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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 8B ThinkingAlibabaRemove
  2. Kimi K3.1 ProMoonShot AIRemove
  3. Gemini 4 ArgonGoogleRemove
qwen3-vl-8b-thinking vs kimi-k3.1-pro vs gemini-4-argon
AttributeQwen3 VL 8B Thinkingqwen3-vl-8b-thinkingKimi K3.1 Prokimi-k3.1-proGemini 4 Argongemini-4-argon
Pricing
Input$0.18 / 1M$2.00 / 1M$2.00 / 1M
Output$2.10 / 1M$10.00 / 1M$10.00 / 1M
Cache Write (5m)$0.18 / 1M$2.00 / 1M$2.00 / 1M
Cache Write (1h)$0.18 / 1M$2.00 / 1M$2.00 / 1M
Cache Read$0.18 / 1M$2.00 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context256K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAlibabaMoonShot AIGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryQwen3-VL-8B-Thinking is the reasoning-focused version of the Qwen3-VL-8B multimodal model, built for advanced visual and textual reasoning across images, documents, and video. It adds deeper vision-language fusion and deliberate reasoning paths, supports very long context (256K–1M tokens), and excels at STEM problem solving, causal analysis, and multi-step video understanding — while retaining strong OCR, multilingual capability, and high-quality text generation.Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution.Gemini 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.