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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. GPT Image 2OpenAIRemove
  2. DeepSeek V4.1 Flash 1017DeepSeekRemove
  3. Nemotron 3.5 Super VL (Free)NVIDIARemove
gpt-image-2 vs deepseek-v4.1-flash-1017 vs nemotron-3.5-super-vl:free
AttributeGPT Image 2gpt-image-2DeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free
Pricing
Request$0.04 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$0.10 / 1M—
Cache Write (1h)Not applicable$0.10 / 1M—
Cache ReadNot applicable$0.10 / 1M$0 / 1M
Input—$0.10 / 1M$0 / 1M
Output—$0.50 / 1M$0 / 1M
Web Search—$0 / 1M—
Cache Write——$0 / 1M
Context
Max context272K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAIDeepSeekNVIDIA
Categoryimagechatchat
Charge typePay Per RequestPay As You GoFree
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.DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek’s cost-efficient Mixture-of-Experts (MoE) model, built on its innovative Causal Encoder-Decoder (CED) architecture. Featuring 552B total parameters with 8B activated for input and 16B for output, it combines efficient inference with native multimodal understanding through jointly trained text and visual representations. Optimized for coding, terminal and computer-use agents, and long-horizon workflows, the model introduces compressed KV caching that reduces cache memory usage to approximately one-quarter of the previous Flash generation. DeepSeek reports that it surpasses V4 Pro in performance, inference speed, and task completion time, making it well suited for cost-efficient autonomous agents, complex software engineering, and long-context analysis.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.