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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. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  2. Nemotron 3.5 Super VLNVIDIARemove
  3. Hy4 previewTencentRemove
gemini-3.1-flash-image-vertex vs nemotron-3.5-super-vl vs hy4-preview
AttributeGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexNemotron 3.5 Super VLnemotron-3.5-super-vlHy4 previewhy4-preview
Pricing
Request$0.067 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$0.10 / 1M$0.834 / 1M
Cache Write (1h)Not applicable$0.10 / 1M$0.834 / 1M
Cache ReadNot applicable$0.10 / 1M$0.834 / 1M
Input—$0.10 / 1M$0.834 / 1M
Output—$0.40 / 1M$2.50 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleNVIDIATencent
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released———
Description
SummaryGemini 3.1 Flash Image served from Google Vertex AI. Billed per image at US$0.067. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 2K. A request for a larger size, such as 4K or 4096x4096, returns a 2K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size, for example 4096x4096->2048x2048.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.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.