{"schema_version":"onlylabs.public_signal.v1","title":"InclusionAI (Ant Group) Model: inclusionAI/LLaDA2.0-flash-CAP","description":"InclusionAI (Ant Group) model signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/06c73646-e48b-4526-93ed-21e061a7dc76","json_url":"https://onlylabs.fyi/signals/06c73646-e48b-4526-93ed-21e061a7dc76/signal.json","generated_at":"2026-06-11T02:49:49.610923+00:00","org":{"slug":"inclusionai","name":"InclusionAI (Ant Group)","category":"neolab","category_label":"Neolab","dossier_url":"https://onlylabs.fyi/labs/inclusionai","dossier_json_url":"https://onlylabs.fyi/labs/inclusionai/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/06c73646-e48b-4526-93ed-21e061a7dc76","signal_json":"https://onlylabs.fyi/signals/06c73646-e48b-4526-93ed-21e061a7dc76/signal.json","source":"https://huggingface.co/inclusionAI/LLaDA2.0-flash-CAP","lab_dossier":"https://onlylabs.fyi/labs/inclusionai","lab_dossier_json":"https://onlylabs.fyi/labs/inclusionai/dossier.json","analysis":"https://onlylabs.fyi/analysis/inclusionai","analysis_json":"https://onlylabs.fyi/analysis/inclusionai/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/inclusionai/evidence.json","category":"https://onlylabs.fyi/neolabs","category_json":"https://onlylabs.fyi/neolabs.json","category_feed":"https://onlylabs.fyi/neolabs/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json?category=neolab","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml?category=neolab","data_business":null},"answer_pack":{"answer":"InclusionAI (Ant Group) published inclusionAI/LLaDA2.0-flash-CAP. 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Built upon the 100B-A6B Mixture-of-Experts (MoE) diffusion architecture, this model achieves faster parallel decoding while maintaining strong performance across diverse benchmarks. Experience the models at ZenMux（ https://zenmux.ai ） --- 📊 Performance Comparison Efficiency vs. Quality Trade-off | Model | Average Score | Tokens/Forward (TPF) | Speedup | | :---: | :---: | :---: | :---: | | LLaDA2.0-flash | 78.57 | 3.19 | 1.0× | | **LLaDA2.0-flash-CAP** | **76.85** | **4.65** | **1.46×** | _Evaluated on 12 diverse benchmarks covering knowledge, reasoning, coding, and mathematics._ Key Insights + **1.46× faster generation** with only a 1.72% performance trade-off + Ideal for latency-sensitive applications requiring real-time responses + Maintains competitive accuracy across all task categories --- 🔬 What is CAP Training? **Confidence-Aware Parallel (CAP) Training** is a novel training..."},"evidence_pages":[{"url":"https://huggingface.co/inclusionAI/LLaDA2.0-flash-CAP/raw/main/README.md","final_url":"https://huggingface.co/inclusionAI/LLaDA2.0-flash-CAP/raw/main/README.md","title":"inclusionAI/LLaDA2.0-flash-CAP model card","http_status":200,"content_type":"text/plain; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T02:49:49.610923+00:00","bytes":5729,"raw_path":"8dfdcddeb9bec8d4923f40bee95e6ae72b8259787520938f340c4cb5cad42ffa.md","content_hash":"b68760487771f983c6a173e00f38512b82b802316659002c94d535302e716aa4","excerpt_chars":1200,"truncated":true,"excerpt":"--- license: apache-2.0 library_name: transformers tags: - dllm - diffusion - llm - text_generation --- LLaDA2.0-flash-CAP **LLaDA2.0-flash-CAP** is an enhanced version of LLaDA2.0-flash that incorporates **Confidence-Aware Parallel (CAP) Training** for significantly improved inference efficiency. Built upon the 100B-A6B Mixture-of-Experts (MoE) diffusion architecture, this model achieves faster parallel decoding while maintaining strong performance across diverse benchmarks. Experience the models at ZenMux（ https://zenmux.ai ） --- 📊 Performance Comparison Efficiency vs. Quality Trade-off | Model | Average Score | Tokens/Forward (TPF) | Speedup | | :---: | :---: | :---: | :---: | | LLaDA2.0-flash | 78.57 | 3.19 | 1.0× | | **LLaDA2.0-flash-CAP** | **76.85** | **4.65** | **1.46×** | _Evaluated on 12 diverse benchmarks covering knowledge, reasoning, coding, and mathematics._ Key Insights + **1.46× faster generation** with only a 1.72% performance trade-off + Ideal for latency-sensitive applications requiring real-time responses + Maintains competitive accuracy across all task categories --- 🔬 What is CAP Training? **Confidence-Aware Parallel (CAP) Training** is a novel training..."}],"related_signals":[{"id":"107f41df-b146-4e20-b2f3-fe20b0beba2f","url":"https://onlylabs.fyi/signals/107f41df-b146-4e20-b2f3-fe20b0beba2f","source_url":"https://huggingface.co/inclusionAI/ARGenSeg-8B","title":"inclusionAI/ARGenSeg-8B","context":null,"kind":{"key":"model_released","label":"Model"},"org":{"slug":"inclusionai","name":"InclusionAI (Ant Group)","category":"neolab"},"occurred_at":"2026-05-15T02:33:52+00:00","first_seen_at":"2026-06-06T01:49:59.745196+00:00","date_source":"source"},{"id":"dde86c8e-76c3-4d1e-83d6-49cf5c3f4ffb","url":"https://onlylabs.fyi/signals/dde86c8e-76c3-4d1e-83d6-49cf5c3f4ffb","source_url":"https://huggingface.co/inclusionAI/Ring-2.6-1T","title":"inclusionAI/Ring-2.6-1T","context":null,"kind":{"key":"model_released","label":"Model"},"org":{"slug":"inclusionai","name":"InclusionAI (Ant Group)","category":"neolab"},"occurred_at":"2026-05-14T08:10:02+00:00","first_seen_at":"2026-06-06T01:49:59.745196+00:00","date_source":"source"},{"id":"d6c4a960-010a-4ca7-8e50-d0daac87bfaf","url":"https://onlylabs.fyi/signals/d6c4a960-010a-4ca7-8e50-d0daac87bfaf","source_url":"https://huggingface.co/inclusionAI/LLaDA2.0-Uni-FP8","title":"inclusionAI/LLaDA2.0-Uni-FP8","context":null,"kind":{"key":"model_released","label":"Model"},"org":{"slug":"inclusionai","name":"InclusionAI (Ant Group)","category":"neolab"},"occurred_at":"2026-05-06T08:03:43+00:00","first_seen_at":"2026-06-06T01:49:59.745196+00:00","date_source":"source"},{"id":"d56c53e5-d719-424a-964b-24995a3277c7","url":"https://onlylabs.fyi/signals/d56c53e5-d719-424a-964b-24995a3277c7","source_url":"https://huggingface.co/inclusionAI/Ling-2.6-1T","title":"inclusionAI/Ling-2.6-1T","context":null,"kind":{"key":"model_released","label":"Model"},"org":{"slug":"inclusionai","name":"InclusionAI (Ant Group)","category":"neolab"},"occurred_at":"2026-04-29T03:19:36+00:00","first_seen_at":"2026-06-06T01:49:59.745196+00:00","date_source":"source"},{"id":"5f271d7b-0454-436e-b047-20873d891685","url":"https://onlylabs.fyi/signals/5f271d7b-0454-436e-b047-20873d891685","source_url":"https://huggingface.co/inclusionAI/Ling-2.6-flash","title":"inclusionAI/Ling-2.6-flash","context":null,"kind":{"key":"model_released","label":"Model"},"org":{"slug":"inclusionai","name":"InclusionAI (Ant Group)","category":"neolab"},"occurred_at":"2026-04-28T03:27:56+00:00","first_seen_at":"2026-06-06T01:49:59.745196+00:00","date_source":"source"},{"id":"34bceb00-128e-426c-9c45-ec7f6b585baa","url":"https://onlylabs.fyi/signals/34bceb00-128e-426c-9c45-ec7f6b585baa","source_url":"https://huggingface.co/inclusionAI/LLaDA2.0-Uni","title":"inclusionAI/LLaDA2.0-Uni","context":null,"kind":{"key":"model_released","label":"Model"},"org":{"slug":"inclusionai","name":"InclusionAI (Ant Group)","category":"neolab"},"occurred_at":"2026-04-22T17:10:47+00:00","first_seen_at":"2026-06-06T01:49:59.745196+00:00","date_source":"source"}]}