> 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. # Accuracy > Lightning text-to-speech pronunciation accuracy measured by transcribing the output with Whisper: jiwer word error rate and an LLM-judged score. ## Accuracy Mixed direction - WER, CER, Hallucination, and Deletion are *lower is better*; Pronunciation % is *higher is better*. ### Whisper jiwer | Metric | Direction | Lightning v3.1 | 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 | 1.57% | 1.36% | 1.26% | 1.35% | 1.33% | 1.43% | 1.26% | 1.37% | 1.25% | 1.10% | 2.83% | | CER | lower | 0.67% | **0.40%** | 0.52% | 0.60% | 0.54% | 0.59% | 0.62% | 0.61% | 0.50% | 0.47% | 1.16% | | Hallucination | lower | 0.03% | **0.00%** | 0.07% | 0.08% | 0.01% | 0.06% | 0.04% | 0.01% | 0.06% | 0.00% | 0.22% | | Deletion | lower | NA | **0.00%** | 0.14% | 0.17% | 0.18% | 0.16% | 0.24% | 0.18% | 0.15% | 0.12% | 0.33% | | Pronunciation % Whisper jiwer | higher | 98.61% | 98.68% | 98.94% | 98.90% | 98.87% | 98.79% | 99.02% | 98.82% | 98.95% | 99.02% | 97.72% | ### Whisper LLM (Pro evaluation only) LLM-judged Whisper transcripts, applied during the Pro benchmark run. The follow-on LLM normalizes punctuation, casing, and Whisper's own transcription noise - typically reducing false-positive errors compared to `jiwer`. Standard Lightning v3.1 was not evaluated with this methodology. | 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. > **Note** > > For Pronunciation and WER, the residual gap on Lightning v3.1 (Standard) is concentrated in proper-noun rendering. Use a [pronunciation dictionary](/models/text-to-speech/pronunciation-dictionaries) to pin names, brands, and acronyms; with the dictionary applied, both metrics close to parity. > Pronunciation accuracy measured with Whisper jiwer and Whisper LLM.