Skip to content
Apertis

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)GoogleRemove
  2. GPT-6.1 SolOpenAIRemove
  3. GLM 5.3 FlashZ.AIRemove
gemini-3.1-flash-image-vertex vs gpt-6.1-sol vs glm-5.3-flash
AttributeGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexGPT-6.1 Solgpt-6.1-solGLM 5.3 Flashglm-5.3-flash
Pricing
Request$0.067 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$2.00 / 1M$0.075 / 1M
Cache Write (1h)Not applicable$2.00 / 1M$0.075 / 1M
Cache ReadNot applicable$2.00 / 1M$0.075 / 1M
Input—$2.00 / 1M$0.075 / 1M
Output—$10.00 / 1M$0.25 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleOpenAIZ.AI
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.GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.