Models
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GPUBox tells you exactly which model serves your request. No opaque endpoints, no silent swaps, no "mystery model" pricing. You name the model in your code; we serve that model.
Chat / LLM
liveApache 2.0AWQ-int4qwen2.5-32b-instruct
Qwen2.5-32B-Instruct from Alibaba — strong general-purpose LLM at the 32B parameter class. Reliable function calling, decent reasoning, fast on consumer-grade hardware via 4-bit quantisation.
Context
8,192 tokens
Hardware
RTX 5090
Endpoint
/v1/chat/completions
Capabilities
- Chat completions (OpenAI-compatible)
- Streaming SSE
- Tool / function calling
- JSON mode (response_format)
- Multilingual: English, Chinese, Spanish, French, German, etc.
Speech-to-text
liveMITfp16whisper-large-v3-turbo
OpenAI's Whisper large-v3-turbo via faster-whisper. Real-time-factor ~0.3 on the 5090: a 60-second clip transcribes in roughly 18 seconds.
Context
30 second windows
Hardware
RTX 5090
Endpoint
/v1/audio/transcriptions
Capabilities
- OpenAI-compatible /v1/audio/transcriptions
- Multipart upload (file + model + optional language/prompt/temperature)
- 100+ languages with auto-detection
- verbose_json response with segment-level timestamps and confidence
- Voice-activity detection (VAD) filter
Embeddings
liveMITfp16bge-m3
BAAI BGE-M3 — strong multilingual embeddings, 8k context. Returns L2-normalised 1024-d dense vectors via the OpenAI embeddings shape.
Context
8,192 tokens
Hardware
Ryzen 9 9950X (CPU)
Endpoint
/v1/embeddings
Capabilities
- OpenAI-compatible /v1/embeddings
- Multilingual (100+ languages)
- 1,024-dimensional dense vectors
- L2-normalised by default
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