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Schedules Are Solvable Symbols: Tuning-Free Compilation of Tile Programs on Dataflow Architectures

Lobsters Hottest ↗ · 2026-10-02 Cached

A paper from NUS introducing Loom, a tuning-free symbolic compiler framework that formulates tile-based SPMD compilation as CP-SAT optimization over symbolic schedules, matching or exceeding vendor-optimized TTNN library performance on Tenstorrent Wormhole and Blackhole for GEMM, Flash Attention, and Flash Decode without per-shape profiling.

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Tenstorrent Qwen3.7-27b Benchmarks

Reddit r/LocalLLaMA ↗ · 2026-08-29

The author shares benchmarks for the Tenstorrent QuietBox 2 with P300c cards running the Qwen3.7-27b AI model, detailing hardware specifications and the absence of MTP support.

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Tenstorrent Quietbox 2 Arrived!

Reddit r/LocalLLaMA ↗ · 2026-08-29

Tenstorrent has released the Quietbox 2, a high-performance system with 256GB memory and 128GB interconnected GDDR, designed for AI development with impressive scalability and interconnect features.

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@tenstorrent: Thank you Tokyo! Here’s everything we announced at TT-Deploy Japan: Faster AI Inference • Kimi K2.6 900 t/s/u, 3x faste…

X AI KOLs Timeline ↗ · 2026-07-02 Cached

Tenstorrent announced at TT-Deploy Japan faster AI inference for Kimi K2.6, LTX 2.3, and DeepSeek-R1 on their hardware, plus the licensable TT-Ascalon S RISC-V CPU for agentic AI.

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Qualcomm wants to grow in the AI space (multiple acquisition's underway)

Reddit r/singularity ↗ · 2026-06-24

Qualcomm is aggressively expanding in AI through multiple acquisitions, including Modular (creator of Mojo and MAX inference framework) and potentially Tenstorrent, signaling a significant push against Nvidia's CUDA ecosystem.

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@TheAhmadOsman: Local AI hardware = capacity × bandwidth × software stack - Capacity tells you what fits - Bandwidth tells you how hard…

X AI KOLs Following ↗ · 2026-06-21 Cached

A detailed comparison of local AI hardware in terms of memory capacity, bandwidth, and software stack, covering GPUs, Apple Silicon, AMD, Intel, Tenstorrent, and others, with a focus on what bottlenecks matter for AI inference.

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@steeve: Progress: 26 tok/s (llama 3.1 3b) .@tenstorrent claims 33 tok/s so we’re not far off

X AI KOLs Following ↗ · 2026-05-22 Cached

Steeve Morin reports running Llama 3.1 3B on Tenstorrent hardware via ZML, achieving 26 tok/s, close to Tenstorrent's claimed 33 tok/s.

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