Descriptions:
Fahd Mirza puts MesoTTS 8B — a new open-weights text-to-speech model built on the Sesame CSM architecture — through a hands-on installation and inference test on an Ubuntu system with a single Nvidia RTX A6000 (48GB VRAM). The model uses a dual-transformer design: a large Llama 8B backbone processes text and audio frame embeddings, paired with a 300-million parameter autoregressive decoder that predicts higher-order audio codecs across 32 codebooks. The full model download weighs 32.8GB.
The video documents the complete setup process, including cloning the repo, installing prerequisites, and running the default inference script — which generates a multi-turn conversational exchange between two speakers, feeding each completed audio segment back as context to maintain voice consistency across turns. In practice, VRAM consumption climbs from ~32GB during model loading to nearly the full 48GB during inference, and the initial run crashed with an out-of-memory error before Mirza upgraded GPU capacity to complete it.
Audio results are mixed but genuinely interesting. The model produces clearly emotive speech — a romantic parting scene, a casual phone conversation, and an emotionally charged dialogue all carry audible prosody variation that flat TTS systems lack. However, Mirza identifies some naturalness issues in certain passages where emotions feel slightly rushed or mechanical. For developers evaluating expressive open-weights TTS models, this video provides an honest assessment of both MesoTTS 8B’s emotional range and the substantial hardware requirements needed to run it locally.
📺 Source: Fahd Mirza · Published June 05, 2026
🏷️ Format: Review
