テーマ — 基準日 2026-07-22
LLM基盤（2026-07）
現行のフロンティア基盤モデル · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開ランキング LM Arena / Chatbot ArenaPublic Text/Code/Agent arena boards (ex-LMSYS; HF Space is a mirror entry)
- 公開ランキング LMSYS Arena HF Space (mirror)Arena HF Space mirror (often more reachable)
- 公開API OpenRouter Models APIMachine-readable model catalog (id/pricing/context)
- 公開ランキング Artificial AnalysisIndependent quality/speed/price comparison
- 公開ランキング Hugging Face Open LLM LeaderboardOpen-weight evaluation entry point
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Claude Fable 5 / Opus 4.8 class マップ優先度: 100 | Primary long-horizon control-plane class; still top-tier on agent/SWE boards |
| 2 | GPT-5.6-Sol / GPT-5.5 Pro class マップ優先度: 99 | Coding/STEM flagship; default executor in Codex and ChatGPT product surface |
| 3 | Gemini 3.1 / 3.x class マップ優先度: 98 | Long-context science/multimodal surface tightly tied to Google stack |
| 4 | Grok 4.5 / xAI マップ優先度: 97 | Realtime + X-native retrieval; cost-effective cross-check route |
| 5 | DeepSeek-V3 / R1 class マップ優先度: 96 | Open-weight reasoning cost leader for private/local deploy |
| 6 | Qwen3 / Qwen 3.7 class (Alibaba) マップ優先度: 95 | Active bilingual + contest-math line; open and cloud dual track |
| 7 | Llama 4 class (Meta) マップ優先度: 94 | Default open ecosystem base; wide fine-tune and private deploy |
| 8 | Mistral Large / Mixtral line マップ優先度: 93 | EU-positioned open/API line favored in enterprise procurement |
| 9 | Kimi K3 / Moonshot long-context マップ優先度: 92 | Long-context + strong frontend-code arena presence; CN document workflows |
| 10 | GLM-5.x / Zhipu マップ優先度: 91 | CN API + open dual track; frequent open-weight Arena contender |
| 11 | Amazon Nova class マップ優先度: 90 | Bedrock-native tiered models default inside AWS accounts |
| 12 | Claude Sonnet 5 / writing tier マップ優先度: 89 | Writing/instruction-following product default; cost-efficient daily writing tier |
| 13 | o-series / deliberative reasoners マップ優先度: 88 | Explicit multi-step reasoning route for hard second-pass work |
| 14 | Claude Haiku / fast tier マップ優先度: 87 | Low-latency triage tier used as cheap front filter |
| 15 | Phi-4 / small strong on-device マップ優先度: 86 | On-device/edge small models for privacy and offline |
| 16 | Cohere Command / Embed / Rerank マップ優先度: 85 | Still common specialized components for enterprise RAG stacks |
| 17 | xAI image/video generation stack マップ優先度: 84 | Same-vendor multimodal gen stack beside Grok chat |
| 18 | OpenAI Images 2.0 / GPT Image 2 マップ優先度: 83 | High-res controllable product-image path used in delivery |
| 19 | Local GGUF 70B-class (llama.cpp) マップ優先度: 82 | Fully offline private inference baseline for air-gapped envs |
| 20 | Command R+ / retrieval-first LLMs マップ優先度: 81 | Retrieval-first enterprise QA family still on buy lists |
エージェント枠組み
システムとして出荷するオーケストレーション · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公式ドキュメント Model Context Protocol SpecCross-runtime tool protocol standard
- 公式ドキュメント LangGraph DocumentationStateful agent graph runtime docs
- 公式ドキュメント Anthropic Claude Agent SDKOfficial Claude Agent SDK docs (same tool loop as Claude Code)
- 公式ドキュメント OpenAI Agents SDKOpenAI Agents Python SDK
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | LangGraph 採用度: 100 | Stateful recoverable graphs; a de-facto complex-agent standard |
| 2 | Claude Agent SDK / Claude Code harness 採用度: 99 | Native coding-agent harness with hooks/skills |
| 3 | OpenAI Agents SDK 採用度: 98 | Hosted tool-loop with MCP integration path |
| 4 | MCP (Model Context Protocol) 採用度: 97 | Tool protocol standard across IDEs/runtimes |
| 5 | CrewAI 採用度: 96 | Role-based multi-agent team templates |
| 6 | AutoGen / AG2 採用度: 95 | Multi-agent conversational collaboration patterns |
| 7 | Semantic Kernel 採用度: 94 | Enterprise plugin orchestration (.NET/Python) |
| 8 | LlamaIndex Workflows 採用度: 93 | Data/index-centric agent pipelines |
| 9 | Dify 採用度: 92 | Low-code agent app build and publish |
| 10 | n8n + AI nodes 採用度: 91 | Workflow automation with embedded LLM steps |
| 11 | Temporal + LLM workers 採用度: 90 | Durable long-running agent jobs |
| 12 | Mastra 採用度: 89 | TypeScript-native agent framework |
| 13 | PydanticAI 採用度: 88 | Typed Python agent tooling |
| 14 | Cursor Agent mode 採用度: 87 | In-IDE multi-file agent UX default |
| 15 | Codex CLI 採用度: 86 | Terminal-side OpenAI coding agent |
| 16 | Aider 採用度: 85 | Git-diff-aware CLI pair programmer |
| 17 | Browser-use / computer-use stacks 採用度: 84 | GUI/browser action agents |
| 18 | Haystack 採用度: 83 | Composable NLP/RAG/agent pipelines |
| 19 | OpenClaw / Hermes-class harnesses 採用度: 82 | Personal multi-tool agent OS direction |
| 20 | Smolagents 採用度: 81 | Minimal Hugging Face agent runtime |
コーディングエージェントとIDE
日々の出荷に使う面 · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公式ドキュメント Claude Code DocsOfficial Claude Code documentation
- 信頼サイト OpenAI Codex (GitHub)Official Codex repo entry (marketing pages often bot-403)
- 公式ドキュメント Cursor DocsCursor IDE agent docs
- 信頼サイト Aider GitHubOpen-source CLI pair-programming agent
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Claude Code 出荷頻度: 100 | Deep-repo agent with hooks/skills; strong multi-file reasoning |
| 2 | Codex CLI / VS Code agent 出荷頻度: 99 | Terminal-first autonomous coding; top Terminal-Bench surface |
| 3 | Cursor 出荷頻度: 98 | Mainstream AI IDE default; highest daily multi-file edit polish |
| 4 | GitHub Copilot Workspace / agent 出荷頻度: 97 | PR-native agent with CI; common enterprise procurement default |
| 5 | Windsurf / Devin Desktop 出荷頻度: 96 | Cognition-consolidated agent IDE surface; async ticket-style work |
| 6 | Grok Build 出荷頻度: 95 | xAI coding CLI/build surface; fastest-rising newcomer |
| 7 | OpenCode 出荷頻度: 94 | Open multi-provider coding agent; leading MIT/star open entry |
| 8 | Gemini CLI 出荷頻度: 93 | Google terminal coding agent; free frontier-model entry |
| 9 | Aider 出荷頻度: 92 | Pure CLI + git workflow camp |
| 10 | Continue.dev 出荷頻度: 91 | Open IDE extension hub |
| 11 | Zed AI 出荷頻度: 90 | Performance-first editor AI |
| 12 | JetBrains AI Assistant 出荷頻度: 89 | Embedded in JetBrains ecosystem |
| 13 | Amazon Q Developer 出荷頻度: 88 | AWS-centric code agent |
| 14 | Cline / Roo Code 出荷頻度: 87 | Open VS Code agent fork family |
| 15 | Replit Agent 出荷頻度: 86 | Cloud IDE full-stack agent |
| 16 | v0 / Lovable class 出荷頻度: 85 | UI generation to runnable frontends |
| 17 | Bolt / StackBlitz agent 出荷頻度: 84 | In-browser full-stack generation |
| 18 | Devin-class autonomous eng agents 出荷頻度: 83 | Highly autonomous async eng-agent category |
| 19 | SWE-agent patterns 出荷頻度: 82 | Research-to-prod coding loop patterns |
| 20 | Sourcegraph Cody 出荷頻度: 81 | Code-graph-aware assistant |
RAG・記憶・知識
検索とセッション横断メモリ · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公式ドキュメント LlamaIndex DocsData/index-centric RAG framework
- 公式ドキュメント LangChain Retrieval DocsRetrieval-augmented concepts and components
- 公開API Pinecone API ReferenceVector DB public REST API
- 公開API Weaviate REST APIOpen-source vector DB REST API
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | LlamaIndex 成熟度: 100 | A default data framework for RAG apps |
| 2 | LangChain / LangGraph retrievers 成熟度: 99 | Broadest connector and chain retrieval ecosystem |
| 3 | Pinecone 成熟度: 98 | Managed vector DB common buy default |
| 4 | Qdrant 成熟度: 97 | Open high-performance vector store |
| 5 | Weaviate 成熟度: 96 | Hybrid search with modules |
| 6 | pgvector 成熟度: 95 | Vectors inside Postgres for existing PG stacks |
| 7 | Chroma 成熟度: 94 | Local-first vector store for prototypes |
| 8 | Elasticsearch vector 成熟度: 93 | Search+vector hybrid upgrade path |
| 9 | Voyage / Cohere embeddings 成熟度: 92 | High-quality embedding APIs |
| 10 | Docling / Unstructured 成熟度: 91 | Document parse-to-chunk entry |
| 11 | Firecrawl / web extract 成熟度: 90 | Web to clean markdown extraction |
| 12 | GraphRAG patterns 成熟度: 89 | Entity-graph retrieval patterns |
| 13 | Mem0 / agent memory libs 成熟度: 88 | Cross-session agent memory libraries |
| 14 | Azure AI Search 成熟度: 87 | Microsoft enterprise hybrid search |
| 15 | Vertex AI Search 成熟度: 86 | GCP enterprise RAG |
| 16 | NotebookLM class 成熟度: 85 | Source-grounded notebooks |
| 17 | Obsidian + AI plugins 成熟度: 84 | Personal knowledge base + AI |
| 18 | Zep / conversation memory 成熟度: 83 | Conversation long-term memory services |
| 19 | Code graphs (Tree-sitter / codegraph) 成熟度: 82 | Structural code retrieval vs pure vectors |
| 20 | Haystack pipelines 成熟度: 81 | Production NLP/RAG pipelines |
画像生成（現行）
2026の主要パス · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公式ドキュメント OpenAI Images APIOfficial OpenAI Python SDK (images API; marketing/docs often bot-403)
- 公開API Stability AI Platform APIStable Diffusion family public API
- 信頼サイト Black Forest Labs / FLUXFLUX official product site
- 公開API Replicate · text-to-imageMachine-readable image models + API (Midjourney main site often bot-403)
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | ChatGPT Images 2.0 / GPT Image 2 出荷可用性: 100 | Delivery-oriented high-res controllable images; stronger readable text |
| 2 | Grok / Imagine 出荷可用性: 99 | xAI image gen; usable style-reference edits |
| 3 | Flux family 出荷可用性: 98 | Open-weight photoreal main line |
| 4 | Midjourney v7 class 出荷可用性: 97 | Aesthetic still default |
| 5 | Ideogram 出荷可用性: 96 | Strong text-in-image layout |
| 6 | Imagen 3/4 出荷可用性: 95 | Google product image stack |
| 7 | Stable Diffusion 3.x 出荷可用性: 94 | Open ecosystem baseline |
| 8 | Adobe Firefly 出荷可用性: 93 | Brand-safe commercial licensing narrative |
| 9 | Recraft 出荷可用性: 92 | Design-system / vector-ish outputs |
| 10 | Leonardo 出荷可用性: 91 | Game/asset-oriented generation |
| 11 | ControlNet stacks 出荷可用性: 90 | Pose/depth/edge control |
| 12 | IP-Adapter / identity ref 出荷可用性: 89 | Character identity consistency |
| 13 | Kolors / CN diffusion 出荷可用性: 88 | Chinese aesthetic open routes |
| 14 | Playground class 出荷可用性: 87 | Design-friendly UI generation |
| 15 | Civitai community models 出荷可用性: 86 | Community fine-tune marketplace |
| 16 | SDXL Lightning / turbo 出荷可用性: 85 | Fast preview generation |
| 17 | Topaz / RealESRGAN upscalers 出荷可用性: 84 | Post-gen upscale finish |
| 18 | Background removal models 出荷可用性: 83 | E-commerce cutout necessity |
| 19 | Inpaint/outpaint toolchains 出荷可用性: 82 | Local repaint workflows |
| 20 | DALL·E lineage integrations 出荷可用性: 81 | Legacy integrations still inside many products |
動画とモーション
T2V/I2Vとトーキングヘッド · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開API Runway APIRunway developer API docs
- 公開API Luma Dream Machine APILuma video generation API
- 信頼サイト Kling AIKling product entry (public product surface)
- 信頼サイト OpenAI GitHub orgOpenAI public org repos (Sora/marketing pages often bot-403)
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Google Veo 3.x 利用パス: 100 | Google cinematic T2V/I2V main line; unified multimodal stack |
| 2 | Sora class 利用パス: 99 | High-end narrative T2V category (product entry still shifting) |
| 3 | Kling 利用パス: 98 | Common CN-market video generation |
| 4 | Runway Gen-3/4 利用パス: 97 | Creator video tool stack |
| 5 | Luma Dream Machine 利用パス: 96 | Accessible cinematic T2V |
| 6 | Pika 利用パス: 95 | Social short-form oriented |
| 7 | Hailuo / MiniMax video 利用パス: 94 | CN product video models |
| 8 | Seedance / ByteDance video 利用パス: 93 | ByteDance motion/video pipelines |
| 9 | Vidu class 利用パス: 92 | Multi-subject video |
| 10 | HeyGen 利用パス: 91 | Avatar presenter videos |
| 11 | Synthesia 利用パス: 90 | Enterprise training avatars |
| 12 | ElevenLabs + lipsync stacks 利用パス: 89 | Voice-driven lipsync stacks |
| 13 | Hedra / talking-head 利用パス: 88 | Portrait talking-head video |
| 14 | CapCut AI suite 利用パス: 87 | Mass-market edit + gen |
| 15 | Descript 利用パス: 86 | Transcript-first video edit |
| 16 | Remotion + AI assets 利用パス: 85 | Code-driven video |
| 17 | HyperFrames / card video 利用パス: 84 | Card short-video templates |
| 18 | Adobe Firefly Video 利用パス: 83 | Adobe brand-safe motion |
| 19 | Viggle / character motion 利用パス: 82 | Character motion transfer |
| 20 | Open-Sora / CogVideo class 利用パス: 81 | Open video research routes |
音声とオーディオ
TTS/STT/音楽/ボイスエージェント · top 20 · as_of 2026-07-22
情報源 / 公開API
- 信頼サイト OpenAI Whisper (GitHub)Official Whisper repo; Audio API docs often bot-403
- 公開API ElevenLabs APISpeech synthesis/cloning public API
- 公開API Deepgram APIRealtime speech recognition API
- 信頼サイト CartesiaLow-latency TTS product entry
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | ElevenLabs 本番採用: 100 | High-quality TTS/clone default |
| 2 | OpenAI Realtime / TTS 本番採用: 99 | Low-latency voice-agent path |
| 3 | Whisper family 本番採用: 98 | Open STT baseline |
| 4 | Deepgram 本番採用: 97 | Production STT APIs |
| 5 | AssemblyAI 本番採用: 96 | STT plus speech understanding |
| 6 | Cartesia 本番採用: 95 | Realtime voice generation |
| 7 | Azure Speech 本番採用: 94 | Enterprise STT/TTS |
| 8 | Google Cloud Speech 本番採用: 93 | GCP speech stack |
| 9 | Amazon Polly / Transcribe 本番採用: 92 | AWS default speech |
| 10 | Suno 本番採用: 91 | Mass-market music generation |
| 11 | Udio 本番採用: 90 | Music generation competitor |
| 12 | Play.ht / PlayAI 本番採用: 89 | Voice product stack |
| 13 | Resemble AI 本番採用: 88 | Enterprise voice clone |
| 14 | Descript Studio Sound 本番採用: 87 | Podcast denoise |
| 15 | FunASR / SenseVoice 本番採用: 86 | Chinese open STT |
| 16 | Fish Audio / CN TTS 本番採用: 85 | Chinese natural TTS |
| 17 | Coqui / open TTS 本番採用: 84 | Open voice models |
| 18 | WebRTC realtime voice bots 本番採用: 83 | Telephony-grade voice bots |
| 19 | Podcast AI digests 本番採用: 82 | Audio-to-summary pipelines |
| 20 | Audo / cleanup tools 本番採用: 81 | Audio cleanup tools |
評価・可観測・ガードレール
計測・追跡・制約 · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公式ドキュメント LangSmith Docs / APIAgent/LLM tracing and evaluation
- 公式ドキュメント Arize PhoenixOpen-source LLM observability
- 公開API Braintrust APIEval/logging public API
- 公開ランキング HELM (Stanford CRFM)Academic multi-scenario evaluation
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | LangSmith 運用準備: 100 | LangChain-family tracing and evals |
| 2 | Langfuse 運用準備: 99 | Open LLM observability |
| 3 | Phoenix / Arize 運用準備: 98 | ML+LLM monitoring |
| 4 | Braintrust 運用準備: 97 | Eval and logging platform |
| 5 | Promptfoo 運用準備: 96 | Prompt/regression testing |
| 6 | DeepEval 運用準備: 95 | Python eval framework |
| 7 | RAGAS 運用準備: 94 | RAG quality metrics |
| 8 | Helicone 運用準備: 93 | Gateway-layer observability |
| 9 | Weights & Biases Weave 運用準備: 92 | Experiment + LLM traces |
| 10 | OpenTelemetry GenAI 運用準備: 91 | Standardized tracing |
| 11 | Guardrails AI 運用準備: 90 | Output validators |
| 12 | NeMo Guardrails 運用準備: 89 | Dialog policy rails |
| 13 | Llama Guard (Meta) 運用準備: 88 | Safety classifier models |
| 14 | Presidio / PII redaction 運用準備: 87 | Privacy redaction |
| 15 | LiteLLM 運用準備: 86 | Unified model proxy |
| 16 | Portkey 運用準備: 85 | Gateway and fallback routing |
| 17 | Humanloop 運用準備: 84 | Prompt management |
| 18 | Sentry 運用準備: 83 | App+error observability (incl. AI integrations) |
| 19 | Garak (NVIDIA) 運用準備: 82 | LLM adversarial/red-team testing |
| 20 | OpenAI Evals 運用準備: 81 | Custom task eval patterns |
推論インフラ
モデルが実際に動く場所 · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公式ドキュメント vLLM DocsHigh-throughput open inference engine
- 公式ドキュメント Hugging Face TGIText Generation Inference docs
- 公開API Together AI Models APIHosted inference model catalog API
- 公開API Fireworks AI APIHosted inference public API
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | vLLM 配備現実: 100 | Default open high-throughput serving |
| 2 | TensorRT-LLM 配備現実: 99 | NVIDIA-optimized inference |
| 3 | Ollama 配備現実: 98 | Local model UX default |
| 4 | llama.cpp / GGUF 配備現実: 97 | CPU/GPU local quantization |
| 5 | MLX 配備現実: 96 | Apple Silicon inference |
| 6 | Fireworks AI 配備現実: 95 | Fast hosted open models |
| 7 | Together AI 配備現実: 94 | Open-model cloud |
| 8 | Groq 配備現実: 93 | Ultra-low-latency LPU inference |
| 9 | AWS Bedrock 配備現実: 92 | Enterprise multi-model hosted API |
| 10 | Azure OpenAI / AI Foundry 配備現実: 91 | Microsoft enterprise model platform |
| 11 | Vertex AI 配備現実: 90 | GCP model platform |
| 12 | Hugging Face TGI / Inference 配備現実: 89 | HF serving path |
| 13 | Modal 配備現実: 88 | Serverless GPU jobs |
| 14 | Replicate 配備現実: 87 | Model-as-API marketplace |
| 15 | Cloudflare Workers AI 配備現実: 86 | Edge inference |
| 16 | NVIDIA NIM 配備現実: 85 | Packaged enterprise inference microservices |
| 17 | SGLang 配備現実: 84 | Fast open serving |
| 18 | Kubernetes 配備現実: 83 | DIY production orchestration baseline |
| 19 | SkyPilot 配備現実: 82 | Multi-cloud GPU cluster orchestration |
| 20 | Anyscale / Ray 配備現実: 81 | Distributed train and serving |
AIプロダクトと成長形
2026に予算/流通を得やすい形 · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開レポート State of AI ReportAnnual industry survey (trend cross-check)
- 公開レポート a16z Generative AIa16z AI topic hub (old /generative-ai 404)
- 信頼サイト Product Hunt AIPublic launch signals for new products
- 信頼サイト GitHub TrendingPublic open-source heat list (not this map's ranks)
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Agentic coding workspaces 予算引力: 100 | Highest concentration of eng budgets |
| 2 | Vertical agents (legal/tax/health) 予算引力: 99 | Domain trust + workflow binding |
| 3 | Personal agent OS / second brain 予算引力: 98 | Daily habit and memory compounding |
| 4 | AI ads & UGC factories 予算引力: 97 | Performance-ad creative factories |
| 5 | AI landing-page generators 予算引力: 96 | Marketing landing-page throughput |
| 6 | Support copilots with tools 予算引力: 95 | Support ROI clear and billable |
| 7 | Meeting → action systems 予算引力: 94 | Calendar-native agents |
| 8 | Sales research agents 予算引力: 93 | Outbound/lead intelligence |
| 9 | Internal knowledge chat 予算引力: 92 | Default enterprise RAG delivery |
| 10 | Multimodal design suites 予算引力: 91 | Design-to-ship pipelines |
| 11 | Voice-first mobile agents 予算引力: 90 | Hands-free mobile scenarios |
| 12 | Computer-use automation 予算引力: 89 | Legacy GUI RPA upgrade |
| 13 | Eval-as-product dashboards 予算引力: 88 | Buyer trust layer |
| 14 | Open-weight private clouds 予算引力: 87 | Data-sovereignty procurement |
| 15 | AI education / cohort tools 予算引力: 86 | Creator/training monetization |
| 16 | Synthetic data platforms 予算引力: 85 | Training-flywheel infrastructure |
| 17 | Compliance-aware AI (audit trails) 予算引力: 84 | Regulated-industry entry ticket |
| 18 | Hardware + AI gadgets 予算引力: 83 | Edge-form-factor products |
| 19 | Skills / MCP tool marketplaces 予算引力: 82 | Ecosystem lock-in and distribution |
| 20 | Outcome-priced AI services 予算引力: 81 | Outcome pricing beyond seats |
AIリーダー地図（2026）
フォロワー数ではなく議題を定義する人 · top 20 · as_of 2026-07-22
情報源 / 公開API
- 信頼サイト Google DeepMindOfficial DeepMind org and research entry
- 公式ドキュメント Anthropic ResearchAnthropic public research and leadership context
- 信頼サイト OpenAI GitHub orgOpenAI public org repos (main research pages often bot-403)
- 信頼サイト meta-llama GitHubMeta Llama public org repos (ai.meta.com 400 for some clients)
- 信頼サイト X · @demishassabisDeepMind CEO public X
- 信頼サイト X · @samaOpenAI CEO public X
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Demis Hassabis (Google DeepMind) 議題影響力: 100 | Science+product dual narrative; Alpha lineage + Gemini control plane |
| 2 | Dario Amodei (Anthropic) 議題影響力: 99 | Safety/interpretability commercial flagship; Claude line |
| 3 | Sam Altman (OpenAI) 議題影響力: 98 | Platform distribution + capital narrative center; ChatGPT default |
| 4 | Yann LeCun (Meta FAIR / AMI Labs) 議題影響力: 97 | Open-source + world-model public debate bridge academia↔industry |
| 5 | Jensen Huang (NVIDIA) 議題影響力: 96 | De-facto tax rate of the compute supply chain |
| 6 | Ilya Sutskever (SSI) 議題影響力: 95 | Scaling+alignment legacy and next-gen SSI narrative |
| 7 | Mustafa Suleyman (Microsoft AI) 議題影響力: 94 | Consumer+enterprise dual stack; Copilot execution authority |
| 8 | Fei-Fei Li 議題影響力: 93 | Human-centered AI + vision foundations public voice |
| 9 | Geoffrey Hinton 議題影響力: 92 | Godfather-layer public risk voice; high policy weight |
| 10 | Yoshua Bengio 議題影響力: 91 | Safety/governance academic agenda-setting |
| 11 | Andrej Karpathy 議題影響力: 90 | Engineering education + product intuition mass amplifier |
| 12 | Satya Nadella (Microsoft) 議題影響力: 89 | CEO who ships frontier models into enterprise distribution |
| 13 | Mark Zuckerberg (Meta) 議題影響力: 88 | Open-weight + social distribution free-tier strategy |
| 14 | Elon Musk (xAI) 議題影響力: 87 | Realtime X data + Grok product alternate narrative center |
| 15 | Noam Shazeer 議題影響力: 86 | Transformer co-author → consumer-agent product path |
| 16 | Jared Kaplan (Anthropic) 議題影響力: 85 | Scaling-laws→alignment productization research leadership |
| 17 | Jim Fan (NVIDIA) 議題影響力: 84 | Public flagship for embodied/game agents research |
| 18 | Percy Liang (Stanford CRFM) 議題影響力: 83 | HELM-class measurable-trust eval infrastructure |
| 19 | Andrew Ng 議題影響力: 82 | Education + applied-AI global distribution layer |
| 20 | Oriol Vinyals (DeepMind) 議題影響力: 81 | Sequence models + multi-agent research leadership |
トップラボ / フロンティア組織
モデル・論文・スタック — 公式X付き · top 20 · as_of 2026-07-22
情報源 / 公開API
- 信頼サイト Google DeepMindTop-lab official entry
- 信頼サイト OpenAI (GitHub org)OpenAI public org repos (main site often bot-403)
- 信頼サイト AnthropicAnthropic org entry
- 信頼サイト meta-llama GitHubLlama weights/models public org repos
- 信頼サイト facebookresearch GitHubMeta FAIR open-source org repos
- 信頼サイト Microsoft Research AIMicrosoft Research AI public surface
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Google DeepMind システム影響: 100 | Science breakthrough + Gemini; Search/Cloud distribution |
| 2 | OpenAI システム影響: 99 | ChatGPT default entry; API + agent platform center |
| 3 | Anthropic システム影響: 98 | Claude long-horizon/safety stack; enterprise coding narrative |
| 4 | Meta FAIR / Superintelligence Labs システム影響: 97 | Llama open-weight default base; research→community flywheel |
| 5 | Microsoft Research / Microsoft AI システム影響: 96 | Copilot distribution + Azure hosting; enterprise buy path |
| 6 | xAI システム影響: 95 | Grok + X realtime surface; Imagine multimodal |
| 7 | NVIDIA Research / AI システム影響: 94 | Compute + NIM inference; supply choke point |
| 8 | Amazon Science / AWS AI システム影響: 93 | Bedrock multi-model shelf; default-visible in AWS accounts |
| 9 | Mistral AI システム影響: 92 | EU-compliance open/API dual track |
| 10 | DeepSeek システム影響: 91 | Open reasoning cost shock; private-deploy reference |
| 11 | Alibaba Qwen / Tongyi システム影響: 90 | Bilingual + tool-use ecosystem; open and cloud |
| 12 | Moonshot / Kimi システム影響: 89 | Strong Chinese long-context product |
| 13 | Cohere システム影響: 88 | Enterprise RAG/retrieval + Command line |
| 14 | Hugging Face システム影響: 87 | Model/dataset/Spaces distribution hub |
| 15 | Allen Institute for AI (AI2) システム影響: 86 | Open science path incl. OLMo-class models |
| 16 | Stanford CRFM システム影響: 85 | Eval×policy academic hub (HELM) |
| 17 | Stability AI システム影響: 84 | Image-gen open-weight and API product node |
| 18 | Black Forest Labs (FLUX) システム影響: 83 | FLUX image-gen research/product line |
| 19 | Perplexity システム影響: 82 | Retrieval-native chat product; active public eng narrative |
| 20 | Runway Research システム影響: 81 | Video-gen research+product; Gen-series public reference |
里程標論文 / 思想アンカー
各行が正規論文リンク · top 20 · as_of 2026-07-22
情報源 / 公開API
- 信頼サイト arXiv cs.AI / cs.LG / cs.CLPrimary paper distribution; verify by arXiv id
- 公開レポート Attention Is All You Need (arXiv:1706.03762)Canonical Transformer paper anchor
- 公開ランキング Papers with CodePaper↔code↔leaderboard cross-index
- 信頼サイト Semantic ScholarPublic citation and author-graph search
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Attention Is All You Need (Vaswani et al.) 思想遺産: 100 | Origin of the default Transformer architecture |
| 2 | Scaling Laws / Kaplan et al. 思想遺産: 99 | Start of predictable compute-data-params narrative |
| 3 | GPT-3 / few-shot learners 思想遺産: 98 | Public proof that large pretrain yields general ability |
| 4 | InstructGPT / RLHF 思想遺産: 97 | Productization path aligning to human preference |
| 5 | Constitutional AI (Anthropic) 思想遺産: 96 | Discussable blueprint for principle-based alignment |
| 6 | Chain-of-Thought prompting 思想遺産: 95 | Made reasoning an explicit controllable interface |
| 7 | ReAct (reason + act) 思想遺産: 94 | Default mental model for tool-using agents |
| 8 | LLaMA (Meta) 思想遺産: 93 | Turn where open weights became a default base |
| 9 | Chinchilla compute-optimal 思想遺産: 92 | Efficiency correction: data vs parameters |
| 10 | Diffusion / DDPM family 思想遺産: 91 | Image-gen main path shift GAN→diffusion |
| 11 | CLIP (OpenAI) 思想遺産: 90 | Vision-language shared representation into products |
| 12 | AlphaFold (DeepMind) 思想遺産: 89 | Undeniable science-AI achievement sample |
| 13 | FlashAttention 思想遺産: 88 | Feasibility jump for long-context train/serve |
| 14 | Mixture-of-Experts / Switch Transformers 思想遺産: 87 | Sparse activation scaling became mainstream |
| 15 | DPO (Direct Preference Optimization) 思想遺産: 86 | Widely adopted simplified alignment training path |
| 16 | Toolformer 思想遺産: 85 | Early clear demo of models learning to call APIs |
| 17 | Segment Anything (Meta) 思想遺産: 84 | Vision foundation model train-once multi-downstream template |
| 18 | Whisper (OpenAI) 思想遺産: 83 | One default open baseline for speech recognition |
| 19 | BERT (Devlin et al.) 思想遺産: 82 | Prior-gen turn: bidirectional pretrain as NLP industrial default |
| 20 | LoRA / PEFT family 思想遺産: 81 | Cheap adapters made private fine-tune a default move |
買い手が実際に引用するベンチ
各行が公式ボード/リポジトリ · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開ランキング LM Arena / Chatbot ArenaPublic Text/Code/Agent arena Elo boards
- 公開ランキング SWE-benchPublic software-engineering task board
- 公開ランキング HELM (Stanford CRFM)Academic multi-scenario evaluation
- 公開ランキング Artificial AnalysisQuality×speed×price comparison
- 公開ランキング MLPerfIndustry hardware/inference throughput yardstick
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | LM Arena / Chatbot Arena Elo 意思決定引用率: 100 | Public arena perceived quality; often cited in sales (arena.ai) |
| 2 | SWE-bench / SWE-bench Verified 意思決定引用率: 99 | Real software tasks; coding-agent purchase yardstick |
| 3 | HumanEval 意思決定引用率: 98 | Classic code-gen yardstick (OpenAI) |
| 4 | LiveCodeBench 意思決定引用率: 97 | Continuously updated code-gen board |
| 5 | MMLU 意思決定引用率: 96 | Multi-subject knowledge default (watch saturation) |
| 6 | GPQA 意思決定引用率: 95 | Hard science QA; real-reasoning cross-check |
| 7 | MATH dataset 意思決定引用率: 94 | Math-reasoning strength cross-check |
| 8 | HELM (Stanford CRFM) 意思決定引用率: 93 | Multi-scenario reproducible academic eval framework |
| 9 | Artificial Analysis 意思決定引用率: 92 | Quality×speed×price three-axis purchase view |
| 10 | Open LLM Leaderboard (HF) 意思決定引用率: 91 | Open-weight public comparison entry |
| 11 | τ-bench (tool-agent) 意思決定引用率: 90 | Tool-use reliability; critical for agent products |
| 12 | WebArena 意思決定引用率: 89 | Browser-agent task completion |
| 13 | MMMU benchmark 意思決定引用率: 88 | Multimodal understanding purchase view |
| 14 | VBench 意思決定引用率: 87 | Video-gen perception and consistency |
| 15 | Common Voice (ASR data) 意思決定引用率: 86 | Public ASR corpus/entry point |
| 16 | RAGAS 意思決定引用率: 85 | RAG faithfulness and retrieval quality |
| 17 | AgentBoard 意思決定引用率: 84 | Multi-agent task composite board |
| 18 | BIG-bench 意思決定引用率: 83 | Prior-gen composite ability (legacy yardstick) |
| 19 | MLPerf Inference 意思決定引用率: 82 | Hardware/serving throughput industry yardstick |
| 20 | LMSYS Chatbot Arena paper 意思決定引用率: 81 | Arena methodology paper (how to read Elo) |
Product Hunt · AIプロダクト索引
ローンチ面でよく名指しされるAI製品——各行ホームリンク · top 20 · as_of 2026-07-22
情報源 / 公開API
- 信頼サイト Product Hunt · Artificial IntelligenceMaster index of AI product launches
- 信頼サイト Product Hunt · AI homepageLaunch-surface home
- 信頼サイト Product Hunt on XOfficial Product Hunt X
- 公開レポート Y Combinator Library (launch context)Launch/growth narrative cross-reads
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | ChatGPT 流通ヒート: 100 | Default chat entry; launch-narrative center |
| 2 | Claude 流通ヒート: 99 | Long-form/coding chat product surface |
| 3 | Cursor 流通ヒート: 98 | AI IDE path from launch to mainstream |
| 4 | Perplexity 流通ヒート: 97 | Retrieval-native answer engine; strong distribution narrative |
| 5 | v0 (Vercel) 流通ヒート: 96 | UI-gen→deployable launch product template |
| 6 | Lovable 流通ヒート: 95 | NL→full-stack app PH-hot product shape |
| 7 | Bolt.new 流通ヒート: 94 | In-browser one-shot full-stack prototypes |
| 8 | Gamma 流通ヒート: 93 | AI decks/docs launch tool |
| 9 | Notion AI 流通ヒート: 92 | Workspace-native writing/Q&A |
| 10 | Raycast AI 流通ヒート: 91 | Launcher-native AI command layer |
| 11 | Linear 流通ヒート: 90 | Eng project management + AI assist |
| 12 | ElevenLabs 流通ヒート: 89 | Voice gen/clone product surface |
| 13 | Suno 流通ヒート: 88 | Mass-market music-gen launch breakout shape |
| 14 | Runway 流通ヒート: 87 | Creator video-gen tool stack |
| 15 | Ideogram 流通ヒート: 86 | Text-in-image friendly image product |
| 16 | Replicate 流通ヒート: 85 | Model-as-API marketplace; dev distribution |
| 17 | Hugging Face 流通ヒート: 84 | Model/Spaces community distribution hub |
| 18 | Descript 流通ヒート: 83 | Transcript-first A/V product |
| 19 | Midjourney 流通ヒート: 82 | Aesthetic still-gen mass entry (main site often bot-walled) |
| 20 | Product Hunt AI topic 流通ヒート: 81 | Master index of AI launches (topic page) |
Apple App Store · AIアプリ索引
iOSの主要AI入口——各行App Storeリンク · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開ランキング App Store · iPhone ChartsOfficial iPhone charts entry (cross-check)
- 信頼サイト App Store · ProductivityProductivity category (AI assistants frequent)
- 公式ドキュメント Apple Developer · App StoreApp Store product and distribution rules
- 公開レポート Sensor Tower (industry charts)Third-party store intel cross-check (account may be required)
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | ChatGPT ストア可視性: 100 | Default consumer chat entry |
| 2 | Claude by Anthropic ストア可視性: 99 | Long-form/coding assistant on iOS |
| 3 | Google Gemini ストア可視性: 98 | Google multimodal assistant entry |
| 4 | Microsoft Copilot ストア可視性: 97 | Microsoft assistant + OS integration narrative |
| 5 | Grok ストア可視性: 96 | xAI assistant; X-ecosystem distribution |
| 6 | Perplexity ストア可視性: 95 | Retrieval-native Q&A mobile entry |
| 7 | Character.AI ストア可視性: 94 | Character-chat consumer breakout shape |
| 8 | PhotoRoom AI Photo Editor ストア可視性: 93 | E-commerce/cutout AI photo edit |
| 9 | Remini – AI Photo Enhancer ストア可視性: 92 | Photo upscale/enhance breakout |
| 10 | Lensa: AI Photo & Video Editor ストア可視性: 91 | Portrait stylization AI editor |
| 11 | FaceApp: Face Editor ストア可視性: 90 | Face-transform AI filters |
| 12 | CapCut – Video Editor ストア可視性: 89 | Short-video edit + AI features |
| 13 | Canva: AI Photo & Video Editor ストア可視性: 88 | Design templates + generative features |
| 14 | Grammarly Keyboard ストア可視性: 87 | Writing-assistant keyboard layer |
| 15 | Duolingo ストア可視性: 86 | Language learning + AI conversation |
| 16 | Speak: Language Learning ストア可視性: 85 | Speaking-practice AI coach |
| 17 | Notion ストア可視性: 84 | Notes/wiki + Notion AI |
| 18 | starryai – AI Art Generator ストア可視性: 83 | Text-to-image consumer entry |
| 19 | Wondershare Wonder AI Art ストア可視性: 82 | AI art generation consumer tool |
| 20 | Microsoft 365 (Copilot surface) ストア可視性: 81 | Office suite Copilot distribution surface |
Google Play · AIアプリ索引
Androidの主要AI入口——各行Play詳細 · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開ランキング Google Play · Top chartsOfficial top charts entry (cross-check)
- 信頼サイト Google Play · ProductivityProductivity category (AI assistants frequent)
- 公式ドキュメント Google Play Console helpPlay distribution and listing docs
- 公開レポート Sensor Tower (industry charts)Third-party store intel cross-check (account may be required)
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | ChatGPT ストア可視性: 100 | Default consumer chat entry |
| 2 | Claude by Anthropic ストア可視性: 99 | Long-form/coding assistant on Android |
| 3 | Google Gemini ストア可視性: 98 | Google multimodal assistant entry |
| 4 | Microsoft Copilot ストア可視性: 97 | Microsoft assistant Android entry |
| 5 | Grok ストア可視性: 96 | xAI assistant; X-ecosystem distribution |
| 6 | Perplexity ストア可視性: 95 | Retrieval-native Q&A mobile entry |
| 7 | Character.AI ストア可視性: 94 | Character-chat consumer breakout shape |
| 8 | PhotoRoom ストア可視性: 93 | E-commerce/cutout AI photo edit |
| 9 | Remini ストア可視性: 92 | Photo upscale/enhance breakout |
| 10 | Lensa ストア可視性: 91 | Portrait stylization AI editor |
| 11 | FaceApp ストア可視性: 90 | Face-transform AI filters |
| 12 | CapCut ストア可視性: 89 | Short-video edit + AI features |
| 13 | Canva ストア可視性: 88 | Design templates + generative features |
| 14 | Grammarly Keyboard ストア可視性: 87 | Writing-assistant keyboard layer |
| 15 | Duolingo ストア可視性: 86 | Language learning + AI conversation |
| 16 | Notion ストア可視性: 85 | Notes/wiki + Notion AI |
| 17 | Microsoft 365 (Office) ストア可視性: 84 | Office suite Copilot distribution surface |
| 18 | Background Eraser / remove.bg class ストア可視性: 83 | Background-removal AI tools |
| 19 | starryai (Play search) ストア可視性: 82 | Text-to-image consumer entry (search index) |
| 20 | Speak-class language AI (Play search) ストア可視性: 81 | Speaking AI coach category index |
Xホットトピック · AI
X上の主要AI議題——各行検索/ハッシュタグ · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開ランキング X ExploreX Explore entry (live trends often login-gated; this board is an editorial topic index)
- 信頼サイト X Advanced SearchAdvanced search for reproducible topic queries
- 公式ドキュメント X Developer PlatformOfficial API docs (trends/search need access)
- 信頼サイト X AI search (sample query)Sample live AI keyword search
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | AI Agents 議題ヒート: 100 | Autonomous agents / tool-use as main narrative |
| 2 | Claude / Anthropic 議題ヒート: 99 | Long-form, coding, and safety narrative center |
| 3 | ChatGPT / OpenAI 議題ヒート: 98 | Default chat entry and release-cadence talk |
| 4 | Grok / xAI 議題ヒート: 97 | X-native assistant and model-release talk |
| 5 | Gemini / Google AI 議題ヒート: 96 | Multimodal and search-integration agenda |
| 6 | DeepSeek 議題ヒート: 95 | Open-weight / efficient-training contrast narrative |
| 7 | Open-weight LLMs 議題ヒート: 94 | Qwen / Kimi / Mistral open-weight wave |
| 8 | MCP (Model Context Protocol) 議題ヒート: 93 | Tool-interop standard as infrastructure talk |
| 9 | Cursor / AI IDE 議題ヒート: 92 | In-editor coding-agent product surface |
| 10 | AI Video Generation 議題ヒート: 91 | Sora / Kling / Seedance-class video gen |
| 11 | Image Gen / Flux 議題ヒート: 90 | T2I aesthetics and local-model discussion |
| 12 | Voice AI / Realtime 議題ヒート: 89 | Realtime voice assistants and call automation |
| 13 | AI Memory / Personalization 議題ヒート: 88 | Memory and personalization as product competition |
| 14 | Local / On-device AI 議題ヒート: 87 | On-device and local inference feasibility |
| 15 | AI Jobs / Automation 議題ヒート: 86 | Jobs and knowledge-labor automation agenda |
| 16 | AI Safety (near-term) 議題ヒート: 85 | Near-term safety / bio / cyber risk talk |
| 17 | Evals / Arena 議題ヒート: 84 | Public arena and purchase-eval yardsticks |
| 18 | RAG / Knowledge 議題ヒート: 83 | RAG and enterprise knowledge bases |
| 19 | AI Regulation 議題ヒート: 82 | Policy, copyright, and deployment compliance |
| 20 | Multimodal / World Models 議題ヒート: 81 | Multimodal and world-model frontier narrative |
Reddit · AIホットトピック
AIコミュニティ主要議題——subreddit/hot検索 · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開ランキング r/MachineLearning hotML research community hot feed
- 公開ランキング r/LocalLLaMA hotLocal/open-weight LLM practice hot feed
- 信頼サイト Reddit search · AISitewide AI hot search
- 公式ドキュメント Reddit API wiki (archive)Public API wiki archive (programmatic charts need compliance; reddit.com/dev often bot-blocked)
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | r/MachineLearning · hot コミュニティヒート: 100 | Papers, methods, and review-culture main community |
| 2 | r/LocalLLaMA · hot コミュニティヒート: 99 | Local models / quant / hardware practice |
| 3 | r/OpenAI · hot コミュニティヒート: 98 | ChatGPT/API product and policy talk |
| 4 | r/ClaudeAI · hot コミュニティヒート: 97 | Claude product use and comparisons |
| 5 | r/ChatGPT · hot コミュニティヒート: 96 | Mass-market chat product experience feedback |
| 6 | r/singularity · hot コミュニティヒート: 95 | Long-run capability curve and social-impact narrative |
| 7 | r/artificial · hot コミュニティヒート: 94 | General AI news and discussion |
| 8 | r/StableDiffusion · hot コミュニティヒート: 93 | Open image-gen workflows |
| 9 | r/midjourney · hot コミュニティヒート: 92 | Aesthetic stills and prompt culture |
| 10 | r/LangChain · hot コミュニティヒート: 91 | Orchestration / tool-chain engineering practice |
| 11 | r/Oobabooga · hot コミュニティヒート: 90 | Local WebUI inference stack |
| 12 | r/LocalAI · hot コミュニティヒート: 89 | Self-hosted inference and API-compat layers |
| 13 | r/PromptEngineering · hot コミュニティヒート: 88 | Prompt and system-instruction craft |
| 14 | r/MLOps · hot コミュニティヒート: 87 | Train/deploy/monitor productionization |
| 15 | r/computervision · hot コミュニティヒート: 86 | Vision models and applications |
| 16 | Coding agents (Reddit search) コミュニティヒート: 85 | Cursor/Copilot/agent coding heat |
| 17 | AI video gen (Reddit search) コミュニティヒート: 84 | Video-gen models and tools discussion |
| 18 | RAG / memory (Reddit search) コミュニティヒート: 83 | RAG and long-term memory practice |
| 19 | Open-weight models (Reddit search) コミュニティヒート: 82 | Open-weight releases and benchmark contrast |
| 20 | AI jobs / automation (Reddit search) コミュニティヒート: 81 | Jobs and workflow-replacement talk |
GitHub · AIリポジトリ索引
主要OSS AIリポジトリ——各行GitHub · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公開ランキング GitHub TrendingOfficial Trending entry (cross-check; not AI-only)
- 公開ランキング GitHub topic · artificial-intelligenceAI topic repository aggregation
- 公開レポート OSSInsight · Trending AI ReposThird-party AI repo trend cross-check
- 公式ドキュメント GitHub REST API docsProgrammatic stars/search entry
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | ollama/ollama エコ可視性: 100 | Local model runtime; Docker-like one-shot pull |
| 2 | ggml-org/llama.cpp エコ可視性: 99 | CPU/GPU local quantized inference base |
| 3 | huggingface/transformers エコ可視性: 98 | Default model load/train library |
| 4 | vllm-project/vllm エコ可視性: 97 | High-throughput open serving |
| 5 | sgl-project/sglang エコ可視性: 96 | Fast structured-generation serving |
| 6 | langchain-ai/langchain エコ可視性: 95 | Default app orchestration ecosystem |
| 7 | langchain-ai/langgraph エコ可視性: 94 | Stateful agent-graph runtime |
| 8 | openai/codex エコ可視性: 93 | Terminal/repo coding-agent reference |
| 9 | Aider-AI/aider エコ可視性: 92 | Git-native pair-programming agent |
| 10 | All-Hands-AI/OpenHands エコ可視性: 91 | Open software-engineering agent platform |
| 11 | cline/cline エコ可視性: 90 | IDE-side autonomous coding agent |
| 12 | continuedev/continue エコ可視性: 89 | Open IDE autocomplete/agent extension |
| 13 | modelcontextprotocol/servers エコ可視性: 88 | MCP official/community server collection |
| 14 | comfyanonymous/ComfyUI エコ可視性: 87 | Node-based image/video gen workflows |
| 15 | open-webui/open-webui エコ可視性: 86 | Self-hosted ChatGPT-style frontend |
| 16 | langgenius/dify エコ可視性: 85 | Visual LLM app/workflow platform |
| 17 | n8n-io/n8n エコ可視性: 84 | Workflow automation + AI nodes |
| 18 | deepseek-ai/DeepSeek-V3 エコ可視性: 83 | Open-weight frontier model release anchor |
| 19 | QwenLM/Qwen3 エコ可視性: 82 | Qwen open-model series entry |
| 20 | microsoft/autogen エコ可視性: 81 | Multi-agent conversation framework |
AI Skills · エコ索引
Agent/Claude Skillsと配信面——docs/repo · top 20 · as_of 2026-07-22
情報源 / 公開API
- 公式ドキュメント Anthropic · Agent Skills overviewOfficial Agent Skills concept and format
- 信頼サイト anthropics/skills (GitHub)Anthropic public skills sample repo
- 公開ランキング AgentSkill.sh directoryThird-party skill discovery directory (not an official store)
- 信頼サイト ClawHubOpenClaw-family skill distribution surface
| # | 名称 | 地図に載る理由 |
|---|---|---|
| 1 | Anthropic Agent Skills (docs) 配信可視性: 100 | Official skill format and usage contract |
| 2 | anthropics/skills 配信可視性: 99 | Official public skill sample repo |
| 3 | vercel-labs/agent-skills 配信可視性: 98 | Engineering-oriented agent skills pack (Vercel) |
| 4 | awesome-claude-skills 配信可視性: 97 | Curated Claude skills list |
| 5 | AgentSkill.sh 配信可視性: 96 | Third-party skill discovery directory |
| 6 | ClawHub 配信可視性: 95 | OpenClaw-family skill distribution surface |
| 7 | modelcontextprotocol/servers 配信可視性: 94 | MCP servers as pluggable tool-skill layer |
| 8 | GitHub Skills 配信可視性: 93 | Official GitHub interactive learning skills |
| 9 | openai/codex 配信可視性: 92 | Codex runtime + extension/skill surface |
| 10 | Aider-AI/aider 配信可視性: 91 | In-repo coding-skill habit reference |
| 11 | cline/cline 配信可視性: 90 | IDE agent skill/tool composition surface |
| 12 | continuedev/continue 配信可視性: 89 | Open IDE extension skill ecosystem |
| 13 | crewAIInc/crewAI 配信可視性: 88 | Multi-role agent skill orchestration |
| 14 | microsoft/autogen 配信可視性: 87 | Conversational multi-agent skill composition |
| 15 | langchain-ai/langgraph 配信可視性: 86 | Graph state machine for reusable sub-skills |
| 16 | All-Hands-AI/OpenHands 配信可視性: 85 | Software-engineering agent skill platform |
| 17 | firecrawl/firecrawl 配信可視性: 84 | Web-crawl skill (agent data ingress) |
| 18 | BerriAI/litellm 配信可視性: 83 | Multi-model routing skill middleware |
| 19 | langgenius/dify 配信可視性: 82 | Visual workflow as composable skill canvas |
| 20 | n8n-io/n8n 配信可視性: 81 | Automation node skill library |
Live secondary evidence (GitHub · not editorial rank)
- ollama/ollama ★ 176621 · forks 17060
- ggml-org/llama.cpp ★ 121254 · forks 20878
- huggingface/transformers ★ 162835 · forks 33973
- vllm-project/vllm ★ 86861 · forks 19703
- sgl-project/sglang ★ 30622 · forks 7323
- langchain-ai/langchain ★ 142318 · forks 23678
- langchain-ai/langgraph ★ 37847 · forks 6346
- openai/codex ★ 100606 · forks 15062
- Aider-AI/aider ★ 47613 · forks 4749
- All-Hands-AI/OpenHands ★ 81682 · forks 10443
- cline/cline ★ 64924 · forks 6967
- continuedev/continue ★ 35026 · forks 5090
snapshot 2026-07-22T11:13:50.347893+00:00 · secondary only