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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. Gemini 3.8 FlashGoogleRemove
  2. GLM 5.3Z.AIRemove
  3. Muse Spark 1.3MetaRemove
  4. GPT-5.3-CodexOpenAIRemove

4 is the maximum. Remove one to add another.

gemini-3.8-flash vs glm-5.3 vs muse-spark-1.3 vs gpt-5.3-codex
AttributeGemini 3.8 Flashgemini-3.8-flashGLM 5.3glm-5.3Muse Spark 1.3muse-spark-1.3GPT-5.3-Codexgpt-5.3-codex
Pricing
Input$0.75 / 1M$1.40 / 1M$1.25 / 1M$1.75 / 1M
Output$3.75 / 1M$4.40 / 1M$4.25 / 1M$14.00 / 1M
Cache Write (5m)$0.75 / 1M$1.40 / 1M$1.25 / 1M$1.75 / 1M
Cache Write (1h)$0.75 / 1M$1.40 / 1M$1.25 / 1M$1.75 / 1M
Cache Read$0.75 / 1M$1.40 / 1M$1.25 / 1M$1.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M400K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderGoogleZ.AIMetaOpenAI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.GPT-Codex-5.3 is OpenAI's most advanced agentic coding model, designed for software engineering workflows that extend beyond single prompts into long-running, tool-driven execution. It combines the frontier coding performance of earlier Codex models with stronger reasoning and professional knowledge capabilities, enabling reliable handling of complex refactors, multi-step debugging, research-driven development, and autonomous task execution. Optimized for developer productivity, GPT-Codex-5.3 supports interactive collaboration during execution, allowing users to steer tasks in real time without losing context. With improved agentic reliability, faster inference, and stronger performance on long-horizon engineering tasks, it is well suited for coding agents, IDE and CLI workflows, and end-to-end software development pipelines where persistence, tool use, and execution continuity are critical.