Inworld 1.5	S2 Pro
WER	lower	0.96%	0.82%	0.72%	0.57%	0.88%	0.70%	0.72%	0.60%	0.55%	2.15%
CER	lower	0.34%	0.30%	0.28%	0.21%	0.30%	0.35%	0.33%	0.23%	0.18%	1.03%
Hallucination	lower	0.00%	0.07%	0.07%	0.00%	0.02%	0.02%	0.01%	0.03%	0.00%	0.10%
Pronunciation % _{Whisper LLM}	higher	99.04%	99.25%	99.35%	99.43%	99.14%	99.32%	99.29%	99.43%	99.45%	97.95%

What each Accuracy metric measures

WER (Word Error Rate) — Percentage of words in the transcript that differ from the reference; measures how faithfully the TTS renders the input text.
CER (Character Error Rate) — Like WER but at the character level.
Hallucination — Words or sounds the TTS generates that have no basis in the input text. Insertions, substitutions, or fabricated content.
Deletion — Words from the reference text that the TTS dropped entirely.
Pronunciation % — The proportion of words pronounced correctly out of total words.
Whisper jiwer vs Whisper LLM — Two judging methodologies. jiwer uses raw Whisper-decoded transcripts; LLM-judged uses a follow-on LLM to normalize transcription noise. Both report the same metric family; LLM-judged tends to give lower error rates by reducing false positives from punctuation/casing.

MOS v2 — higher is better

Metric	Lightning v3.1 Pro	Lightning v3.1	GPT-4o-mini	ElevenLabs Turbo v2.5	ElevenLabs Multilingual v2	Sonic-3	Gemini 2.5 Pro	Gemini 2.5 Flash	MAI-Voice-1	Inworld 1.5	S2 Pro
Mean MOS	4.22	—	4.16	3.98	4.02	3.76	4.11	4.24	3.97	3.73	3.99
UTMOS	3.76	—	3.76	3.37	3.41	2.77	3.57	3.71	3.33	2.54	3.50
WV-MOS	5.05	4.71	4.55	4.60	4.63	4.76	4.65	4.76	4.62	4.91	4.48

What each MOS metric measures

Mean MOS — Mean Opinion Score: average listener rating on a 1–5 scale across the test set; the canonical aggregate quality metric in TTS evaluation.
UTMOS — A predicted MOS from the UTMOS reference model — an automated proxy for subjective quality.
WV-MOS — A predicted MOS from the WavLM-based WV-MOS reference model — another automated proxy commonly reported alongside UTMOS for cross-validation.

Want to reproduce these results? See the TTS evaluation script to measure TTFB and synthesis quality in your own environment.

Supported Languages

Pro language support varies per voice — Indian Pro voices speak English with native Hindi code-switching; British and American Pro voices speak English only. For languages outside these, use the standard Lightning v3.1 model.

Voice group	Languages	Code-switching
Indian Pro voices	English (`en`), Hindi (`hi`)	English ↔ Hindi within a single utterance via `language="auto"`
British Pro voices	English (`en`)	—
American Pro voices	English (`en`)	—

Voice Catalog

The Pro voice catalog is distinct from standard Lightning v3.1. Voices below are listed in recommended ranking per accent group.

Indian — Female

Voice ID	Name
`rhea`	Rhea
`zariya`	Zariya
`kareena`	Kareena
`mishka`	Mishka
`inaaya`	Inaaya
`saira`	Saira
`meher`	Meher
`aarini`	Aarini

Indian — Male

Voice ID	Name
`aviraj`	Aviraj
`vyom`	Vyom
`zoravar`	Zoravar
`reyansh`	Reyansh
`ahan`	Ahan

British — Female

Voice ID	Name
`cressida`	Cressida
`elowen`	Elowen
`ottilie`	Ottilie
`seraphina`	Seraphina
`tabitha`	Tabitha
`arabella`	Arabella

British — Male

Voice ID	Name
`benedict`	Benedict
`cormac`	Cormac
`everett`	Everett
`finley`	Finley
`rupert`	Rupert
`winston`	Winston
`caspian`	Caspian

American — Female

Voice ID	Name
`willow`	Willow
`autumn`	Autumn
`skylar`	Skylar
`savannah`	Savannah
`kennedy`	Kennedy
`reagan`	Reagan
`sierra`	Sierra

American — Male

Voice ID	Name
`maverick`	Maverick
`brooks`	Brooks
`hunter`	Hunter
`colton`	Colton
`wesley`	Wesley
`asher`	Asher

Need a voice not in this list? Use the standard Lightning v3.1 catalog (217 voices, more languages, voice cloning). Pass "model": "lightning_v3.1" (or omit the field) instead of lightning_v3.1_pro.

API Reference

Endpoints

Endpoint	Method	Use Case
`https://api.smallest.ai/waves/v1/tts`	POST	Synchronous synthesis
`https://api.smallest.ai/waves/v1/tts/live`	POST (SSE)	Server-sent events streaming
`wss://api.smallest.ai/waves/v1/tts/live`	WebSocket	Real-time streaming

Request Parameters

Parameter	Type	Required	Default	Description
`text`	string	Yes	—	Text to synthesize
`voice_id`	string	Yes	—	Voice identifier (Pro catalog above)
`model`	string	No	`lightning_v3.1`	Pass `lightning_v3.1_pro` to route to the Pro pool. The field is optional, but the default routes to standard Lightning v3.1 — for Pro you must set it explicitly.
`sample_rate`	integer	No	`44100`	Output sample rate (Hz)
`speed`	float	No	`1.0`	Speech speed (0.5–2.0)
`language`	string	No	`"auto"`	`en`, `hi`, or `auto` (per voice’s `tags.language`)
`output_format`	string	No	`"pcm"`	`pcm`, `mp3`, `wav`, `ulaw`, `alaw`
`pronunciation_dicts`	array	No	—	List of pronunciation dictionary IDs — works on REST sync, SSE, and WebSocket

Quickstart

Generate your first audio in under a minute with a single API call.

Technical Specifications

Audio Output

Specification	Details
Native sample rate	44,100 Hz
Supported sample rates	8,000 / 16,000 / 24,000 / 44,100 Hz
Output formats	PCM, MP3, WAV, ulaw, alaw
Audio channels	Mono

Text Formatting Guidelines

Aspect	Recommendation
Language scripts	Use native script for each language. English in Latin script; Hindi in Devanagari
Break points	Natural punctuation (`.` `!` `?` `,`)
Mixed language	Use native script per language; avoid transliteration

Compute Infrastructure

Hardware

Recommended GPU: NVIDIA L40S
Recommended VRAM: 48 GB

Software

Server regions (AWS): India (Hyderabad), USA (Oregon)
Automatic geo-location based routing for lowest latency

Best Practices

Voice ID + model pairing

Pair Pro voice IDs above with "model": "lightning_v3.1_pro". The API does not currently reject mismatched pairings, but pairing a Pro voice with "model": "lightning_v3.1" (or omitting model) can produce wrong or hallucinated audio. Server-side validation is on the roadmap.

Language selection

Each voice’s supported languages live in tags.language on the voice catalog. Passing a language outside that list is accepted by the API but produces English-pronounced output, since the voice wasn’t trained on it. Pick a voice whose tags.language matches your target language.

Text Formatting

Chunk boundaries. Segment input at natural prosodic boundaries (. ! ? ,). Maximum chunk size is 250 characters; optimal throughput at 140 characters per request.
Script integrity. Use native script for each language. Mixed-script input within a single language token produces unpredictable phoneme mappings.
Lexicon overrides. Use pronunciation dictionaries for domain-specific terms, brand names, and acronyms where default grapheme-to-phoneme conversion is insufficient.

For comprehensive text formatting rules (numeric handling, date/time, symbols, chunking logic), see TTS Best Practices.

Use Cases

Direct Use

Voice assistants and conversational AI
Interactive chatbots with voice output
Real-time narration and live streaming
Accessibility tools and screen readers
Customer service automation

Downstream Use

Multi-turn conversational agents
Audio content generation pipelines
Telephony and IVR systems
Podcast generation

Limitations & Safety

Known Limitations

No voice cloning. Voice cloning is not available on the Pro pool. Clones continue to use standard Lightning v3.1 and the existing voice-cloning flow.

Lightning v3.1 Pro must not be used for impersonation or fraud, generating deceptive audio content (deepfakes), creating content that violates consent or privacy, harassment or abuse, or any illegal or unethical purposes.

Safety & Compliance

No retention of synthesized audio
Usage monitoring for policy compliance

For compliance documentation (GDPR, SOC2, HIPAA), contact support@smallest.ai.

Channel	Details
Support	support@smallest.ai
Documentation	docs.smallest.ai/waves
Console	app.smallest.ai
Community	Discord