tensorfold

Imagination Studio by keys+Wasserman powered by TensorFold: an AI film studio for Mac and NVIDIA DGX Spark. Plan a film like a crew (Slate workflow by Sam Wasserman), render Qwen-Image-2.1 / FLUX3-K pictures and MiniMax H3 / FastH3 video with sound on TensorFold.

DeepSeek-V4.1-Flash-1017 EXL3 2.9bpw on 2x NVIDIA DGX Spark (GB10) with TensorFold: 2.1-2.3x the vLLM kit's decode speed.

Imagination Studio by Keys (x.com/u1tra_instinct) + Sam Wasserman / Wasserman Productions (wassermanproductions.com · x.com/SamJWasserman), powered by TensorFold: a local all-in-one AI film studio for NVIDIA DGX Spark and Apple silicon, with Wasserman's Filmmaker Suite built in.

GLM-5.3-Flash BIZ for DGX Spark-class GB10 systems. 3.x serves the XSFP4 checkpoint or NVIDIA's pinned NVFP4 one with TensorFold's native Zig/CUDA engine (TP=2 or TP=3, MTP drafts equal serial, tool calls, structured output, images, video). Apache-2.0 code, weights fetched separately. BIZ = business-use intent, not support or certification.

DeepSeek V4.1 Flash 1017 EXL3 on 3 DGX Sparks. TensorFold 1.2.5: exact production K2a, adaptive speculation, prefix-state cleanup and vision control. Stock SparkDash: 246.2 tok/s C12 code aggregate, thinking OFF. Full recipes, tests and evidence.

MiniMax H3 audio-video model on TensorFold NVFP4 kernels: a faster ComfyUI loader for one RTX 50-series GPU (2.3x stock at 20 steps, 81 s per 5 s 1344x768 video with Turbo + sparse attention on an RTX 5070 Ti)

GLM-5.3-Flash EXL3 on 4x RTX PRO 6000 with TensorFold: one-command recipe and engine patches. By Aevonix Research in collaboration with Mia's AI Lab.

Qwen3.8-Flash-Next EXL3 3.05bpw on ONE DGX Spark (GB10): ~2.4x prefill (700->1777 t/s), prompt-lookup drafter, native vision/video, 262k ctx. Unofficial TensorFold v0.6.5 fork, 18 patches, byte-exact receipts.

DeepSeek-V4.1-Flash-1017 on two NVIDIA DGX Sparks (GB10) with TensorFold TP2: scripts, chat-template fix, speed and quality results

DeepSeek Flash on 1-2 NVIDIA DGX Sparks, measured honestly: DeepSeek-V4.1-Flash-1017 on TensorFold TP2 (91.5 tok/s C1, 98% quality, 1M context), V4-Flash-0731 certified numbers, the laws, the harness, every CSV

GLM-5.3-Flash EXL3 on 2x RTX PRO 6000 with TensorFold: one-command recipe and engine patches. By Aevonix Research in collaboration with Mia's AI Lab.

GLM-5.3 EXL3 on 4x RTX PRO 6000 with TensorFold: one-command recipe and engine patches. By Aevonix Research in collaboration with Mia's AI Lab.

ThinkingCap Kearuga EXL3: TandemLLM-first DGX Spark serving, independent RTX 5090 receipts and a retained TensorFold reproduction recipe.

Kolibri-1 (Aleph Alpha) on two NVIDIA DGX Sparks with TensorFold: ~2x decode tok/s vs one Spark. Recipe, patches, measured results.

Keep every AI model on a NAS; insert any of them on your GPU box with one click (Ollama / vLLM) — never evicts a model you didn't name. Stdlib Python, demo mode, web UI.

TensorFold deployment for GLM-5.3-Flash on 4x NVIDIA CMP 170HX (GA100 sm_80): bit-exact 4-rank TP, shm all-gather, W4A16 affine - complete tested solution (199.4 tok/s structured, exactness maintained)

DeepSeek-V4.1-Flash-1017 on native TensorFold, 2x DGX Spark (TP=2): prose 55 / code 104 tok/s at 1 stream, 135 / 203 at 8, 0.2 s first token · text, images, video · EXL3 2.9 bpw

Qwen3.8 Flash Next on one NVIDIA Jetson AGX Thor with TensorFold: recipe, gated benchmarks, and a head-to-head with a DGX Spark

DeepSeek-V4.1-Flash-1017 on one 256 GB M5 Ultra: 1M context, 70.7-104.9 tok/s decode with DSpark drafts, 1,739-1,867 tok/s cold prompts (8k-131k) with int8 x int8 prompt experts, a 1M prompt in 740 s, images, tools, JSON. TensorFold native Metal.

Four DGX Spark switchless TensorFold TP4 deployment for GLM-5.3-Flash EXL3, with ring exchange and measured benchmarks