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. Muse Spark OpenMetaRemove
  3. Qwen3 VL 8B ThinkingAlibabaRemove
gemini-4-argon vs muse-spark-open vs qwen3-vl-8b-thinking
AttributeGemini 4 Argongemini-4-argonMuse Spark Openmuse-spark-openQwen3 VL 8B Thinkingqwen3-vl-8b-thinking
Pricing
Input$2.00 / 1M$1.25 / 1M$0.18 / 1M
Output$10.00 / 1M$4.25 / 1M$2.10 / 1M
Cache Write (5m)$2.00 / 1M$1.25 / 1M$0.18 / 1M
Cache Write (1h)$2.00 / 1M$1.25 / 1M$0.18 / 1M
Cache Read$2.00 / 1M$1.25 / 1M$0.18 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M256K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleMetaAlibaba
Categorychatchatchat
Charge typePay As You GoPay 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.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.Qwen3-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.