bonsai-2-27b-gsq-rco-gguf
ProCreations基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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Dory-Beam-4B
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View details ↗Dory-Beam-4B-GGUF
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View details ↗grug-27b
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View details ↗grug-27b-gguf
ProCreations**2026-07-23: all rocks re-squeezed from v2.1 weights** (deep think on hard problems, stuck-loop escape, stop discipline - full changelog on grug-27b card). re-download if you grab rocks before. mmproj unchanged (vision tower untouched). this GGUF of grug-27b: Qwen3.6-27B that think in dense grug-speak inside ` `, answer in normal english. same reasoning depth, way fewer think token. full story on main model card. both parent grug hunt HumanEval and sanitized MBPP. number below come from big parent brain, NOT squeezed GGUF rock. grug not claim rock test it never get. number show pass@1 percent. bold grug win that hunt.
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View details ↗grug-27b-mtp-gguf
ProCreationsgrug rock WITH prediction head inside. Q8_0 / Q5_K_M / Q4_K_M, mtp tensors included for llama.cpp speculative decoding (needs build with qwen3_5 MTP support). draft head trained on grug data: t+2 agreement 89.3%. main card: grug-27b-mtp. no-MTP rocks: grug-27b-gguf. grug made by ProCreations.
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View details ↗grug-27b-qat-q4-gguf
ProCreations**2026-07-23 refresh: rock now QAT-trained from grug-27b v2.1 weights** (deep-think + agent-discipline update). bench table below measured on the v1-era rock vs v1 control - directional guide still; v2.1 rock inherit both the QAT recovery AND the v2.1 brain improvements. grug put 27b brain in four-bit cave DURING training. brain feel rounding rock before final squish. this not normal quant. this QAT recovery rock, made for Q4 people. recipe (same as grug-9b-qat, scaled): full-weight QAT on grug-27b, fake int4 asymmetric group-32 with straight-through gradient, ~3M token of grug-think data, Adafactor LR 2e-6, 249 step on one H200. release = 25% QAT move + 75% original anchor (full QAT overcorrect, 9b teach grug this). then fresh BF16 export, quantize ONE time to Q4_K_M.
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View details ↗grug-27b-v2-gguf
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View details ↗grug-35b-v2-gguf
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View details ↗grug-v1.1-qwen-3.8-27b-gguf
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View details ↗MiMo-V2.6-Flash-MOPD-NVFP4
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View details ↗MiMo-V2.6-Flash-RL-NVFP4
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View details ↗Nanbeige4.3-33B-DFlash2
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View details ↗Ternary-Bonsai-2-27B-DFlash2
ProCreationsUpdated September 18, 2026 with the best verified continued-training checkpoint: **r2-dflash**. The original Ternary Bonsai 2 27B PQ2_0 target is unchanged. The head is available as BF16 master weights and **integer Q8_0** inference weights, not FP8. Matched testing against the previous release measured **169.12 → 170.04 decode tokens/sec (+0.54%)** on eight unseen prompts with two repeats. This is a small measured gain, not a large speedup. Both arms used the same runtime and maximum 3 draft tokens. Acceptance is accepted draft tokens divided by proposed draft tokens. Throughput is total generated tokens divided by total decode time, including reasoning tokens. The complete comparison links to the preserved raw requests, outputs and counters in the same reports directory.
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View details ↗Ternary-Bonsai-2-27B-MTP
ProCreationsUpdated September 18, 2026 with the best verified continued-training checkpoint: **r3-mtp**. The original Ternary Bonsai 2 27B PQ2_0 target is unchanged. The head is available as BF16 master weights and **integer Q8_0** inference weights, not FP8. **The +1.26% below is the extra gain over our previous trained MTP head, not the total gain from enabling MTP.** For an independent MTP-on versus MTP-off comparison, see the community reproduction below. Matched testing against the previous release measured **167.14 → 169.25 decode tokens/sec (+1.26%)** on eight unseen prompts with two repeats. This is a small measured gain, not a large speedup. Both arms used the same runtime and maximum 2 draft tokens.
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