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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. Qwen3 VL 235B A22B InstructAlibabaRemove
  2. GLM 5.3 FlashZ.AIRemove
qwen3-vl-235b-a22b-instruct vs glm-5.3-flash
AttributeQwen3 VL 235B A22B Instructqwen3-vl-235b-a22b-instructGLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.30 / 1M$0.075 / 1M
Output$1.50 / 1M$0.25 / 1M
Cache Write (5m)$0.30 / 1M$0.075 / 1M
Cache Write (1h)$0.30 / 1M$0.075 / 1M
Cache Read$0.30 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context131.1K1M
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderAlibabaZ.AI
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
Description
SummaryQwen3-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.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.