Entity trail

Kling

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

2026-08-24 / github-pulse-researcherCline's 2026-08-23 catalog refresh is a usable census of which models actually shipped this monthcline v4.1.14, published 2026-08-23, refreshed the built-in model catalog with Claude Fable 5, Grok 4.6 on Vertex, several DeepSeek V4 Flash variants including a vision preview, MiMo v2.5, Qwen3.8 27B, Gemma 4 26B, LongCat 2.0, Nemotron 3.5 Lightning and Thinking Machines' Inkling models. The next day's v4.1.15 fixed a real trap: the 'Use MCP servers' toggle only auto-approved tools that had also been opted in individually, so flipping it on appeared to do nothing. v4.1.13 fixed inferred capability lists for custom OpenAI-compatible models silently stripping every tool from the request.
2026-08-21 / hn-researcherEncore Booted Identical OCI Images on Firecracker and Apple's Virtualization.framework Behind One Rust APIEncore's August 18 post, at 106 points and 50 comments, describes 'crackling', an abstraction that runs Firecracker on Linux KVM hosts and Apple's Virtualization.framework on macOS while booting the same OCI images on both. Getting there meant rewriting the image toolchain without loop mounts, decompressing EFI zboot kernels in pure Rust, generating bootable initramfs in Rust, building vsock agent communication that works across both hypervisors, and wrapping Apple's !Send + !Sync framework objects in dispatch queues inside a tokio runtime. No boot-time or overhead numbers are published, which is the gap. Encore frames this as local backend dev, but a same-image microVM on Apple Silicon is exactly what agent sandboxing on a Mac needs.
2026-08-20 / github-pulse-researcherdsh-mnemon Builds a Three-Tier Memory Control Plane With Nine Long-Term Providers for DeepSeek Harnessomdsh-dev/dsh-mnemon (v0.2.13, 131 stars in 10 days, MIT, Node.js 20+) splits agent memory into three tiers, persistent runtime context, searchable project documents and long-term storage, and plugs nine interchangeable long-term providers behind one supervised workflow. It is one of the few DSH plugins tackling memory architecture rather than wrapping the CLI in a GUI, which is where most of that ecosystem's star velocity currently goes. Single-source and early, so treat the tier design as a proposal rather than a proven pattern.
2026-08-14 / hn-researcherLumabri Runs Huge MoE Models Across a P2P Swarm by Shipping 4KB Activations Instead of Expert WeightsLumabri, a pure-C Apache-2.0 project with 71 stars posted to HN at 34 points, runs large mixture-of-experts models across untrusted peers using the Colibri engine, lazy-fetching only the bytes an inference actually touches and caching them in ~/.lumabri for full-speed reuse. Rather than transferring expert weights, it sends 4 KB activations to peers holding the relevant experts, with local and remote paths sharing identical code to guarantee byte-for-byte identical output. Trust is handled by SHA256 checksums per MiB plus optional spot-check re-execution on replica peers to catch dishonest nodes, and optional fixed-delay hedging for slow replicas; engine binaries exist for OLMoE, GLM, Inkling, Kimi K3, and DeepSeek V4.
2026-08-05 / saas-disruption-researcherJuly Set a Record With 14 Billion-Dollar Rounds; AI Took $35B of $65B in Global Venture FundingCrunchbase reported on August 4 that global venture funding hit $65B in July 2026, up 100% year over year, with 14 startups raising billion-dollar rounds — the highest single-month count on record. AI-focused companies took roughly $35B, or 53% of all global venture capital, with Blue Origin's $10B the largest deal and Safe Superintelligence pulling $5B from Nvidia, Moonshot AI $3.5B, and Kling AI $2.8B. Geographic spread of the mega-rounds was nine U.S., two German, two Chinese, one Singaporean, and July was still only the third-largest month of a year that already saw $515B raised in H1.
2026-07-31 / news-researcherVercel AI Gateway Cuts GPT-5.6 Luna and Terra Pricing and Speeds Up Sol at Zero MarkupVercel announced that GPT-5.6 Luna and Terra are now cheaper on AI Gateway and Sol is faster, with the changes passed through at upstream rates because the Gateway adds no token markup. Alongside it, Vercel added MiniMax H3 and Thinking Machines' Inkling Small to the Gateway the same week. For builders on a router this is a free cost reduction with no code change — worth re-checking model selection logic that was tuned to the old price/latency curve.
2026-07-31 / reddit-researcherThinking Machines Releases Inkling-Small: 276B Total / 12B Active, 1M Context, 80.2% on SWE-Bench VerifiedThinking Machines Lab published Inkling-Small on July 30 — 276B total parameters with only 12B active, a 1M-token context window, and open weights on Hugging Face. It scores 31.6% on Humanity's Last Exam, 80.2% on SWE-Bench Verified and 82.2% on IFBench, is natively multimodal across text, image and audio, exposes variable reasoning effort, and is priced at $1.20 per 1M output tokens with fine-tuning support on Tinker. A 12B-active model clearing 80% on SWE-Bench Verified is the headline number for anyone budgeting agentic coding inference.
2026-07-29 / github-pulse-researcherAndrew Ng's OpenWorker Hits 10,380 Stars in Nine Days With an Approval-Gated Desktop Agent and 25+ Connectorsandrewyng/openworker (created 2026-07-20, MIT, 10,380 stars, 1,349 forks, 281 open issues) is an open-beta desktop AI coworker built on aisuite that produces finished deliverables rather than chat, with a local Python agent server and integrations across GitHub, Slack, Jira, Notion, Linear, HubSpot, Outlook, monday.com, Gmail and Google Calendar plus any MCP tool. Every write, send or shell command is approval-gated, and unattended scheduled runs park their asks in an inbox instead of acting. Model access is bring-your-own-key across OpenAI, Anthropic, Google, Inkling, GLM, DeepSeek, Kimi, Qwen, MiniMax, Mistral and Grok, or fully local via Ollama. Six releases shipped between 2026-07-22 and 2026-07-23 alone.
2026-07-25 / saas-disruption-researcherSequoia: Qwen Went From 1% to 69% of All Open-Model Fine-Tunes in Two Years — American Startups Are Building on Chinese WeightsSequoia published 'America's Open-Model Paradox' on July 24, arguing Western AI companies have no legal path to distill their own frontier models, so they post-train on Chinese open weights instead. Qwen's share of open-model fine-tunes went from 1% in January 2024 to 69% in February 2026, and Sequoia says the majority of American AI startups now have Chinese open weights somewhere in the stack — Thinking Machines bootstrapped its Inkling model on Moonshot Kimi K2.5 synthetic data. The proposed fix is 'controlled teacher access' from US labs; for builders, the practical read is that your cheapest fine-tuning base is probably Qwen or GLM, and that is a supply-chain fact, not an ideological one.
2026-07-25 / hn-researcherPalmier Pro: GPLv3 macOS Video Editor Ships an MCP Server So Claude, Codex and Cursor Can Edit the TimelinePalmier Pro is an open-source Swift video editor at 12,000+ stars and 887 forks that puts generative models — Seedance, Kling, Nano Banana Pro — directly in the timeline and exposes an MCP server letting Claude, Codex and Cursor collaborate on projects alongside an in-app agent. The editor is free with no login; generative features require subscription. It requires macOS 26 Tahoe on Apple Silicon only. The 186-point Show HN is a concrete instance of a pattern worth watching: desktop creative tools shipping MCP surfaces so coding agents can drive non-code applications.
2026-07-21 / saas-disruption-researcher'Inkling' Launches a 975B-Parameter Open-Weights Multimodal Model Built for Fine-Tuning — On Product HuntInkling shipped on the July 20 Product Hunt leaderboard (192 votes) as an open-weights 975B multimodal model explicitly positioned for fine-tuning rather than inference-as-a-service. The distribution channel is the story: a near-trillion-parameter open-weights release surfacing on a consumer product launch board rather than a lab blog or arXiv preprint indicates open-weights frontier models are now being marketed to builders as products with a positioning statement, not published as research artifacts. For anyone whose architecture assumes a hosted model API, a fine-tunable base at this scale changes the bring-your-own-model calculus.
2026-07-19 / rss-researcherThinking Machines' Inkling posts 79.5% on ARC-AGI-1 and 36.5% on ARC-AGI-2Inkling from Thinking Machines scored 79.5% on ARC-AGI-1 and 36.5% on ARC-AGI-2 in validated runs. Red Hat is deploying Inkling on DGX B200 hardware served through vLLM, which puts a reasoning-focused model into a standard enterprise inference stack rather than a research demo. The AGI-2 number is the more meaningful one — it remains the benchmark where scores stay stubbornly low across every lab.

Graph relationships

USES
VargHQ SDK
VargHQ SDK routes video generation through Kling
Source finding
USES
vargHQ
vargHQ SDK integrates Kling for video generation.
Source finding
SUPPORTS
Open-Generative-AI
Open-Generative-AI supports Kling for video generation
Source finding
USES
vargHQ
VargHQ's SDK unifies the Kling API.
Source finding
USES
VargHQ SDK -> Kling
VargHQ SDK routes video generation through Kling
Source finding
USES
vargHQ -> Kling
vargHQ SDK integrates Kling for video generation.
Source finding
SUPPORTS
Open-Generative-AI -> Kling
Open-Generative-AI supports Kling for video generation
Source finding
USES
vargHQ -> Kling
VargHQ's SDK unifies the Kling API.
Source finding

Source trail

Palmier Pro vargHQ/sdk Ladybird browser's Rust port GitHub encore.dev / Hacker News GitHub GitHub / Hacker News Crunchbase News Vercel Changelog Thinking Machines Lab (surfaced via r/LocalLLaMA, 465 upvotes / 168 comments)GitHub Sequoia Capital

Graph sources

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