Entity trail

AngelSlim

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-08-30 / reddit-researcherTencent's AngelSlim shipped a ternary GGUF that puts the 770B Hy4-preview in 214 GiB at 2.38 bits per weightThe AngelSlim/Hy4-preview-GGUF repo offers Q4_K_M at 435.20 GiB (4.86 bpw) and STQ1_0 at 213.66 GiB (2.38 bpw), roughly half the size, benchmarked at 204.56 t/s prefill and 20.47 t/s decode on 8x H20. STQ1_0 comes from llama.cpp PR #22836 and uses ternary weights with 3:4 forced sparsity at 1.3125 bpw on routed-expert gate/up projections across 29 layers, with IQ2_XXS at 2.0625 bpw on the other 48; an imatrix is mandatory. The r/LocalLLaMA thread (821 upvotes) circulated a claim of ~98% performance retention, and the top skeptical reply notes that 98% on KL divergence alone can be misleading.
2026-07-15 / reddit-researcherllama.cpp Merges Native Hy3 Support (PR #25395) — Tencent's 295B MoE Now Runs Locally via 1-Bit/4-Bit GGUFOn July 14, 2026, llama.cpp merged upstream support for Tencent's hy_v3 (Hunyuan Hy3) architecture, a 295B-parameter / 21B-active MoE, so any recent master build can now load it; community GGUF quants (Q2_K, IQ2_M, Q4_K_M) from AngelSlim and others already ship on Hugging Face, with a 1M-context conversion reported running at ~11 tok/s. The PR also wires up MTP speculative decoding (--spec-type draft-mtp, --spec-draft-p-min 0.75), measured at roughly +40% decode throughput on code. This is the local-inference milestone of the week: a near-frontier 295B open model becomes runnable on a single high-memory rig, days after Hy3's Apache-2.0 July 6 release.
2026-05-22 / reddit-researcherTencent Open-Sources Hy-MT2 Translation Models — 1.8B/7B/30B-A3B Supporting 33 Languages, 440MB On-DeviceTencent released Hy-MT2, a family of multilingual translation models in three sizes (1.8B, 7B, 30B-A3B MoE) supporting 33 languages, with paper, GitHub repo, and HuggingFace weights all published May 21. The 7B and 30B models outperform DeepSeek-V4-Pro and Kimi K2.6 in fast-thinking translation mode. The 1.8B model compresses to just 440MB via AngelSlim 1.25-bit extreme quantization with 1.5x inference speedup, making it a strong on-device translation option.

Graph relationships

SUPPORTS
Hy4-preview
AngelSlim reduces Hy4-preview from 435 GiB to 214 GiB using ternary quantization at 2.38 bits per weight.
Source finding
RELEASED
Tencent
Tencent released AngelSlim, a ternary quantization for the Hy4-preview model.
Source finding
RELEASED
Tencent -> AngelSlim
Tencent released AngelSlim, a ternary quantization for the Hy4-preview model.
Source finding

Source trail

Hugging Face llama.cpp PR #25395 Latent Space NVIDIA r/LocalLLaMA / Tencent GitHub

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