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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. Gemini 3.7 FlashGoogleRemove
  2. DeepSeek V4 Pro 0813DeepSeekRemove
  3. GLM 5.3 FlashZ.AIRemove
gemini-3.7-flash vs deepseek-v4-pro-0813 vs glm-5.3-flash
AttributeGemini 3.7 Flashgemini-3.7-flashDeepSeek V4 Pro 0813deepseek-v4-pro-0813GLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.375 / 1M$0.435 / 1M$0.075 / 1M
Output$1.88 / 1M$0.87 / 1M$0.25 / 1M
Cache Write (5m)$0.375 / 1M$0.435 / 1M$0.075 / 1M
Cache Write (1h)$0.375 / 1M$0.435 / 1M$0.075 / 1M
Cache Read$0.375 / 1M$0.435 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleDeepSeekZ.AI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 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.DeepSeek V4 Pro 0813 is DeepSeek's large-scale Mixture-of-Experts (MoE) model and the general availability (GA) release of DeepSeek V4 Pro. It is designed for high-capability workloads requiring advanced reasoning, coding, and agentic task execution. As the production-ready V4 Pro release, it is well suited for complex software engineering, long-horizon agent workflows, and demanding reasoning tasks where reliability and model capability are critical.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.