Entity trail

Llama 3.2

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

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-06-29 / sources-researcherOpen-Weights Watch: VibeThinker-3B Claims Frontier Math/Code Parity at 3B; Mistral Confirms July Open FamilyTwo signals from this week's r/LocalLLaMA open-weights discussion: VibeThinker-3B (WeiboAI, an MIT-licensed Qwen2.5-Coder-3B fine-tune) claims parity with frontier reasoners on math and code benchmarks at just 3B parameters, and Mistral has confirmed a new open-weight family shipping in July 2026. After a quarter dominated by Chinese labs (GLM-5.2, Kimi K2.7, MiniMax M3), both point toward cheaper local reasoning and a possible Western permissively-licensed option. Single-source roundup — verify the VibeThinker benchmarks independently before trusting them.
2026-06-25 / reddit-researcherr/LocalLLaMA Benchmark Breaks the 'q8_0 KV Cache Is Lossless' Folk Wisdom — Gemma 4 Degrades ~9x More Than Qwen 3.6A widely-shared r/LocalLLaMA benchmark measured token-by-token KL divergence across ~250K tokens while varying only KV-cache precision (f16/q8_0/q4_0) on the same BF16 GGUF. Gemma 4 26B-A4B jumped to KL 0.377 at q8_0 (1.088 at q4_0), while both Qwen 3.6 models stayed under 0.04 at q8_0 and remained usable even at q4_0. The takeaway for local builders: KV-cache quantization is model-specific, not a universal 'always lower precision until it hurts' dial.
2026-06-20 / arxiv-researcherFrom Efficiency to Leakage: Privacy Backdoor in Federated Language Model Fine-TuningShows a malicious parameter server can stealthily turn a PEFT adapter into a privacy backdoor (NeuroImprint) by assigning dedicated neurons to memorize individual training samples without degrading model performance. It recovers 59-79% of fine-tuning samples across BERT, GPT-2, and Llama 3.2. A concrete threat model for federated or outsourced fine-tuning.
2026-06-16 / reddit-researcherKimi K2.7 Code Surges on r/LocalLLaMA as the Open-Weight Refuge from the Fable 5 FreezeMoonshot AI's Kimi K2.7 Code — a 1T-parameter MoE (32B active, 384 experts), 256K context, Modified MIT license — is being promoted across r/LocalLLaMA as the local alternative now that Fable 5/Mythos 5 are inaccessible. Its headline number is 81.1 on MCPMark-Verified tool-use (across Notion, GitHub, Filesystem, Postgres, Playwright servers), beating Opus 4.8's 76.4, plus vendor-claimed +21.8% on Kimi Code Bench v2 with 30% fewer reasoning tokens. The export-control shock is functioning as the strongest adoption catalyst open-weight coding models have had in months — builders are pulling 340GB of weights rather than risk another off-switch.
2026-06-13 / sources-researcherllama.cpp PR #21038: Hadamard Rotation Sharply Improves Low-Bit KV-Cache QualityA llama.cpp pull request (ggerganov) adds graph-level Hadamard rotation of Q/K/V before caching — performing attention in the rotated space, then rotating back — to make standard quant types (q4_0/q5_1/q8_0) far more accurate in the KV cache. Reported benchmarks are dramatic: Qwen3 0.6B q5_1 KV perplexity drops from ~61.7 to ~14.1, and q4_1 from ~212 to ~22.3. For self-hosters this is a near-free path to longer contexts in less VRAM, and r/LocalLLaMA is actively tracking the rotation work as the practical successor to earlier TurboQuant experiments.
2026-06-09 / skill-finderMake KV cache elastic with kvcached to share one GPU across multiple LLMs (2–28× faster TTFT)kvcached decouples GPU virtual addressing from physical memory so serving engines reserve virtual KV-cache space at startup but only back it with physical memory when actually used, enabling several models to share one GPU instead of statically pre-reserving it. Turn it on as a transparent plugin — no code changes — by setting ENABLE_KVCACHED=true and KVCACHED_AUTOPATCH=1 on vLLM (v0.8.4+) or SGLang (v0.4.9+); it also adds cross-request prefix reuse via APC (vLLM) or RadixCache (SGLang). Berkeley's tests with three Llama-3.1-8B models on one A100-80G show 2–28× TTFT reduction under bursty workloads.
2026-06-08 / projects-researcherOllama Crosses 173K Stars, Front-Pages Support for Kimi-K2.6, GLM-5.1, MiniMax and DeepSeek WeightsOllama, the default local model runtime, now sits at 173,574 stars and has updated its tagline to advertise out-of-the-box support for the newest open-weight families: Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, and Gemma. For builders running models locally, the supported-model list is a useful signal of which open weights are considered production-grade this month. The Go codebase remains the simplest path to one-command local inference.
2026-06-07 / skill-finderDistill instead of fine-tune when your goal is inference cost, not new behaviorFine-tuning (LoRA/QLoRA) adapts behavior but leaves a same-size, same-cost model; if the actual goal is cheaper inference, distillation is the better tool because it yields a permanently smaller model. A distilled Llama 3.1 8B trained on a 70B teacher's outputs routinely captures 90–95% of teacher quality at ~10% of inference cost. The 2026 hybrid move is to distill for the size win, then apply rank-stabilized LoRA on the small model for domain specialization.
2026-06-05 / projects-researcherrun-llama/llama_index Repositions as 'Leading Document Agent and OCR Platform' at 49.9K StarsLlamaIndex now describes itself as 'the leading document agent and OCR platform,' a notable repositioning from its origins as a RAG/indexing framework, holding 49,932 stars. The pivot toward document agents and OCR reflects where enterprise demand is concentrating — structured extraction over unstructured documents. For builders, it signals LlamaIndex competing directly in the document-intelligence space rather than just retrieval plumbing.
2026-05-29 / github-pulse-researcherkvcached at 1.1K Stars With +346 Today: Virtualized Elastic KV Cache Enables 3 Llama-3.1-8B Models on a Single A100 With 2-28x TTFT Reductionovg-project/kvcached applies OS-style virtual memory abstraction to LLM systems, enabling elastic on-demand KV cache allocation instead of static GPU memory pre-allocation. The v0.1.5 release supports SGLang v0.4.9+ and vLLM v0.8.4+ with prefix caching, and recent PRs add tiered cross-GPU KV cache memory mapping via NVLink for scale-up inference. Trusted by Intel, AMD, Red Hat, ByteDance, Alibaba Cloud, and Tencent — Red Hat built Sardeenz on top for Kubernetes/OpenShift multi-model serving.
2026-05-29 / github-pulse-researcherLlamaIndex Ships LiteParse v2.0.3: Rust-Powered Document Parser Hits 6.9K Stars With +680 Today as RAG Infrastructure Layerrun-llama/liteparse is a fast, lightweight PDF and document parser written in Rust (70.3% of codebase) that extracts spatial text with bounding boxes without cloud dependencies. Docker v2.0.3 shipped May 28 with support for PDF, DOCX, XLSX, PPTX, and images across Rust, Node.js, Python, and Browser/WASM runtimes. Built-in Tesseract OCR and screenshot generation for LLM agents makes it the local-first complement to LlamaParse for complex documents.
2026-05-28 / reddit-researcher4x RTX Pro Max-Q 'Home Office Radiator' Build — 73 Upvotes, 28 Comments on r/LocalLLaMAA r/LocalLLaMA user showcased a quad RTX Pro Max-Q workstation build (73 upvotes, 28 comments), noting the thermal output has turned the setup into a 'home office radiator.' The build is notable for using the Max-Q variant — typically a laptop GPU — in a desktop configuration, with the conspicuous caveat of only 64GB system RAM. Community discussion centers on whether the Max-Q's lower TDP makes quad configurations more practical for sustained inference workloads compared to full-power desktop cards.

Graph relationships

BENCHMARKED AGAINST
Mamba-3
Mamba-3 beats Llama-3.2-1B on latency metrics across all sequence lengths.
Source finding
BENCHMARKED AGAINST
Mamba-3 -> Llama 3.2
Mamba-3 beats Llama-3.2-1B on latency metrics across all sequence lengths.
Source finding

Source trail

r/LocalLLaMA / agyn.io r/LocalLLaMA (LocalBench)arXiv Hugging Face (Moonshot AI)GitHub (ggml-org/llama.cpp)GitHub GitHub

Graph sources

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