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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. GPT-5.1 Codex (Mini)OpenAIRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. GLM 5.3 FlashZ.AIRemove
gpt-5.1-codex-mini vs gemini-3.8-flash vs glm-5.3-flash
AttributeGPT-5.1 Codex (Mini)gpt-5.1-codex-miniGemini 3.8 Flashgemini-3.8-flashGLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.125 / 1M$0.75 / 1M$0.075 / 1M
Output$1.00 / 1M$3.75 / 1M$0.25 / 1M
Cache Write (5m)$0.125 / 1M$0.75 / 1M$0.075 / 1M
Cache Write (1h)$0.125 / 1M$0.75 / 1M$0.075 / 1M
Cache Read$0.125 / 1M$0.75 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context400K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAIGoogleZ.AI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGPT-5.1 Codex is a coding-focused version of GPT-5.1 designed for both interactive development and long autonomous engineering tasks. It can build projects, add features, debug, refactor, and review code with higher steerability and cleaner outputs than GPT-5.1. It integrates with developer tools (CLI, IDEs, GitHub, cloud), supports adjustable reasoning effort, handles images/screenshots for UI work, and uses tools for search and environment setup — making it purpose-built for agentic coding workflows.Gemini 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-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.