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Chat across multiple AI models

Switch models per conversation, compare providers, and pair answers with voice workflows.

Why multiple models

Different families excel at different tasks: some are extremely fast for brainstorming, others are stronger at long-context reasoning or multilingual answers. WebVoice lets you pick from the catalogue enabled by your administrator — typically including high-throughput hosts (such as Groq-accelerated stacks), frontier assistants from providers like Moonshot (Kimi), MiniMax, and other ChatAIModel entries configured in the control plane.

You can start a thread with one model, open another thread with a different model, or change the default for new conversations so teams can standardise on a safeguard-oriented profile for customer-facing replies and a lighter model for internal drafts.

Providers and defaults

Each row in the model list shows display name, provider, and credits per request where applicable. Groq-backed options often cost fewer credits per turn while maintaining low latency; other providers may charge more per message but add capabilities (longer memory windows, specific tool formats, etc.). Superusers curate which model IDs are visible so obsolete endpoints disappear without client updates.

Optional chat tones and agent personas (when enabled) layer system instructions on top of the base model, so the same backbone can sound formal, concise, or educational without swapping weights.

Together with voice

Chat is not isolated: you can move from transcription to summarisation, then send polished text to TTS, or attach voice memos alongside written prompts. Credits for chat, TTS, and STT share one wallet, which simplifies budgeting for mixed-media projects.

Summary

  • Selectable models from an admin-curated catalogue (Groq, Moonshot, MiniMax, …)
  • Per-request credits shown before you send
  • Multiple parallel threads with different models
  • Works alongside TTS/STT and API-based automation

Trusted for production voice workloads

Inside the product — app screenshots, workflow, and reserved logo slots on the main site.

Product teams, agencies, and developers use WebVoice for TTS, STT, chat, and API-first integrations — from prototypes to customer-facing apps.

SaaS & product
Agencies
Education
Internal tools
50K+

Hours of audio synthesized & transcribed monthly (illustrative range)

30+

Neural voices and locales in the catalogue (varies by deployment)

REST

Same credit wallet for browser app and documented HTTP API

Figures are indicative and depend on traffic and configuration.

“We shipped read-aloud and STT in one sprint — the API matched what we tested in the UI.”

“Credits per feature make finance happy — we can forecast TTS vs chat separately.”

“Low-latency Groq routes for chat let us keep UX snappy without a separate vendor.”

Quotes represent typical feedback patterns; not attributed to specific customers.

Frequently asked questions

Yes — open multiple threads and assign a model to each, so you can compare answers or separate internal vs external-facing work.

Each completion debits the model’s listed credits per request. Picking a different model changes the debit for that thread.

Yes — credits share one wallet, so you can transcribe, summarise, then send polished text to speech in one account.

When enabled, optional tones layer system instructions on the base model without swapping weights.

Latency is often lower; pricing still follows the per-model credit shown in the picker.

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Get Started API documentation