AnalysisTutorial / explainerEfficiency & Inference · Hardware & Compute · Large Language Models1 source · Oct 11, 2026

Running Next Flash IQ3_XXS at ~70 tok/s with 100k context or 2 instances of Qwen 3.6 35B A3B IQ4 at ~145 tok/s with 256k all on $500 of ex mining BC-250 boards

This will be my third update on the bc-250 cluster and for my first forray into local ai I have been having a blast.

Proof1 community thread

Key points

  • I am running 4 BC-250 boards connected by 2.5gb ethernet adapters to a 2.5gb switch using llama with vulkan and RPC.
  • After starting out at 30 tok/s on flash next Iq2 and 80 tok/s with 3.6 35B I pointed Claude Code at the cluster and we are now running a better quant next flash as well as maintaining 60-70 tok/s (~150 ppt) at context.
  • The 4 boards can run 2 instances of 3.6 35B at 145tok/s (~450 ppt) starting and going below 100 tok/s at 150k context.
  • The next step for me is to use AIO coolers for each board as now I have been seeing some thermal throttling as the boards are better utilized .

Sources (1)

Extractive summary: sentences quoted from the sources.

Before this

  1. Oct 10, 2026Benefits of using bigger models than Qwen 3.8 flash next?
  2. Oct 10, 202648Gb VRAM speed AND quality ! (Qwen 3.8 27B Swift 1.5 W8A16)
  3. Oct 10, 2026Qwen3.8-27B on a single 3090: 140 tok/s on code with a custom megakernel
  4. Oct 10, 2026Strata with Qwen3.8 Flash Next UD-Q4_K_XL
  5. Oct 9, 2026anthropics/claude-code v2.1.296
  6. Oct 8, 2026anthropics/claude-code v2.1.295

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