2026-10-11 17:12 UTC

Independent benchmarks will determine whether IBM’s released Granite Speech 5.0 Turbo CTC provides accurate, unusually fast fully local transcription on modest hardware.

state: expiredheat: lowuncertainty: highknownscott: mediumlocal-speech speech-to-text open-models local-inferenceIBM Granite

What is this?

IBM has released Granite Speech 5.0 470M Turbo CTC, a compact automatic-speech-recognition model that removes the earlier LLM backbone in favor of a smaller, non-autoregressive design. IBM reports throughput near 12,600× real time on a single H100 GPU—roughly twice the cited Hugging Face Open ASR leaderboard leaders—but the supplied material does not independently verify its accuracy, speed on modest local hardware, or practical feature trade-offs. The snippets are also thin on release details and primarily reflect IBM’s own testing, so independent hardware and word-error-rate benchmarks remain decisive.

Why it matters to Scott

The radar already tracks the same independent-validation question for fully local ASR in “audio.cpp 0.4 local speech validation” and “NeMo-Speech.cpp local stack.” Granite is nevertheless a concrete evaluation candidate for Scott’s local speech-engine laboratory, Whisper-based pipelines, and hardware-aware inference work; it becomes actionable only if modest-hardware benchmarks establish a useful speed–accuracy advantage beyond IBM’s H100 claims.
dev:project.audiodev:technology.whisperdev:concept.hardware-aware-local-inferenceip:concept.evaluation-driven-developmentip:concept.voice-accelerated-thinkingradar:audio-cpp-0-4-local-speech-validationradar:nemo-speech-cpp-local-stackradar:concept.speech-to-textradar:concept.local-inferenceradar:concept.model-evaluation
queries asked of Scott's wikis
  • local-first speech transcription architecture
  • on-device ASR latency and accuracy trade-offs
  • open speech models versus transcription APIs
  • local inference economics on modest hardware
  • speech-to-text pipelines for agent memory
  • benchmarking claims for non-autoregressive models

Measured heat

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How the heat travelled

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Evidence (2) — ⭐ canonical anchor

sourceobjectauthorscorecomments
🟠 redditGranite Speech 5.0 Turbo CTC: Extremely Fast and Accurate Transcription
LocalLLaMA
coder54314313
🟧 echo.blog ⭐IBM released Granite Speech 5.0 470M TurboCTC as a fast, accurate speech-transcription model.IBM Granite——

Interpretation history

Decision trace