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Home › Speech and audio AI
Use case

Speech and audio AI.

Whisper-large fits in 8GB VRAM. Real-time TTS and music models fit on consumer GPUs. Training novel models needs workstation-class hardware.

≥ 8GB VRAM Consumer tier
Best GPUs

Top GPUs for this workload.

Ranked by suitability — higher fitness scores mean the card handles this workload more comfortably.

GPU Tier VRAM Fit
Nvidia logo Nvidia GeForce RTX 4090
consumer 24GB 75 Compare →
Nvidia logo Nvidia GeForce RTX 4080
consumer 16GB 70 Compare →
Nvidia logo Nvidia L4
datacenter 24GB 60 Compare →
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Best AI models

Top models for this workload.

Whisper Large v3

2B
by OpenAI · Whisper · 30 ctx

OpenAI's open-weight speech-to-text — the standard transcription model.

Whisper Medium

1B
by OpenAI · Whisper · 30 ctx

769M Whisper variant — half the size of Large, 80% of the accuracy.

Whisper Small

0B
by OpenAI · Whisper · 30 ctx

244M Whisper — fits on edge GPUs and CPU.

GPT-4o

multimodal
by OpenAI · GPT · 128,000 ctx

OpenAI's multimodal model — text, vision, audio in one.

Whisper Base

0B
by OpenAI · Whisper · 30 ctx

74M Whisper — browser / Raspberry Pi-deployable.

Whisper Tiny

0B
by OpenAI · Whisper · 30 ctx

39M Whisper — runs in-browser via WebGPU.

Claude Haiku 4.5

text
by Anthropic · Claude · 200,000 ctx

Fast, cheap Claude variant for high-throughput inference.

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