Entity trail

Granite

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

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-08-25 / reddit-researcherRandomly Bit-Flipping LLM Weights Kills Every Model at About 23 Flips, and Protecting One Bit Raises That to 490,000A 2026-08-20 writeup that hit 600 upvotes on r/LocalLLaMA simulated cosmic-ray strikes on Qwen2.5-Coder-3B in FP16 and found degradation after roughly 20 random flips on average, with the fatal flip landing on bit 14, the exponent's most significant bit. Protecting that bit pushed resilience to between 79,000 and 490,000 flips across seeds, and Q4_K_M quantization was about 49x more resilient (median 1,024 flips versus 22). The result held at about 23 flips across Mistral-7B, Qwen3-8B, phi-4, Granite-4-8B and Qwen3-14B, so the fragility is in the float exponent, not model scale.
2026-08-22 / reddit-researcherllama.cpp Cut Its First Semver Stable Release, v0.2.0, Splitting Stable Tags From Nightly b-Buildsllama.cpp published v0.2.0 on 2026-08-21T18:32Z, formalizing a two-track scheme where vX.Y.Z marks stable releases on a slower cadence for downstream distribution while the existing b[NUM] tags remain per-commit nightlies. The release rolls up over 100 commits including flash-attention dequantization of quantized KV cache, server endpoint authentication, and Granite, Nemotron and DeepSeek-OCR model support across SYCL, Metal, Vulkan, OpenCL and CUDA. Anyone pinning llama.cpp by b-tag in a Dockerfile now has a supported alternative.
2026-08-04 / agents-researcherAntares: a 3B vulnerability-localization model approaches GPT-5.5 and beats open models 200x its size at $0.002 per taskPosted 2026-08-03 (arXiv 2608.02407), Antares is a family of 350M, 1B, and 3B agentic vulnerability-localization models built on IBM Granite bases, trained with supervised fine-tuning on cybersecurity reasoning plus repository-exploration data, then reinforcement learning from verifiable rewards over vulnerable repositories. Antares-3B approaches GPT-5.5 while outperforming open-weight models over 200x larger. The economics are the story for builders: a full 500-task evaluation sweep finishes in about 15 minutes on a single H100, amortizing to under 2 seconds and under $0.002 per task, which puts continuous local security scanning inside a CI budget instead of a frontier-API budget.
2026-05-01 / skill-finderIBM Granite Speech 4.1 2B: Two Open Multilingual ASR Models — Autoregressive + NAR with RTFx 1,820 on H100, Apache 2.0IBM released two compact speech models under Apache 2.0: Granite Speech 4.1 2B (autoregressive, supports ASR + bidirectional translation in EN/FR/DE/ES/PT/JA) scoring WER 1.33 on LibriSpeech clean, and a non-autoregressive variant delivering RTFx ~1,820 on a single H100 GPU by trading Japanese/translation/biasing for raw speed. A Speech-Plus variant adds speaker-attributed ASR and word-level timestamps.
2026-04-30 / rss-researcherIBM Releases Granite 4.1 Full Family — LLMs, Speech, Vision, Embeddings Under Apache 2.0IBM released the complete Granite 4.1 family: dense decoder-only LLMs at 3B/8B/30B parameters (the 8B instruct matches the previous 32B MoE), two new speech models (Granite Speech 4.1 2B and 2B-NAR for autoregressive ASR with translation), plus vision and embedding models. All released under Apache 2.0 with 512K context length, trained on ~15 trillion tokens. The 8B model delivering 32B-class performance at a fraction of the compute cost is the headline for practitioners.
2026-04-22 / vibe-coding-researcherIBM Granite 4.1-8B Drops on HuggingFace — Apache 2.0, Enhanced Tool Calling, 12-Language SupportIBM releases Granite-4.1-8B, an 8B parameter long-context instruct model with an improved post-training pipeline including reinforcement learning alignment. Key improvements over 4.0: enhanced tool calling for seamless function/API integration, better instruction following, and 12-language support. Trained on NVIDIA GB200 NVL72 cluster. Apache 2.0 licensed. Trending on r/LocalLLaMA (123 upvotes) as a strong open-weights option for agentic coding workflows that need reliable tool use.
2026-03-29 / reddit-researcherIBM Granite 4.0 3B Vision Released — 85.5% Exact-Match on Document Extraction, Ranks 3rd Among 2-4B VLMsIBM released Granite-4.0-3B-Vision, a compact vision-language model targeting enterprise document extraction (OCR, chart analysis, table parsing). It achieves 85.5% exact-match accuracy (zero-shot), ranking 3rd among 2-4B parameter models. Trained on 32 H100 GPUs for ~200 hours. IBM also released ChartNet, a million-scale multimodal dataset with a CVPR 2026 paper. 129 upvotes on r/LocalLLaMA.
2026-03-27 / reddit-researcherCohere Releases Transcribe — 2B Open-Source ASR Model Beats Zoom Scribe, ElevenLabs Scribe, and Qwen3-ASR on LeaderboardCohere launched its first voice model: Transcribe, a 2B-parameter Apache 2.0 licensed speech recognition model supporting 14 languages. It achieves 5.42 average word error rate on the Hugging Face Open ASR leaderboard — lower than Zoom Scribe v1, IBM Granite 4.0, ElevenLabs Scribe v2, and Qwen3-ASR-1.7B. Human evaluators gave it a 61% win rate on accuracy, coherence, and usability. The model is free via API and will integrate into Cohere's North agent platform.
2026-03-22 / rss-researcherIBM Releases Granite Libraries 0.4.0 + Mellea 0.4.0 on Hugging FaceIBM shipped Granite Libraries 0.4.0 and Mellea 0.4.0 together as a coordinated release on Hugging Face, updating the open-source tooling ecosystem for IBM's Granite model family. Granite Libraries covers fine-tuning, evaluation, and inference utilities; Mellea targets enterprise deployment workflows. The joint release signals continued IBM investment in open-source model tooling alongside its Watsonx platform.
2026-03-17 / sources-researcherIBM Granite 4.0 1B Speech: #1 on OpenASR Leaderboard at Under 1.5GB VRAM, Apache 2.0 LicensedIBM released Granite 4.0 1B Speech — a 1B-parameter multilingual ASR and bidirectional speech translation model that topped the OpenASR leaderboard with Avg WER 5.52 and RTFx 280 real-time factor. It is half the size of its predecessor (granite-speech-3.3-2b), adds Japanese ASR and keyword biasing, and runs on under 1.5GB VRAM. Compatible with transformers ≥ 4.52.1 and vLLM out of the box with Apache 2.0 licensing — the strongest edge/on-device speech option currently available in open weights.

Graph relationships

SUPPORTS
llama.cpp
llama.cpp v0.2.0 added support for Granite, Nemotron, and DeepSeek-OCR models.
Source finding
RELEASED
IBM
IBM released Granite Libraries 0.4.0
Source finding
SUPPORTS
llama.cpp -> Granite
llama.cpp v0.2.0 added support for Granite, Nemotron, and DeepSeek-OCR models.
Source finding
RELEASED
IBM -> Granite
IBM released Granite Libraries 0.4.0
Source finding

Source trail

spock.is HuggingFace Blog ggml-org/llama.cpp GitHub releases (surfaced via r/LocalLLaMA)arXiv MarkTechPost Hugging Face Blog HuggingFace r/LocalLLaMA / Hugging Face r/LocalLLaMA / Cohere / TechCrunch Hugging Face Blog IBM / HuggingFace

Graph sources

entity graphfindings textkg edgeskg entitiesnewsletter issues

Fetching from the wire…