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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. GLM 5.3 FlashZ.AIRemove
  2. Qwen3.5-122B-A10BAlibabaRemove
  3. Gemini 3.7 FlashGoogleRemove
glm-5.3-flash vs qwen3.5-122b-a10b vs gemini-3.7-flash
AttributeGLM 5.3 Flashglm-5.3-flashQwen3.5-122B-A10Bqwen3.5-122b-a10bGemini 3.7 Flashgemini-3.7-flash
Pricing
Input$0.075 / 1M$0.40 / 1M$0.375 / 1M
Output$0.25 / 1M$3.20 / 1M$1.88 / 1M
Cache Write (5m)$0.075 / 1M$0.40 / 1M$0.375 / 1M
Cache Write (1h)$0.075 / 1M$0.40 / 1M$0.375 / 1M
Cache Read$0.075 / 1M$0.40 / 1M$0.375 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M262.1K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderZ.AIAlibabaGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-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.Qwen3.5-122B-A10B is a native vision-language model built on a hybrid architecture that combines linear attention mechanisms with a sparse Mixture-of-Experts (MoE) design for improved inference efficiency. In overall performance, it ranks just below Qwen3.5-397B-A17B, delivering substantial gains over previous generations. Its text capabilities significantly exceed Qwen3-235B-2507, while its visual performance surpasses Qwen3-VL-235B, making it a strong high-end option for advanced multimodal and agent-driven applications.Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.