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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. Perceptron Mk1.5PerceptronRemove
  2. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  3. GLM 5Z.AIRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs gemini-3.1-flash-image-vertex vs glm-5 vs muse-wonder
AttributePerceptron Mk1.5perceptron-mk1.5Gemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexGLM 5glm-5Muse Wondermuse-wonder
Pricing
Input$0.15 / 1M—$0.60 / 1M$4.00 / 1M
Output$1.50 / 1M—$2.20 / 1M$20.00 / 1M
Cache Write (5m)$0.15 / 1MNot applicable$0.60 / 1M$4.00 / 1M
Cache Write (1h)$0.15 / 1MNot applicable$0.60 / 1M$4.00 / 1M
Cache Read$0.15 / 1MNot applicable$0.60 / 1M$4.00 / 1M
Web Search$0 / 1M—$0 / 1M$0 / 1M
Request—$0.067 / request——
Billing—Pay Per Request——
Context
Max context36.9KN/A202.8K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingNoNoYesYes
JSON ModeNoNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderPerceptronGoogleZ.AIMeta
Categorychatimagechatchat
Charge typePay As You GoPay Per RequestPay As You GoPay 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 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.GLM-5 is Z.AI's flagship open-source foundation model, engineered for complex systems design and long-horizon agent workflows. Built with expert developers in mind, it delivers production-grade performance on large-scale programming tasks, rivaling leading closed-source models. With strong agentic planning, deep backend reasoning, and iterative self-correction capabilities, GLM-5 extends beyond traditional code generation to support full-system construction and autonomous execution, making it well suited for advanced engineering and agent-driven development environments.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.