Skip to content

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. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
  3. GLM 5.3Z.AIRemove
gemini-3.1-flash-image-vertex vs nemotron-3.5-super-vl:free vs glm-5.3
AttributeGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeGLM 5.3glm-5.3
Pricing
Request$0.067 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable—$1.40 / 1M
Cache Write (1h)Not applicable—$1.40 / 1M
Cache ReadNot applicable$0 / 1M$1.40 / 1M
Input—$0 / 1M$1.40 / 1M
Output—$0 / 1M$4.40 / 1M
Cache Write—$0 / 1M—
Web Search——$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleNVIDIAZ.AI
Categoryimagechatchat
Charge typePay Per RequestFreePay 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.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.