Skip to content

Compare models

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 4 ArgonGoogleRemove
  2. Qwen3 VL 235B A22B InstructAlibabaRemove
gemini-4-argon vs qwen3-vl-235b-a22b-instruct
AttributeGemini 4 Argongemini-4-argonQwen3 VL 235B A22B Instructqwen3-vl-235b-a22b-instruct
Pricing
Input$2.00 / 1M$0.30 / 1M
Output$10.00 / 1M$1.50 / 1M
Cache Write (5m)$2.00 / 1M$0.30 / 1M
Cache Write (1h)$2.00 / 1M$0.30 / 1M
Cache Read$2.00 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M131.1K
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderGoogleAlibaba
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
Description
SummaryGemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.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.