![[Free] How to Clear the EPSON EP-804A Waste Ink Pad Error with the Open-Source EWR Tool](https://miyagadget.page/wp-content/uploads/2026/09/hero-ep804a-waste-ink-error-640x360.jpg)
[Free] How to Clear the EPSON EP-804A Waste Ink Pad Error with the Open-Source EWR Tool
I cleared the waste ink pad error on an EPSON EP-804A for free with the open-source EWR tool: the startup-crash fix, a dry run, an EEPROM backup, and real logs.
Author: Shichinomiya
Dual Tesla V100 SXM2 on a Single PCIe Slot: 64GB VRAM & 300 GB/s NVLink Tested — Is This $700 Setup Worth It?
In-depth technical analysis of the 39com Dual Tesla V100 SXM2 NVLink adapter board. 64GB HBM2 and 300 GB/s NVLink on a single PCIe slot via PLX switch. Cooling mods, 1Cat-vLLM benchmarks, and complete build guide.
Modded RTX 4080 32GB Benchmarked: Qwen3.8-27B at 262K Context, 125B MoE, and MiniMax H3 Video — What 32GB Actually Delivers
In-depth testing of a modded RTX 4080 32GB from China: Qwen3.8-27B Q8_0 fits fully in VRAM at 22.47 tok/s, while the native 262,144-token context runs in 26,240 MiB with q8_0 KV cache. Generation matches the Tesla V100 32GB, but prefill is 2.4–3.2x faster. Also covers running the 125B Qwen3.8-Flash-Next MoE offloaded to system RAM, MiniMax H3 video generation, and simulated 16GB/24GB limits.
Tesla V100 32GB Runs Qwen3.8-27B: 131k Context on a Single Card — Measured Benchmark
Benchmarking Qwen3.8-27B on a 2017 Tesla V100 32GB. 33.41 tok/s on Q4_K_XL, and a 131,072-token context fits in 25,264 MiB on one card. Plus the KV-quantization CPU fallback and why --reasoning-budget 1024 decides whether it is practical.
Tesla V100 32GB in 2026: Local LLM Benchmark with Qwen 3.6 — 98.8 tok/s on MoE 35B, 1.6x Faster Than M1 Max (Used, ≈$900)
We benchmark Qwen 3.6 on a used Tesla V100 32GB (~$900): 98.8 tok/s on MoE 35B, great value, but prebuilt llama.cpp dropped Volta - build from source.
Darkbloom Review: Can a Mac Really Earn Money Serving AI? (I Tested It for a Day)
I ran Darkbloom, which pays you to serve AI inference on an Apple Silicon Mac, for a full day. The calculator promised $75/month, but I actually earned $0.60/day. Here's the honest profit-and-loss with GPU logs and measured power.
Can you really cut your AI API bill? I deployed the context-compression tool “Headroom” and measured it
Hi, this is Shichinomiya-san (@shichinomiya_s). When you use AI agents like Claude Code or Cursor, one thing quietly adds up: token cost. Every time you have them read logs, return huge JSON, or ingest whole files, the context balloons and…
Does the trending Claude Code skill “ADHD” actually make the agent smarter? A measured duel vs single-shot
Hi, this is Shichinomiya-san (@shichinomiya_s). Last time I measured Headroom, which claims “95% token reduction”. This time I tested ADHD, another fast-rising project on GitHub (700+ stars in ~9 days, featured by The New Stack) — a skill for Claude…
Qwen 3.6 on a Mac, Measured: on an M1 Max 64GB, the MoE 35B ran 3.7x faster than the 27B
Hi, this is Shichinomiya-san (@shichinomiya_s). Last time I tested how far you can push Qwen as a local LLM on a GTX 1080Ti. This time I ran the new Qwen 3.6 on an Apple M1 Max (64GB unified memory) and…
Can GTX 1080 Ti Run Modern AI? Qwen 3.5 Local LLM Benchmark Results
Hello, this is Shichinomiya (@shichinomiya_s). This time, I ran a full benchmark to see how far the latest local LLM “Qwen 3.5 9B” (released in 2026) can go on the legendary 2017 GPU: the NVIDIA GeForce GTX 1080 Ti. If…