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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. Muse Spark OpenMetaRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. GLM 5.3 FlashZ.AIRemove
  4. Qwen3.8 27BAlibabaRemove

4 is the maximum. Remove one to add another.

muse-spark-open vs perceptron-mk1.5 vs glm-5.3-flash vs qwen3.8-27b
AttributeMuse Spark Openmuse-spark-openPerceptron Mk1.5perceptron-mk1.5GLM 5.3 Flashglm-5.3-flashQwen3.8 27Bqwen3.8-27b
Pricing
Input$1.25 / 1M$0.15 / 1M$0.075 / 1M$0.45 / 1M
Output$4.25 / 1M$1.50 / 1M$0.25 / 1M$3.20 / 1M
Cache Write (5m)$1.25 / 1M$0.15 / 1M$0.075 / 1M$0.45 / 1M
Cache Write (1h)$1.25 / 1M$0.15 / 1M$0.075 / 1M$0.45 / 1M
Cache Read$1.25 / 1M$0.15 / 1M$0.075 / 1M$0.45 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M36.9K1M262K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesYesYesYes
Catalogue
ProviderMetaPerceptronZ.AIAlibaba
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-25——
Description
SummaryMuse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.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.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.