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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 3.8 FlashGoogleRemove
  2. GLM 5.3 FlashZ.AIRemove
  3. Qwen3 VL 235B A22B InstructAlibabaRemove
gemini-3.8-flash vs glm-5.3-flash vs qwen3-vl-235b-a22b-instruct
AttributeGemini 3.8 Flashgemini-3.8-flashGLM 5.3 Flashglm-5.3-flashQwen3 VL 235B A22B Instructqwen3-vl-235b-a22b-instruct
Pricing
Input$0.75 / 1M$0.075 / 1M$0.30 / 1M
Output$3.75 / 1M$0.25 / 1M$1.50 / 1M
Cache Write (5m)$0.75 / 1M$0.075 / 1M$0.30 / 1M
Cache Write (1h)$0.75 / 1M$0.075 / 1M$0.30 / 1M
Cache Read$0.75 / 1M$0.075 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M131.1K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleZ.AIAlibaba
Categorychatchatchat
Charge typePay 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-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-VL-235B-A22B Instruct is an open-weight multimodal model that combines strong language generation with image and video understanding, aimed at general vision-language tasks like VQA, document parsing, chart/table extraction, and multilingual OCR. It features robust perception, spatial grounding, and long-context visual comprehension, and supports agent-style workflows such as multi-image dialogue, video timeline alignment, GUI control, and visual-to-code assistance. With competitive benchmark performance and strong text-only ability, it's well suited for production uses across document AI, OCR, UI assistance, spatial reasoning, and vision-language research.