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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. Perceptron Mk1.5PerceptronRemove
  2. Claude Fable 5.1AnthropicRemove
  3. Nemotron 3.5 Super VLNVIDIARemove
perceptron-mk1.5 vs claude-fable-5.1 vs nemotron-3.5-super-vl
AttributePerceptron Mk1.5perceptron-mk1.5Claude Fable 5.1claude-fable-5.1Nemotron 3.5 Super VLnemotron-3.5-super-vl
Pricing
Input$0.15 / 1M$10.00 / 1M$0.10 / 1M
Output$1.50 / 1M$50.00 / 1M$0.40 / 1M
Cache Write (5m)$0.15 / 1M$12.50 / 1M$0.10 / 1M
Cache Write (1h)$0.15 / 1M$20.00 / 1M$0.10 / 1M
Cache Read$0.15 / 1M$0.25 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context36.9K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingYesYesYes
Catalogue
ProviderPerceptronAnthropicNVIDIA
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-25——
Description
SummaryPerceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Claude Fable 5.1 is an upgraded version of Fable 5, delivering broad improvements with particularly strong gains in agentic coding, long-running workflows, and professional knowledge work. It excels at large code refactors, front-end and visual code generation, financial analysis, and complex analytical tasks. Compared with Fable 5, it also produces more concise plans and summaries while maintaining strong performance across extended tasks, making it a natural upgrade for existing Fable workflows and a strong option alongside Opus 5 for reasoning-intensive applications.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.