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Compare models

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

  1. GPT Image 2OpenAIRemove
  2. Nemotron 3.5 Super VLNVIDIARemove
  3. Muse Spark OpenMetaRemove
gpt-image-2 vs nemotron-3.5-super-vl vs muse-spark-open
AttributeGPT Image 2gpt-image-2Nemotron 3.5 Super VLnemotron-3.5-super-vlMuse Spark Openmuse-spark-open
Pricing
Request$0.04 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$0.10 / 1M$1.25 / 1M
Cache Write (1h)Not applicable$0.10 / 1M$1.25 / 1M
Cache ReadNot applicable$0.10 / 1M$1.25 / 1M
Input—$0.10 / 1M$1.25 / 1M
Output—$0.40 / 1M$4.25 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context272K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAINVIDIAMeta
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released———
Description
SummaryGPT Image 2 combines OpenAI's GPT-5.4 with advanced image generation capabilities from GPT Image 2, enabling fully integrated multimodal workflows. It allows users to seamlessly transition between reasoning, coding, and visual generation within a single interaction, making it well suited for creative, development, and agent-driven applications that require both intelligence and visual output.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.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.