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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 Opus 4.7AnthropicRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
claude-opus-4-7 vs nemotron-3.5-super-vl:free
AttributeClaude Opus 4.7claude-opus-4-7Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free
Pricing
Input$5.00 / 1M$0 / 1M
Output$25.00 / 1M$0 / 1M
Cache Write (5m)$6.25 / 1M—
Cache Write (1h)$10.00 / 1M—
Cache Read$0.50 / 1M$0 / 1M
Web Search$0 / 1M—
Cache Write—$0 / 1M
Context
Max context1M1M
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderAnthropicNVIDIA
Categorychatchat
Charge typePay As You GoFree
Released——
Description
SummaryOpus 4.7 is the next generation of Anthropic's Opus family, designed for long-running, asynchronous agent workflows. Building on Opus 4.6, it delivers stronger performance on complex, multi-step tasks and more reliable execution across extended pipelines such as large codebases, multi-stage debugging, and end-to-end project orchestration. Beyond coding, Opus 4.7 enhances knowledge work capabilities, including document drafting, presentation creation, and data analysis. With strong coherence over long outputs and sessions, it is well suited for tasks requiring persistence, judgment, and sustained execution.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.