The frontier is open-source today
6 hours ago
- #Open-Source Models
- #Transcription Tool
- #AI Benchmark
- GLM-5.2 outperformed Opus 4.8 on an AI-resistant take-home test, delivering higher-quality transcriptions, better speaker identification, closer instruction-following, and more maintainable code.
- offmute-v2 combines insights from previous projects into a multi-step pipeline using a regular STT model and a multimodal LLM to produce accurate, diarized, timestamp-correct transcripts with identified speakers.
- The tool is extensible, runs in the browser, and allows for customization, such as fixing common misspellings or focusing on conversations in noisy environments.
- GLM's version, offmute-v2@glm, is now the primary version, with Opus's version preserved as offmute-v2@opus. Opus's best ideas are being integrated into the GLM version.
- Both models faced issues: GLM had a silent bug serving cached transcripts, while Opus crashed on audio-only files and had spec-implementation drift.
- Despite Opus posting a better raw WER (Word Error Rate), the difference narrowed after fixing GLM's deduplication bug. WER is not the sole metric, as output quality, speaker matching, and maintainability are more important.
- This marks a significant milestone where an open-source model (GLM) outperformed a frontier model (Opus) across multiple axes, offering cost-effectiveness, open weights, and competitive intelligence.
- The advancement in open-source models like GLM-5.2 enables new possibilities for secure, reliable data use at scale, with potential for more accessible pretraining and tuning in the future.