MiaAI-Lab / DeepSeek-v4.1-Flash-1017-2x-DGX-Sparks
DeepSeek-V4.1-Flash-1017 EXL3 on 2x DGX Sparks with TensorFold
MiaAI-Lab / DeepSeek-v4.1-Flash-1017-2x-DGX-Sparks
Elevatormusic / DeepSeek-V4.1-Flash-1017-EXL3-TensorFold-2x-DGX-Spark
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.
MiaAI-Lab / GLM-5.3-Flash-EXL3-2x-DGX-Sparks
GLM-5.3 Flash EXL3 for 2-4x DGX Sparks
MiaAI-Lab / GLM-5.3-Flash-EXL3-2x-DGX-Sparks-TensorFold
GLM-5.3-Flash EXL3 on 2x DGX Spark with TensorFold
MiaAI-Lab / DeepSeek-v4-Flash-One-DGX-Spark
DeepSeek v4 Flash EXL3 on one DGX Spark
sybil-solutions / glm-flash-lite
GLM-5.3-Flash EXL3 on one 24 GB RTX 3090 + DDR4: elastic GPU expert cache, zero-copy experts, AVX2 CPU tier, OpenAI API
beamivalice / sushi
Sushi engine runs very high quality quant model in Apple Silicon, using hybrid affine/exl3 with special expert tuning techniques.
MiaAI-Lab / DeepSeek-v4.1-Flash-EXL3-2x-DGX-Sparks
DeepSeek v4.1 Flash EXL3 2.9 bpw for 2x DGX Sparks
MiaAI-Lab / Qwen3.8-27B-DFlash2-EXL3-5.0bpw
Deployment kit: Qwen3.8-27B EXL3 3.5bpw target + DFlash2 EXL3 5.0bpw speculative draft — launcher, config, model cards
Yamz-Labs / kyojin
Kyojin: the Yamz inference engine for AMD Strix Halo (ROCm, gfx1151), built on ExLlamaV3. Runs 300B-class MoE models on one 128 GB mini PC.
0xSero / deepseek-v4-flash-0731-spark-sparkinfer
Pinned one-DGX-Spark Docker recipe for DeepSeek V4 Flash with EXL3, SparkInfer, and 262K NVFP4 MLA KV cache
sybil-solutions / dsv41-flash-offload
DeepSeek-V4.1-Flash EXL3 on one 24 GB RTX 3090 + DDR4 + NVMe: staged-DMA prefill, AVX2 CPU expert tier, elastic VRAM expert cache, Engram on disk, OpenAI API
jayleaton / glm53-tensorfold-spark
GLM-5.3-Flash (abliterated EXL3) on 2x NVIDIA DGX Spark with the TensorFold engine: 1.8x faster decode than vLLM, 4x256k concurrent threads, byte-exact speculative decoding. Work in progress.
0xSero / DeepSeek-V4.1-Flash-Two-Sparks
DeepSeek-V4.1-Flash on two DGX Sparks: EXL3 routed experts, 262k context, 2M-token KV, vision, tools, MTP, bundled with Pi
Enntity / sparkglm
Fast, capable GLM-5.3-Flash FP4-Local on two DGX Sparks: opinionated Atlas serving and reproducible inference research.
Reederey87 / glm53-flash-exl3-2x-dgx-spark
GLM-5.3-Flash EXL3 (320B MoE) on 2x NVIDIA DGX Spark — production serving kit, 1M context, 97%+ multi-session prefix caching, DFlash2 spec decode
vcruz305 / Qwen3.8-Flash-Next-EXL3-DGX-Spark-recipe
Serve Qwen3.8-Flash-Next (turboderp ExLlamaV3 pack) on one NVIDIA DGX Spark with exllamav3
samuelcardillo / glm-5.3-flash-2x-rtx-pro-6000-blackwell
Validated GLM-5.3 Flash recipe for 2x NVIDIA RTX PRO 6000 Blackwell 96GB: 262K context, EXL3/TR3, adaptive MTP, tools, and vision.
0xBakeer / TandemLLM
An environment where open models work as agents: a first-level harness with routing, skills, memory and sandboxed tools, on an engine that drafts and verifies its own tokens.
gitcommit90 / glm-5.3-one-spark
GLM-5.3-Flash EXL3 2.05 on one DGX Spark — TP1 vLLM, DFlash2 K5, concurrency, 262K context, and published fidelity measurements
Entrpi / glm-5.3-flash-exl3-2x-spark
GLM-5.3-Flash (EXL3 4bpw + DFlash2) on 2x NVIDIA DGX Spark: one-shot installer, 33-74 tok/s c1, 1.3M+ context, vision
sudoingX / dgx-spark-deepseek-v41
DeepSeek-V4.1-Flash on two NVIDIA DGX Sparks: EXL3 weights from the official checkpoint, upstream vLLM with our patches and decode kernels
bertholomus / deepseek-v4.1-tensorfold-tp2-2xgb10
BertholomusAI recipe: DeepSeek-V4.1-Flash on 2x NVIDIA DGX Spark (GB10), our own TensorFold TP2 engine. Weights: Mia-AiLab EXL3 2.9bpw (MIT).
sxuff / glm53-flash-single-gb10
Pinned, checksum-verified GLM-5.3-Flash EXL3 K2 recipe for one NVIDIA GB10.
knapcio / GLM-5.3-Flash-4x-DGX-Spark-TP4
GLM-5.3-Flash NVFP4 on 4x NVIDIA DGX Spark: vLLM TP4, DFlash2 adaptive draft, measured FP8 vs NVFP4 vs EXL3 vs SGLang
WestWaters / pollard-weights
A tiered-memory system design for workloads that don't fit in RAM: measure the working set, pin the hot tier, stream the cold tier from flash. Ships the residency calculator, measurement harnesses, and the build recipes behind it. Predictions validated against public benchmarks.
dolf3131 / dgx-spark-llm-serving
Serving large LLMs on a single DGX Spark (121 GiB): Qwen3.8-Flash-Next on TensorFold/SparkFold EXL3 and vLLM NVFP4, Nemotron 3.5 Super VL on vLLM; what ran, what it measured, what did not work
sfxnz / DeepSeek-V4.1-Flash-EXL3-vLLM-2x-DGX-Spark
DeepSeek-V4.1-Flash EXL3 vLLM recipe for 2x DGX Spark (GB10)
vcruz305 / GLM-5.3-Flash-EXL3-K2-DGX-Spark-recipe
vLLM recipe: GLM-5.3-Flash EXL3 K2 on one DGX Spark GB10. Native MTP k=2. Measured tok/s.
vcruz305 / vllm-exl3
Serve EXL3 (ExLlamaV3 trellis) quantized models on vLLM fork runtimes — any architecture, mixed per-layer bitrates, composable with source-format non-routed weights
MiaAI-Lab / GLM-5.3-EXL3-3x-DGX-Sparks-TensorFold
GLM-5.3 EXL3 on DGX Sparks with TensorFold
r0b0tlab / qwen38-exl3-dflash2
Qwen3.8-27B EXL3 (4.00 bpw) + DFlash2 speculative decoding for ExLlamaV3, validated at 262k context on a 24 GB RTX 3090