THE BEAST IS ALIVE
Benchmarking the BIM TerraNode 256: 8x NVIDIA V100 32GB (256 GB VRAM), 256 GB RAM, 4x 2 TB in RAID 10. Results will follow.
Get yours now: bim-computing.com/products/8…
Local abliterated AI is the solution: your own hardware keeps the weights and removes the provider refusal list.
bim-computing.com
10 UNCENSORED AI MODELS YOU CAN RUN WITH 16GB VRAM
Qwen3.8 27B Abliterated huggingface.co/huihui-ai/Hui…
Gemma 4 12B Uncensored huggingface.co/models?search…
Ornith 1.5 9B Uncensored
huggingface.co/models?search…
Qwen3.5 9B Uncensored
huggingface.co/localgstar/Qw…
Dolphin Mistral 24B
huggingface.co/models?search…
LFM2.5 24B A2B Uncensored
huggingface.co/OS-Software/L…
Qwen3 VL 8B Abliterated
huggingface.co/models?search…
Mistral NeMo 12B Abliterated huggingface.co/models?search…
GPT-OSS 20B Heretic huggingface.co/models?search…)
Llama 3 8B Abliterated huggingface.co/models?search…
use GGUF quantized versions to run locally
check VRAM requirements before downloading
bookmark for later use
Local abliterated AI is the solution: your own GPU, your own weights, no remote refusal list.
bim-computing.com
RTX 3080 unlocked, on the 35B MoE model we serve. Prompt tokens/s:
4.4k: 2,366 stock → 3,057 unlocked + Marlin FP4 kernel
32k: 2,457 → 5,273 with Marlin
FP16 math, FP32 accumulate: 64 → 116 TFLOPS
Same answers. Output at 4.4k: 50 → 41 tok/s.
bim-computing.com
Local abliterated AI is the solution: run uncensored models on hardware you control, bypassing server-side restrictions.
bim-computing.com
Anthropic decides what you're allowed to build now.
On Oct 27th it pushed a new rule to Claude Code from its servers, with no update for you to install and no setting to turn it off.
Anthropic now tells Claude not to recreate a specific existing game, even if you rename it.
If Anthropic can do this to games, it can do it to whatever you're building.
AI companies now decide what you can think and do. In R&D or business, you can't keep proving to an AI your work is legitimate.
Abliterated DeepSeek V4.1 Flash 1017: 45 on the Intelligence Index, close to Opus 5 (51).
The future of AI freedom is local.
bim-computing.com
Tried FreeToken from UC Berkeley on an old RTX 3080 10GB + DDR4. Qwen3.6-35B-A3B (MoE) runs at 68 tokens/s with the full 262K context. Same model in llama.cpp: 34 tok/s. A dense 27B offloaded to RAM: 2.9 tok/s. With MoE, RAM offload finally works.
Code here: github.com/FlashML-org/FreeT…
Modded RTX 3080 20G ➡️ 799€ DDP
bim-computing.com
BIM Computing retweeted
That's probably why we got strange requests from banks with @BIM_Computing
We do trading of modded GPUs from China, they asked us to perform KYC on our customers (wtf why need KYC to buy a graphic card?) and eventually @vividmoney_fr froze our customers' funds.
Vivid: a scam?
@vividmoney_fr froze €47,635 of funds our customers paid us. Account closed "for cause" on 30/09, no reason given. Hold: "3 months" in their notice, "28 days" per support, release "not automatic".
Formal notice sent. @vivid_en @dgccrf
#fintech #neobank
Qwen3.8-27B Q4_K_M (15.6 GB weights) — decode tok/s vs price.
11 configurations: VRAM, memory bandwidth, four context/KV combinations, and whether 256k fits.
Highlighted: Tesla V100 32GB, Tesla P100 16GB, RTX 2080 Ti 22GB.
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