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bertholomus/README.md

BertholomusAI

Reproducible distributed LLM inference, quantization research, and evidence-backed deployment recipes for NVIDIA GB10 / DGX Spark systems.

We publish the receipts that matter: pinned revisions, integrity manifests, exact runtime formulas, bounded capability gates, concurrency/context evidence, restart proof, limitations, licensing, and upstream credits.

Verified public work

Project Topology Focus GitHub Hugging Face
GLM-5.3 (full, 753B) EXL3 3.0 bpw 4× GB10, TP4 Our own quant; TensorFold engine branch; 1M context via context parallelism; MTP drafting; KL 0.109 vs BF16 Recipe + benchmarks Weights
DeepSeek-V4.1-Flash on TensorFold 2× GB10, TP2 Clean-room deepseek_v41 model family for TensorFold; 1M window, vision, DSpark drafting, 4-stream concurrency Recipe Card
DeepSeek-V4.1-Flash DSpark 4× GB10, TP4 SGLang recipe v1.1.6: measured deviations from upstream, 1M context, 8M-token shared KV pool, systemd lane Recipe + evidence Card
GLM-5.3-Flash NVFP4 4× GB10, TP4 1M-configured context, FP8 KV, DFlash2, tools, multimodal and long-context gates Recipe + evidence Evidence card
DeepSeek V4 Flash Graph-8 4× GB10, TP4 Four-node scaling, evidence and release recipe Repository Model card
DeepSeek V4 Flash Graph-8 2× GB10 Reproducible two-node deployment and benchmarks Repository Model card

Engine work and upstream contributions

Publication standard

  • Attribute upstream models, checkpoints, runtimes, kernels, and recipe lineage.
  • Separate configured capability from directly proven capability.
  • Publish machine-readable evidence and known limitations alongside headline results.
  • Never present third-party quantizations as BertholomusAI-created artifacts.
  • Mirror weights only when provenance and redistribution rights are clear.
  • Prefer exact revisions and hashes over mutable tags.

Current research direction

  • Full GLM-5.3 on four GB10 systems: faster prefill and vision for the non-Flash model.
  • New model families and multi-node tensor parallelism for TensorFold on GB10.
  • Full-download quantization workflows with explicit authorship and reproducibility.
  • Speculative decoding, long-context validation, and safe production supervision.
  • Hermes-native local-agent infrastructure.

Hugging Face: huggingface.co/bertholomus · X: @bertholomusai

Popular repositories Loading

  1. deepseek-v4-flash-0731-dspark-graph8-4xgb10 deepseek-v4-flash-0731-dspark-graph8-4xgb10 Public

    Verified four-GB10 DeepSeek-V4-Flash-0731 TP4 DSpark Graph-8 deployment and benchmarks

    Python 1

  2. hermes-agent hermes-agent Public

    Forked from NousResearch/hermes-agent

    The agent that grows with you

    Python 1

  3. deepseek-v4.1-flash-dspark-tp4-4xgb10 deepseek-v4.1-flash-dspark-tp4-4xgb10 Public

    BertholomusAI in-house recipe: DeepSeek-V4.1-Flash on 4x NVIDIA DGX Spark (GB10), TP4 DSpark under SGLang - config, patches, systemd lane, and measured evidence

    Python 1

  4. glm-5.3-tensorfold-tp4-4xgb10 glm-5.3-tensorfold-tp4-4xgb10 Public

    BertholomusAI recipe: full GLM-5.3 (non-Flash) EXL3 3.0bpw on 4x NVIDIA DGX Spark (GB10), TensorFold TP4 - quant formula, launch scripts, benchmarks, measured numbers

    Python 1

  5. deepseek-v4-flash-0731-dspark-graph8 deepseek-v4-flash-0731-dspark-graph8 Public

    Verified two-node GB10 DeepSeek-V4-Flash-0731 DSpark Graph-8 deployment and benchmarks

    Python

  6. glm-5.3-flash-nvfp4-gb10-tp4 glm-5.3-flash-nvfp4-gb10-tp4 Public

    Evidence-backed GLM-5.3-Flash NVFP4 TP4 deployment validation on 4x NVIDIA GB10.

    Python