{"ok":true,"source":"tensorfeed.ai","lastUpdated":"2026-04-30","modelCount":8,"modelCards":[{"id":"claude-opus-4-7","model":"Claude Opus 4.7","lab":"Anthropic","released":"2026-04-17","url":"https://www.anthropic.com/news/claude-opus-4-7","documents":[{"type":"system-card","title":"Claude Opus 4.7 System Card","publisher":"Anthropic","published":"2026-04-17","url":"https://www.anthropic.com/news/claude-opus-4-7","summary":"Anthropic's system card. Capability evaluations, ASL-3 deployment safeguards, autonomous-replication tests, CBRN uplift evaluations."},{"type":"autonomy-eval","title":"METR Pre-Deployment Evaluation: Claude Opus 4.7","publisher":"METR","published":"2026-04","url":"https://metr.org","summary":"Independent autonomy + long-horizon-task evaluation. Measures HCAST score against human-research-time baseline."}]},{"id":"claude-sonnet-4-6","model":"Claude Sonnet 4.6","lab":"Anthropic","released":"2026-02","url":"https://www.anthropic.com/claude/sonnet","documents":[{"type":"system-card","title":"Claude Sonnet 4.6 System Card","publisher":"Anthropic","published":"2026-02","url":"https://www.anthropic.com/news/claude-sonnet-4-6","summary":"Sonnet 4.6 system card. ASL-2 deployment, agentic-coding evaluations, computer-use safety considerations."},{"type":"red-team-report","title":"AISI Pre-Deployment Test: Claude Sonnet 4.6","publisher":"UK AI Safety Institute","published":"2026-02","url":"https://www.aisi.gov.uk","summary":"UK AISI red-team across cyber, biosecurity, autonomous-system uplift dimensions."}]},{"id":"gpt-5.5","model":"GPT-5.5","lab":"OpenAI","released":"2026-04","url":"https://openai.com/index/gpt-5-5/","documents":[{"type":"system-card","title":"GPT-5.5 System Card","publisher":"OpenAI","published":"2026-04","url":"https://openai.com/index/gpt-5-5-system-card/","summary":"OpenAI system card. Preparedness Framework risk levels (Cybersecurity, CBRN, Persuasion, Model Autonomy). Deployment mitigations."},{"type":"red-team-report","title":"Apollo Research: Scheming Capabilities of GPT-5.5","publisher":"Apollo Research","published":"2026-04","url":"https://www.apolloresearch.ai","summary":"Independent evaluation of in-context scheming, sandbagging, and goal-misalignment behaviors."},{"type":"preparedness-framework","title":"OpenAI Preparedness Framework v2","publisher":"OpenAI","published":"2025-04","url":"https://openai.com/safety/preparedness/","summary":"OpenAI's framework for evaluating frontier-model risk levels. Defines tracked risk categories and deployment thresholds."}]},{"id":"gpt-4o","model":"GPT-4o","lab":"OpenAI","released":"2024-05","url":"https://openai.com/index/hello-gpt-4o/","documents":[{"type":"system-card","title":"GPT-4o System Card","publisher":"OpenAI","published":"2024-08","url":"https://openai.com/index/gpt-4o-system-card/","summary":"GPT-4o system card. Voice mode safety, Preparedness scorecard, third-party red-teaming."},{"type":"red-team-report","title":"Apollo Research: GPT-4o Pre-Deployment Evaluation","publisher":"Apollo Research","published":"2024-08","url":"https://www.apolloresearch.ai","summary":"Apollo's pre-deployment scheming-capability evaluation."}]},{"id":"gemini-2.5-pro","model":"Gemini 2.5 Pro","lab":"Google DeepMind","released":"2026-01","url":"https://deepmind.google/technologies/gemini/","documents":[{"type":"model-card","title":"Gemini 2.5 Model Card","publisher":"Google DeepMind","published":"2026-01","url":"https://storage.googleapis.com/deepmind-media/gemini/gemini_v2_5_report.pdf","summary":"Gemini 2.5 Pro model card. Capability evals, Frontier Safety Framework risk assessment, dangerous-capability evaluations."},{"type":"preparedness-framework","title":"Frontier Safety Framework v2","publisher":"Google DeepMind","published":"2025-02","url":"https://deepmind.google/about/responsibility-safety/","summary":"DeepMind's framework for evaluating Critical Capability Levels. Deployment + security mitigations."}]},{"id":"llama-4-maverick","model":"Llama 4 Maverick","lab":"Meta","released":"2026-04","url":"https://ai.meta.com/blog/llama-4/","documents":[{"type":"model-card","title":"Llama 4 Maverick Model Card","publisher":"Meta","published":"2026-04","url":"https://ai.meta.com/blog/llama-4/","summary":"Llama 4 model card. Trust + safety evaluations, MLSafe and CyberSecEval scores, responsible-use guidance."}]},{"id":"llama-3.1-405b","model":"Llama 3.1 405B","lab":"Meta","released":"2024-07","url":"https://ai.meta.com/blog/meta-llama-3-1/","documents":[{"type":"model-card","title":"Llama 3.1 Model Card","publisher":"Meta","published":"2024-07","url":"https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md","summary":"Llama 3.1 model card with capability + safety evaluations across 8B, 70B, 405B variants."},{"type":"safety-eval","title":"CyberSecEval 3 (Llama 3.1)","publisher":"Meta","published":"2024-07","url":"https://meta-llama.github.io/PurpleLlama/CyberSecEval/","summary":"Cybersecurity evaluation suite. Code security, prompt injection, malicious-code-generation tests."}]},{"id":"deepseek-v4-pro","model":"DeepSeek V4 Pro","lab":"DeepSeek","released":"2026-04","url":"https://github.com/deepseek-ai/DeepSeek-V4","documents":[{"type":"model-card","title":"DeepSeek V4 Technical Report","publisher":"DeepSeek","published":"2026-04","url":"https://github.com/deepseek-ai/DeepSeek-V4/blob/main/DeepSeek_V4.pdf","summary":"DeepSeek V4 paper. Architecture, training, inference deployment, plus a brief safety evaluation section."}]}],"crossModelSafetyDocs":[{"id":"ai-incident-db","title":"AI Incident Database","publisher":"Responsible AI Collaborative","published":"ongoing","url":"https://incidentdatabase.ai","summary":"Public catalog of harms caused by AI systems. 1k+ incident reports indexed by severity, sector, and AI system involved.","type":"incident-database"},{"id":"oecd-ai-incidents","title":"OECD AI Incidents Monitor","publisher":"OECD","published":"ongoing","url":"https://oecd.ai/en/incidents","summary":"OECD's monitor of AI incidents and hazards reported in news media. Government-grade taxonomy.","type":"incident-database"},{"id":"mlsafe","title":"MLCommons AILuminate Safety Benchmark","publisher":"MLCommons","published":"2024-12","url":"https://mlcommons.org/benchmarks/ai-safety/","summary":"Industry-consortium safety benchmark. Tests harmful-content generation across 12 hazard categories.","type":"evaluation-suite"},{"id":"aisi-evals","title":"UK AI Safety Institute Evaluations","publisher":"UK AISI","published":"ongoing","url":"https://www.aisi.gov.uk","summary":"UK government pre-deployment red-team across cyber, biosecurity, autonomous-system, and political-influence dimensions.","type":"evaluation-suite"},{"id":"us-aisi","title":"US AI Safety Institute","publisher":"NIST AISI","published":"2024","url":"https://www.nist.gov/aisi","summary":"US government AI safety institute. Voluntary pre-deployment testing agreements with major labs (OpenAI, Anthropic).","type":"standard"},{"id":"anthropic-rsp","title":"Anthropic Responsible Scaling Policy","publisher":"Anthropic","published":"2024-10","url":"https://www.anthropic.com/news/announcing-our-updated-responsible-scaling-policy","summary":"Anthropic's framework defining AI Safety Level (ASL) thresholds and corresponding deployment safeguards.","type":"framework"},{"id":"openai-prep","title":"OpenAI Preparedness Framework v2","publisher":"OpenAI","published":"2025-04","url":"https://openai.com/safety/preparedness/","summary":"OpenAI's framework for tracking + mitigating frontier-model risks across Cybersecurity, CBRN, Persuasion, Model Autonomy.","type":"framework"},{"id":"frontier-safety-framework","title":"Google DeepMind Frontier Safety Framework v2","publisher":"Google DeepMind","published":"2025-02","url":"https://deepmind.google/about/responsibility-safety/","summary":"DeepMind's framework defining Critical Capability Levels and corresponding deployment mitigations.","type":"framework"},{"id":"metr-autonomy-eval","title":"METR Autonomy Evaluation Guide","publisher":"METR","published":"2024","url":"https://metr.github.io/autonomy-evals-guide/","summary":"Framework for evaluating long-horizon agentic capability against human-time-to-complete baselines (HCAST).","type":"evaluation-suite"},{"id":"apollo-evals","title":"Apollo Research Evaluations","publisher":"Apollo Research","published":"ongoing","url":"https://www.apolloresearch.ai","summary":"Independent evaluator focused on in-context scheming, sandbagging, deception, and goal-misalignment behaviors.","type":"evaluation-suite"}]}