GLM-5.3-Flash-Slipstream

GLM-5.3-Flash for the Slipstream inference engine: NVIDIA's NVFP4 checkpoint converted for Slipstream, with the routed and shared experts re-quantized by us to EXL3 4.0 bpw from the BF16 weights (Hessian-calibrated), plus the vision tower.

These are Slipstream weight files (weights.vbin + index.json per directory), the engine's own pre-packed format. They run only with Slipstream; they are not safetensors and do not load in other runtimes. Built with Slipstream's converters at commit 20c2dd9 (2026-10-31).

Base model: zai-org/GLM-5.3-Flash. Engine: Slipstream (engine code release coming soon). Hardware: two NVIDIA DGX Spark (GB10, 128 GB each) connected over their 200 GbE link.

Contents

Directory	What	Node
glm53c_tp2_r0	model weights, rank 0 (NVFP4 + MXFP8 prefill copies, MTP head)	first
glm53c_tp2_r1	model weights, rank 1	second
x3o_tp2_r0	EXL3 4.0 bpw experts, rank 0	first
x3o_tp2_r1	EXL3 4.0 bpw experts, rank 1	second
glm53_vision	vision tower (BF16)	first

Download

On the first Spark (rank 0, runs the HTTP server):

hf download Interactify/GLM-5.3-Flash-Slipstream --local-dir ~/vmodels \
  --include "glm53c_tp2_r0/*" "x3o_tp2_r0/*" "glm53_vision/*"

On the second Spark (rank 1):

hf download Interactify/GLM-5.3-Flash-Slipstream --local-dir ~/vmodels \
  --include "glm53c_tp2_r1/*" "x3o_tp2_r1/*"

The tokenizer, chat template and generation config:

hf download nvidia/GLM-5.3-Flash-NVFP4 --exclude "*.safetensors"   # on the first Spark

The directory names match the defaults in Slipstream's server/models.json, so no configuration is needed.

Run

python server/slipstream.py serve glm-5.3-flash --profile balanced

The server speaks the OpenAI and Anthropic APIs on port 8080. See the Slipstream README for profiles, the router and engine settings.

Measured on Slipstream

• Decode: 46-65 tok/s with MTP drafts (chat, code, JSON).
• Prefill: 1120 (0.9k) / 1680 (3.5k) / 1750 (13.8k) tokens/s.
• Experts: KL 0.053 against BF16 (the NVFP4 experts alone: 0.066).
• Standard profile: perplexity +0.7 % against the checkpoint, KL 0.046.
• tool-eval-bench: 91/100, median agent turn 3.4 s (92 scenarios).

Notes

• Context up to 1,048,576 tokens; Slipstream sizes the window to the memory of the placement.
• An optional DFlash2 drafter is supported by Slipstream but not included here (non-commercial licence; download it yourself).

License

MIT, as the base model (Z.ai) and NVIDIA's NVFP4 checkpoint it is built from. See LICENSE and NOTICE.