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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. Perceptron Mk1.5PerceptronRemove
  2. Gemini 3.1 Flash Lite Image (Google Vertex AI)GoogleRemove
  3. Qwen3.8 27BAlibabaRemove
perceptron-mk1.5 vs gemini-3.1-flash-lite-image-vertex vs qwen3.8-27b
AttributePerceptron Mk1.5perceptron-mk1.5Gemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertexQwen3.8 27Bqwen3.8-27b
Pricing
Input$0.15 / 1M—$0.45 / 1M
Output$1.50 / 1M—$3.20 / 1M
Cache Write (5m)$0.15 / 1MNot applicable$0.45 / 1M
Cache Write (1h)$0.15 / 1MNot applicable$0.45 / 1M
Cache Read$0.15 / 1MNot applicable$0.45 / 1M
Web Search$0 / 1M—$0 / 1M
Request—$0.0336 / request—
Billing—Pay Per Request—
Context
Max context36.9KN/A262K
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoNoYes
JSON ModeNoNoYes
StreamingYesNoYes
Catalogue
ProviderPerceptronGoogleAlibaba
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released2026-09-25——
Description
SummaryPerceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Gemini 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.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.