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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 Lite Image (Google Vertex AI)GoogleRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. Qwen3.8 27BAlibabaRemove
gemini-3.1-flash-lite-image-vertex vs perceptron-mk1.5 vs qwen3.8-27b
AttributeGemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertexPerceptron Mk1.5perceptron-mk1.5Qwen3.8 27Bqwen3.8-27b
Pricing
Request$0.0336 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$0.15 / 1M$0.45 / 1M
Cache Write (1h)Not applicable$0.15 / 1M$0.45 / 1M
Cache ReadNot applicable$0.15 / 1M$0.45 / 1M
Input—$0.15 / 1M$0.45 / 1M
Output—$1.50 / 1M$3.20 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A36.9K262K
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoNoYes
JSON ModeNoNoYes
StreamingNoYesYes
Catalogue
ProviderGooglePerceptronAlibaba
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released—2026-09-25—
Description
SummaryGemini 3.1 Flash Lite Image served from Google Vertex AI. Billed per image at US$0.0336. 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 1K. A request for a larger size returns a 1K 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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.