Model Catalog•3 Architecture Specifications

AI Foundation Models

Explore frontier foundation models, verified benchmarks, 6-axis capability radar, hardware VRAM sizing, and real-time token pricing economics.

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Active Filters:Domain: VideoLab: AnthropicFormat: ProprietaryClear all
Anthropic/Reasoning
Proprietary API

Claude Opus 5.5

The frontier reasoning summit from Anthropic featuring a native 1-million-token context window, 92%+ SWE-bench Verified resolution, and hierarchical multi-agent verification.

Context Window1,000k ctx
Pricing In / Out\$10 / \$50
SWE-bench Verified92.1 % resolved
Overall DNA:98/100
Architecture & Specs
Anthropic/Reasoning
Proprietary API

Claude Opus 5

Anthropic's fifth-generation intelligence flagship, bringing full omni-modal audio/video/image capabilities, 500k context, and deep multi-hop self-critique reasoning.

Context Window500k ctx
Pricing In / Out\$10 / \$50
SWE-bench Verified89.4 % resolved
Overall DNA:97/100
Architecture & Specs
Anthropic/General
Proprietary API

Claude Fable 5.1

Anthropic's current flagship creative simulation and multimodal narrative agent, featuring adaptive emotional prosody, complex scenario branching, and multi-persona alignment.

Context Window500k ctx
Pricing In / Out\$5 / \$25
Chatbot Arena Elo1510 Elo
Overall DNA:93/100
Architecture & Specs

How to Choose the Right Foundation Model for RAG & AI Agents

Context Window for RAG

Retrieval-Augmented Generation (RAG) pipelines benefit from large context windows. Models like Gemini 1.5 Pro (2M tokens) and Claude 3.5 Sonnet (200k tokens) can ingest entire document corpora in a single pass, reducing chunk overlap and retrieval errors. For most RAG workloads, a 128k+ context window is sufficient.

Best Models for AI Agents

Agentic workloads require strong tool-use, function-calling, and instruction-following. GPT-4o and Claude 3.5 Sonnet consistently top agentic benchmarks like SWE-Bench and WebArena. For cost-efficient agents, GPT-4o mini and Claude 3.5 Haiku offer strong performance at a fraction of the price.

Open vs Proprietary for Production

Open-weight models (Llama 3, Mistral, Gemma) offer zero data-retention and full customisation via fine-tuning — ideal for regulated industries. Proprietary APIs (GPT-4o, Claude) trade control for frontier performance and zero infrastructure overhead. The choice depends on latency, cost, and compliance requirements.

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