Build voice & avatar systems
Speech synthesis, avatar video, and lip sync for assistants, characters, and synthetic media products.
Character stack.Speak, present, sync
Inworld Realtime TTS-2
Conversational text-to-speech with realtime voice direction and audio-aware delivery
Inworld Realtime TTS-2, conversational speech with realtime voice direction, session-aware tone and pacing, and one voice identity across 100+ languages. Read guide
Tradeoff. $0.035 per 1,000 input characters. Conversation-first; for bracket-cue emotion control and multi-speaker dialogue see Fish Audio S2.1 Pro.
HeyGen Avatar V
High-fidelity avatar video generation with stronger identity consistency and lip sync
OmniHuman-1.5
Cognitive avatar video from image, audio, and text
lipsync-2-pro
High-resolution diffusion-based lip-sync editing up to 4K
Common questions
Speak — Inworld Realtime TTS-2; Present — HeyGen Avatar V; Animate — OmniHuman-1.5; Sync — KlingAI Lip-Sync; Finish — lipsync-2-pro. Each row above expands with the model's live pricing, capability chips, and sample outputs.
Tradeoffs to consider
HeyGen Avatar V runs $0.1 per second while OmniHuman-1.5 works out to roughly $0.13 per second ($1.3247 per 10 seconds) for higher-fidelity, single-image-driven video. The cost gap is modest — the real difference is input and fidelity: realtime assistants tolerate less fidelity than hero marketing content.
KlingAI Lip-Sync charges $0.0462 up to 5 seconds and $0.0924 up to 10, then $0.0092 per extra second; sync lipsync-2-pro is a flat $0.0733 per second at up to 4K. Short clips favour the banded model, long 4K post favours flat per-second pricing only when the detail is visible.
Production notes
Every price on this page is the model's published rate from the live Runware catalog, using the cheapest listed configuration unless stated otherwise. Prices vary with resolution, duration, quality tier, or token volume, so check the pricing table on each model page before estimating unit economics.
The Runware catalog does not publish per-model latency figures, so this page does not quote end-to-end timings. Where a model's own description commits to speed (for example sub-second generation or realtime streaming), that claim is repeated here. For anything else, benchmark the exact models in the Playground with your own payload sizes before committing to an SLA.
Models are addressed by versioned AIR identifiers, so a workflow pinned to specific model versions keeps producing the same behaviour as new versions ship. Adopt upgrades deliberately by re-running your evaluation set against the new version before switching production traffic.
About this collection
A blueprint bundles the small set of models you would actually wire together for one production use case, instead of ranking a whole category. Each pick covers one stage of the workflow and links to its model page for full schema, pricing, and examples.
Picks are live models from the Best Text-to-Speech (23 live models), Best AI Avatar Generators (10), and Best Lip Sync (22) collections, covering the speech, avatar video, and lip-sync stages at two fidelity tiers each where the catalog supports it.
Model guides.Learn how to use the stack
Formatting LLM output for speech
How to write LLM system prompts that produce text TTS-2 can synthesize naturally, with normalization, filler words, and emphasis cues handled before the audio call.
Read the guide →Controlling voice delivery with steering tags
How to use natural-language steering tags to control emotion, pacing, volume, and vocal style in TTS-2 speech output.
Read the guide →Backgrounds, framing, and aspect ratios
How to compose what surrounds the avatar in Avatar V output: the background, fit mode, aspect ratio for the target platform, and burned-in captions.
Read the guide →Driving the avatar: text to speech or your own audio
How to choose between Avatar V's two input modes: generate the voice from a script, or drive the avatar with your own recorded audio.
Read the guide →