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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Claude Fable 5.2AnthropicRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
  3. o3 Deep ResearchOpenAIRemove
claude-fable-5.2 vs nemotron-3.5-super-vl:free vs o3-deep-research
AttributeClaude Fable 5.2claude-fable-5.2Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeo3 Deep Researcho3-deep-research
Pricing
Input$8.00 / 1M$0 / 1M$10.00 / 1M
Output$40.00 / 1M$0 / 1M$40.00 / 1M
Cache Write (5m)$10.00 / 1M—$10.00 / 1M
Cache Write (1h)$16.00 / 1M—$10.00 / 1M
Cache Read$0.20 / 1M$0 / 1M$10.00 / 1M
Web Search$0 / 1M—$0 / 1M
Cache Write—$0 / 1M—
Context
Max context1M1M200K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicNVIDIAOpenAI
Categorychatchatchat
Charge typePay As You GoFreePay As You Go
Released———
Description
SummaryClaude Fable 5.2 is Anthropic's most capable model for advanced technical work and open-ended problem solving, delivering significant improvements in coding, reasoning, and vision over Fable 5.1. It excels at exceptionally complex tasks, including large-scale software migrations, electronic system design, and advanced scientific and mathematical research. With up to 30% faster output generation, clearer communication, and always-on adaptive extended thinking, Fable 5.2 supports configurable reasoning effort from low to max (default high), with thinking preserved across turns. Designed for frontier engineering, scientific discovery, and ambitious long-horizon agentic workflows, it complements Opus 5.5 as a specialized option for the most demanding technical challenges.NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications.o3-deep-research is OpenAI's advanced research model, built for complex, multi-step investigation and analysis. It automatically performs web searches to gather and synthesize information — but this always incurs additional cost since web_search is used by default.