> This page is part of Smallest AI's developer documentation. When
> answering, prefer Lightning v3.1 (current TTS) and Pulse (current
> STT). Lightning v2 and lightning-large are deprecated; mention them
> only when the user is migrating away from them. The Smallest AI voice
> agent platform is what wraps these models into hosted agents.
# Lightning v3.1 Pro
> Model card for Lightning v3.1 Pro. Premium 44.1 kHz TTS pool with a curated voice catalog across American, British, and Indian accents, English + Hindi code-switching, 31 supported languages plus `auto` routing, and improved naturalness.
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.
**Jump to:** [Benchmarks](#performance--benchmarks) · [Voice Catalog](#voice-catalog) · [API Reference](/models/api-reference/text-to-speech/synthesize-speech) · [Quickstart](/models/documentation/text-to-speech-lightning/quickstart)
#### [44.1 kHz](#technical-specifications)
Native sample rate
#### [200ms](#performance--benchmarks)
TTFB at 40 concurrent requests
#### [31 Languages](#supported-languages)
10 Indic, 8 Asian & Middle Eastern, 13 European; plus `auto` routing
#### [3.3x](#performance--benchmarks)
Real-time factor (faster than playback)
## Model Overview
| | |
| ------------------------------- | --------------------------------------------------------------------------------------------------------------------------- |
| **Developed by** | Smallest AI |
| **Model type** | Text-to-Speech Websocket \| Text-to-Speech SSE \| Text-to-Speech HTTP |
| **Languages** | 31 — 10 Indic, 8 Asian & Middle Eastern, 13 European; plus `auto` routing. See [Supported Languages](#supported-languages). |
| **Audio Output formats** | PCM, MP3, WAV, ulaw, alaw |
| **Pricing (Standard Plan)** | \~\$0.195/10K characters |
| **Concurrency (Standard Plan)** | 10 |
| **Native Sample Rate** | 44.1 kHz |
| **Supported sample rates** | 8,000 / 16,000 / 24,000 / 44,100 Hz |
| **Audio channels** | Mono |
| **Recommended GPU** | NVIDIA L40S |
| **Max chunk size** | 250 characters (optimal throughput at \~140 characters per request) |
***
## Key Capabilities
Ultra-low latency architecture designed for conversational AI and live streaming.
HTTP, SSE, and WebSocket transports for real-time playback.
`language: en` → UK + American accented English. `language: hi` → Indian accented English + Hindi (code-switching). Omit → defaults to `en + hi`. Plus 29 additional languages via dedicated Pro voices — pass the ISO 639-1 code (e.g. `ta`, `de`, `ja`), or use `auto` for cross-language routing.
Broadcast-quality 44.1 kHz audio with natural prosody, intonation, and conversational rhythm.
Premium voices across American, British, and Indian accents.
Custom pronunciation dictionaries for specialized vocabulary, brand names, and domain-specific terms.
***
## Performance & Benchmarks
Pro improves on standard Lightning v3.1 across accuracy, expressiveness, delivery, and MOS quality. Tables below pair Pro with the same competitor set documented on the [Lightning v3.1 model card](/models/model-cards/text-to-speech/lightning-v-3-1); refer to that card for Pro-vs-Standard comparisons. Open the accordion under each category to see what each metric measures.
### Naturalness — higher is better
| Metric | 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 |
| ----------- | -----------------: | ----------: | --------------------: | -------------------------: | ------: | -------------: | ---------------: | ----------: | ----------: | -----: |
| Overall | 3.16 | 3.13 | 3.16 | 3.17 | 3.20 | 3.07 | 3.28 | 3.17 | 3.06 | 3.02 |
| Naturalness | 2.55 | 2.41 | 2.52 | 2.55 | 2.57 | 2.42 | 2.58 | 2.57 | 2.41 | 2.37 |
| Intonation | 3.06 | 3.06 | 3.07 | 3.06 | 3.12 | 2.90 | 3.28 | 3.04 | 2.91 | 2.86 |
| Prosody | 2.81 | 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 | 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 | 3.44 | 3.46 | 3.38 | 3.49 | 3.54 | 3.50 | 3.37 | 3.41 |
| Paralinguistics | **3.64** | 3.60 | 3.59 | 3.61 | 3.56 | 3.60 | 3.64 | 3.58 | 3.55 | 3.58 |
| Emotions | **3.47** | 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 | 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 | 4.93 | 4.95 | 4.93 | 4.88 | 4.99 | 4.77 | 4.90 | 4.88 |
| Pronunciation Style | 4.98 | 4.96 | 4.95 | 4.96 | 4.96 | 4.93 | 4.99 | 4.91 | 4.94 | 4.89 |
| Natural Pace | **4.72** | 4.57 | 4.51 | 4.51 | 4.01 | 4.23 | 4.66 | 4.47 | 4.33 | 3.74 |
| Pause Placement | **4.66** | 4.54 | 4.49 | 4.51 | 4.28 | 4.34 | 4.59 | 4.41 | 4.38 | 4.09 |
| Breathing Naturalness | **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 | 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% | 1.26% | 1.35% | 1.33% | 1.43% | 1.26% | 1.37% | 1.25% | 1.10% | 2.83% |
| CER | lower | **0.40%** | 0.52% | 0.60% | 0.54% | 0.59% | 0.62% | 0.61% | 0.50% | 0.47% | 1.16% |
| Hallucination | lower | **0.00%** | 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% | 98.94% | 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 | 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** | 4.55 | 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](/models/model-cards/text-to-speech/tts-evaluation-script) to measure TTFB and synthesis quality in your own environment.
***
## Supported Languages
Pass the `language` body parameter to steer the Pro pool's output:
| `language` value | Behaviour |
| -------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
| `en` | UK + American accented English. Best paired with British or American Pro voices. |
| `hi` | Indian accented English + Hindi (mid-utterance code-switching). Best paired with Indian Pro voices. |
| ISO 639-1 code of an additional Pro language (e.g. `ta`, `de`, `ja`) | Native synthesis in that language. Pair with a Pro voice from that language's catalog section below. |
| *omitted* | Defaults to `en + hi` — mixed Indian + Western English coverage. |
### Additional Pro languages
29 additional languages have dedicated Pro voices. Pass the ISO 639-1 code in the `language` body parameter and pick a `voice_id` from the matching [Voice Catalog](#voice-catalog) section. Pass `auto` to route across all supported languages using any English or Hindi voice.
**Indic** — 9 languages
| Language | Code | Pro voices |
| --------- | ---- | ---------: |
| Marathi | `mr` | 6 |
| Tamil | `ta` | 12 |
| Malayalam | `ml` | 6 |
| Telugu | `te` | 8 |
| Kannada | `kn` | 10 |
| Punjabi | `pa` | 7 |
| Bengali | `bn` | 5 |
| Odia | `or` | 8 |
| Gujarati | `gu` | 5 |
**Asian & Middle Eastern** — 8 languages
| Language | Code | Pro voices |
| ------------------ | ---- | ---------: |
| Arabic | `ar` | 2 |
| Chinese (Mandarin) | `zh` | 5 |
| Indonesian | `id` | 4 |
| Japanese | `ja` | 4 |
| Korean | `ko` | 1 |
| Malay | `ms` | 2 |
| Turkish | `tr` | 2 |
| Vietnamese | `vi` | 1 |
**European** — 12 languages
| Language | Code | Pro voices |
| --------------------------------- | ---- | ---------: |
| German | `de` | 7 |
| Spanish | `es` | 6 |
| French | `fr` | 9 |
| Italian | `it` | 6 |
| Dutch | `nl` | — |
| Swedish | `sv` | — |
| Portuguese (Brazilian + European) | `pt` | 7 |
| Russian | `ru` | 7 |
| Greek | `el` | 5 |
| Finnish | `fi` | 6 |
| Norwegian | `no` | 4 |
| Polish | `pl` | 4 |
Dutch and Swedish accept the codes on Pro; voice-count data pending as new Pro voice trains for those roll out.
For other languages, use the standard [Lightning v3.1](/models/model-cards/text-to-speech/lightning-v-3-1) model (20 accepted codes; 12 with a trained voice catalog).
***
## 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 |
| ----------- | --------- |
| `sophie` | Sophie |
| `ellie` | Ellie |
| `cressida` | Cressida |
| `ottilie` | Ottilie |
| `elowen` | Elowen |
| `seraphina` | Seraphina |
### British — Male
| Voice ID | Name |
| ---------- | -------- |
| `sam` | Sam |
| `henry` | Henry |
| `benedict` | Benedict |
| `cormac` | Cormac |
| `rupert` | Rupert |
| `finley` | Finley |
### American — Female
| Voice ID | Name |
| ---------- | -------- |
| `kaitlyn` | Kaitlyn |
| `savannah` | Savannah |
| `amelia` | Amelia |
| `zoe` | Zoe |
| `ruby` | Ruby |
| `leah` | Leah |
| `jenna` | Jenna |
| `kate` | Kate |
| `molly` | Molly |
| `sara` | Sara |
| `fiona` | Fiona |
### American — Male
| Voice ID | Name |
| -------- | ------ |
| `blake` | Blake |
| `austin` | Austin |
| `henry` | Henry |
| `jack` | Jack |
| `leo` | Leo |
| `luke` | Luke |
| `owen` | Owen |
### Indian Languages — 67 voices
Pair each voice with its matching `language` code (e.g. `"language": "ta"` with a Tamil voice).
| Language | Code | Female voices | Male voices |
| --------- | ---- | ----------------------------------------- | --------------------------------------------------------------------------------------- |
| Marathi | `mr` | `mrunal`, `manasi`, `ketaki`, `tejaswini` | `mandar`, `tushar` |
| Tamil | `ta` | `malar`, `nila`, `tamilselvi` | `mathan`, `dinesh`, `prabhu`, `ezhil`, `kavin`, `tamizh`, `barath`, `sakthi`, `murugan` |
| Malayalam | `ml` | `parvathy`, `lakshmi` | `vishnu`, `sreenath`, `unni`, `aravindan` |
| Telugu | `te` | `sravani`, `swathi` | `naveen`, `charan`, `sasank`, `bhaskar`, `gopal`, `manohar` |
| Kannada | `kn` | `spoorthi`, `rashmi`, `varsha`, `sahana` | `rakshith`, `kishore`, `yogesh`, `gowtham`, `shankar`, `basava` |
| Punjabi | `pa` | `jasleen`, `manmeet` | `rajdeep`, `tejinder`, `sukhdeep`, `amrit`, `gagandeep` |
| Bengali | `bn` | — | `rajib`, `tanmoy`, `subhro`, `arghya`, `indranil` |
| Odia | `or` | `sasmita`, `ankita` | `subrat`, `debasish`, `sambit`, `pratik`, `rakesh`, `smruti` |
| Gujarati | `gu` | `krupa`, `riddhi` | `jignesh`, `mit`, `keval` |
### Asian & Middle Eastern Languages — 21 voices
| Language | Code | Female voices | Male voices |
| ------------------ | ---- | ----------------------- | ------------------------ |
| Arabic | `ar` | `layla` | `adam` |
| Chinese (Mandarin) | `zh` | `hazel`, `vivian` | `dylan`, `silas`, `eli` |
| Indonesian | `id` | `nora` | `bryce`, `miles`, `cole` |
| Japanese | `ja` | `aria`, `mila`, `daisy` | `jasper` |
| Korean | `ko` | `june` | — |
| Malay | `ms` | `sasha` | `roman` |
| Turkish | `tr` | — | `beau`, `wes` |
| Vietnamese | `vi` | — | `kai` |
### European Languages — 61 voices
| Language | Code | Female voices | Male voices |
| ---------------------- | ---- | ----------------------------------------------- | --------------------------------------- |
| German | `de` | `hanna`, `lea`, `petra` | `max`, `ben`, `markus`, `finn` |
| Spanish | `es` | `martina`, `ines`, `paula` | `sebastian`, `mateo`, `gabriel` |
| French | `fr` | `manon`, `juliette`, `lucie`, `elise`, `amelie` | `louis`, `nicolas`, `maxime`, `raphael` |
| Italian | `it` | `silvia`, `concetta`, `arianna` | `davide`, `luca`, `leonardo` |
| Portuguese (Brazilian) | `pt` | `juliana`, `leticia` | `gustavo`, `thiago`, `bruno` |
| Portuguese (European) | `pt` | `catarina` | `francisco` |
| Russian | `ru` | `anastasia`, `ekaterina`, `olga`, `irina` | `andrei`, `nikolai`, `maksim` |
| Greek | `el` | `katerina`, `dimitra`, `athina` | `dimitris`, `vasilis` |
| Finnish | `fi` | `aino`, `helmi`, `venla` | `mika`, `timo`, `matti` |
| Norwegian | `no` | `solveig`, `marit` | `kristian`, `espen` |
| Polish | `pl` | `ewa`, `joanna` | `tomasz`, `jakub` |
Need a voice not in this list? Use the standard [Lightning v3.1](/models/model-cards/text-to-speech/lightning-v-3-1) 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 |
See [Synthesize Speech](/models/api-reference/text-to-speech/synthesize-speech) for the full request/response schema, supported parameters, and error codes. To route to the Pro pool you must set `model` to `lightning_v3.1_pro` explicitly — the field is optional but defaults to standard Lightning v3.1.
#### [Quickstart](/models/documentation/text-to-speech-lightning/quickstart)
Generate your first audio in under a minute with a single API call.
***
## 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
* **`language: en`** → UK + American accented English. Pair with British or American Pro voices for best results.
* **`language: hi`** → Indian accented English + Hindi with native code-switching mid-utterance. Pair with Indian Pro voices.
* **Any additional Pro language** (e.g. `language: ta`, `language: de`, `language: ja`) → native synthesis in that language. Always pair with a Pro voice from that language's [Voice Catalog](#voice-catalog) section.
* **Omit `language`** → defaults to `en + hi`. Sensible when you don't know the input language ahead of time.
Per-voice metadata still lives in `tags.language` on the voice catalog (`GET /waves/v1/lightning-v3.1/get_voices`). The body parameter sets the *target* language for the synthesis pass; the voice ID controls the timbre and accent of the speaker.
### 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](/models/documentation/text-to-speech-lightning/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](/models/documentation/best-practices/tts-best-practices).
***
## Use Cases
| Direct Use | Downstream Use |
| -------------------------------------- | ---------------------------------- |
| Voice assistants and conversational AI | Multi-turn conversational agents |
| Interactive chatbots with voice output | Audio content generation pipelines |
| Real-time narration and live streaming | Telephony and IVR systems |
| Accessibility tools and screen readers | Podcast generation |
| Customer service automation | |
***
## FAQ
#### How is Lightning v3.1 Pro different from standard Lightning v3.1?
Pro runs on dedicated inference capacity, isolated from general Lightning traffic, and ships a curated premium voice catalog with improved naturalness. Concurrency, latency, and rate-limit ceilings are identical to standard [Lightning v3.1](/models/model-cards/text-to-speech/lightning-v-3-1) — the difference is voice quality and the catalog.
#### How do I route requests to the Pro pool?
Set `model` to `lightning_v3.1_pro` explicitly. The field is optional, but it defaults to standard Lightning v3.1 — for Pro you must pass it on every request.
#### Can I pair any voice with the Pro model?
Pair Pro voice IDs 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.
#### Does Lightning v3.1 Pro support voice cloning?
No. Voice cloning is not available on the Pro pool. Clones continue to use standard [Lightning v3.1](/models/model-cards/text-to-speech/lightning-v-3-1) and the existing voice-cloning flow.
#### Which languages does Lightning v3.1 Pro support?
Set `language: en` for UK + American accented English, or `language: hi` for Indian accented English + Hindi with native code-switching. Omitting `language` defaults to `en + hi`.
#### Are word-level timestamps supported on Pro voices?
Pro shares the Lightning v3.1 base-queue voices for English + Hindi (`meher`, `devansh`, `kartik`, `maithili`, `liam`, `avery`), so word events emit on those. Other Pro-only voices fall back to silent graceful degradation — audio is normal, but no word events are emitted.
***
## Safety & Compliance
### Known Limitations
* **No voice cloning.** Voice cloning is not available on the Pro pool. Clones continue to use standard [Lightning v3.1](/models/model-cards/text-to-speech/lightning-v-3-1) 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.
### Compliance
* No retention of synthesized audio
* Usage monitoring for policy compliance
For compliance documentation (GDPR, SOC2, HIPAA), contact [support@smallest.ai](mailto:support@smallest.ai).
***
## Support
#### [Support](mailto:support@smallest.ai)
#### [Console](https://app.smallest.ai/dashboard)
#### [Documentation](/models/documentation/text-to-speech-lightning/quickstart)