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r0b0tlab/GLM-5.3-Flash-EXL3-SAGE-2.25bpw
GLM-5.3-Flash-EXL3-SAGE-2.25bpw is a text generation model from r0b0tlab. Use it when you need the model to write or continue text. It is set up for exllamav3. The card lists the license as mit.
EXL3 (ExLlamaV3 trellis) quantization of zai-org/GLM-5.3-Flash (320B total / ~18B active MoE) by r0b0tlab.
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From the Hugging Face model README
EXL3 (ExLlamaV3 trellis) quantization of
zai-org/GLM-5.3-Flash
(320B total / ~18B active MoE) by r0b0tlab.
mul1 codebook, mixed K3/K4 tiles,
output scales on, 6-bit head.quantization_config.json (full module/tensor manifest) and tokenizer
files.On a single GB10, our standalone ExLlamaV3 + TabbyAPI runtime
(r0b0tlab/glm53-flash-exl3-exllamav3-gb10)
with our EXL3 DFlash2 draft
(r0b0tlab/GLM-5.3-Flash-DFlash2-EXL3-3.00bpw)
served this pack at 262,144 tokens (FP16 KV, batch size 1, DFlash2 K=5)
and passed a token-exact needle-in-a-haystack retrieval at
259,993 actual prompt tokens — clean answer, exact client/server token
parity, guarded by an independent 6,144-MiB host-memory floor with no NVRM
allocation failure.
Not qualified on that profile: multi-key output formatting, concurrency > 1, throughput at 256K, long-run stability. Details and sanitized evidence live in the runtime repository.
Two runtimes are available for this pack:
ExLlamaV3 / TabbyAPI (256K verified):
r0b0tlab/glm53-flash-exl3-exllamav3-gb10 —
native ARM64 CUDA 13 container, guarded 256K serve.
Published image (ARM64/SM121):
docker pull ghcr.io/r0b0tlab/glm53-flash-exl3-exllamav3-gb10:b25c467.
vLLM (32,768-token published profile):
r0b0tlab/glm53-flash-exl3-dflash2-sm121 —
host-native vLLM v0.30.0rc1 + EXL3 plugin; DFlash2 K=5 measured
structured 50.2 / code 43.4 / prose 19.5 tok/s single-stream on one GB10.
The two engines' results are independent; do not transfer between them.
Text-180: 168/180 (93.33%) — GSM8K 98.75%, HumanEval 97.5%, IFEval 77.5%,
hard_reasoning 95.0%. BFCL-hard20: 6/20. Full 200: 174/200 (87.0%).
Serial execution, effort=low, zero transport errors. (The vLLM runtime's
2026-09-21 kit on its own 32K profile: 170/180 text, 10/20 BFCL — engines are
independent; scores do not transfer.) Evidence:
evidence/glm53-exl3-q200v2-20260927/ in the ExLlamaV3 runtime repo.
Quantized by r0b0tlab from zai-org/GLM-5.3-Flash (MIT). Weights unchanged
beyond quantization. EXL3 format follows exllamav3 (MIT).