Hopper
ChatGPT pluginThe latest open-source models
Hopper is a realtime inference API for open-source models: two LLMs, text-to-speech and speech-to-text, behind a standard chat-completions API. Try the latest open-source models on your own work: in a chat, Hopper runs your prompt or examples on both LLMs side by side and returns each answer with time to first token, tokens per second, token counts and cost, so you can judge the models on your task. It also speaks text with an inline audio player, transcribes recordings you attach (WAV, MP3, M4A, Ogg, FLAC or WebM) with word timestamps, lists models and prices, and returns tested client code for popular SDKs and agent frameworks. After you sign in with your Hopper account, it shows your usage and creates API keys: the key opens once in the Hopper console, with a ready snippet for your code. Where it can run commands in your project, the plugin also finds the prompts your app sends and tests them on both models, and after you say go it points your project's chat-completions client at a Hopper model, changing only the client. Text and audio you send go to Hopper's API; see withhopper.com/privacy.
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5 listing changes logged · latest Oct 24: Description, Skills, Keywords and 2 more. See what changed
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Developer tools581st of 742 by placement
| # | Plugin | Position | 7d |
|---|---|---|---|
| 579 | #6433 | 43places up | |
| 580 | #6441 | 19places down | |
| 581 | #6451 | 21places up | |
| 582 | #6455 | 16places up | |
| 583 | #6466 | 24places up |
Example prompts
- “Try the latest open-source LLM on a prompt from my app”
- “Compare Hopper's two LLMs on this prompt”
- “Read this aloud in a natural voice”
Skills
hopper-integrate
Points a project's LLM calls at a Hopper model (DeepSeek V4.1 Flash or Gemma 4 31B) through Hopper's OpenAI-compatible API: OpenAI SDK (Python or JavaScript), LangChain, Vercel AI SDK, LiteLLM, raw HTTP, LiveKit Agents, Pipecat or Vapi. Gets the project a key, shows the planned change (and, for a voice agent, time to first token on its own prompt), and edits code only after the user says go. Use when the user says "switch this app to DeepSeek on Hopper", "swap the LLM for Gemma 4", "move our OpenAI calls to Hopper", "point base_url at Hopper", "set up Hopper in this project", "add a Hopper API key to this repo" or "go ahead" after a hopper-try comparison. Not for trying or comparing models before deciding (hopper-try), speech or transcription (hopper-speak, hopper-transcribe), or running models locally.
hopper-speak
Turn text into speech with Hopper text-to-speech (Qwen 3 TTS): play it aloud, save a WAV file, or preview and pick a voice. Needs no setup: the first use registers a key for the agent itself. Use when the user says "read this aloud", "say this out loud", "generate a voiceover", "voiceover for my launch video", "audio for my launch video", "narrate this script", "narration for my demo video", "make a podcast intro", "record an announcement", "voice for my ad", "make an audio file of…", "text to speech", "TTS" or "which voice should I use". Makes the speech track only, not video, music or sound effects. Not for writing a script (plain text), transcribing audio (hopper-transcribe) or running an LLM (hopper-try).
hopper-transcribe
Transcribe speech in an audio or video file with Hopper speech-to-text (Nemotron ASR), with word timestamps. Takes WAV, MP3, M4A, voice memos and video such as MP4 or MOV (decoded with ffmpeg). Needs no setup: the first use registers a key for the agent itself. Use when the user says "transcribe this", "what does this recording say", "check my video", "what's said in this video", "review the voiceover in my launch video", "captions for my video", "subtitles", "caption this", "meeting notes from this recording", "summarize this call", "pull quotes from this interview", "speech to text" or "STT". Works from the spoken words only, not the visuals. Not for generating audio (hopper-speak) or running an LLM (hopper-try).
hopper-try
Tests DeepSeek V4.1 Flash and Gemma 4 31B on the user's own prompts: finds real prompts in the project or chat, runs both side by side with time to first token, tokens per second and cost, and gives a verdict per example. Changes no code. Use when asked "there's a new DeepSeek model, how is it? test it for my use case", "DeepSeek V4.1 Flash any good? try it on my prompts", "is Gemma 4 worth trying for this", "give the new DeepSeek a vibe check", "try this prompt on a few open models", "run our real prompts through DeepSeek", "gemma 4 vs deepseek for this, which one?", "could an open model replace GPT-4.1 here", "is DeepSeek a drop-in replacement for OpenAI here", "worth switching to an open model?", "does DeepSeek handle our function calls reliably", "check if Gemma returns valid JSON for our schema" or "try Hopper". Not for testing their code, comparing files, writing prompts, running models locally (Ollama), fine-tuning or published benchmark scores; to switch the project's model, use hopper-integrate.
- Categories
- Sign-in
- On Install
- Capabilities
- Interactive, Read, Write
- Availability
- Available
- Version
- 1.3.0
- Keywords
- llm, inference, open-source models, api, agents, model comparison, text to speech, speech to text, tts, stt, transcription, open-source llm, latest open-source models, chat completions api
- Created
- October 2, 2026
- More info
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