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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. Muse Spark 1.3MetaRemove
  2. Qwen3.5-122B-A10BAlibabaRemove
  3. Gemini 3.7 FlashGoogleRemove
muse-spark-1.3 vs qwen3.5-122b-a10b vs gemini-3.7-flash
AttributeMuse Spark 1.3muse-spark-1.3Qwen3.5-122B-A10Bqwen3.5-122b-a10bGemini 3.7 Flashgemini-3.7-flash
Pricing
Input$1.25 / 1M$0.40 / 1M$0.375 / 1M
Output$4.25 / 1M$3.20 / 1M$1.88 / 1M
Cache Write (5m)$1.25 / 1M$0.40 / 1M$0.375 / 1M
Cache Write (1h)$1.25 / 1M$0.40 / 1M$0.375 / 1M
Cache Read$1.25 / 1M$0.40 / 1M$0.375 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M262.1K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMetaAlibabaGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryMuse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.Qwen3.5-122B-A10B is a native vision-language model built on a hybrid architecture that combines linear attention mechanisms with a sparse Mixture-of-Experts (MoE) design for improved inference efficiency. In overall performance, it ranks just below Qwen3.5-397B-A17B, delivering substantial gains over previous generations. Its text capabilities significantly exceed Qwen3-235B-2507, while its visual performance surpasses Qwen3-VL-235B, making it a strong high-end option for advanced multimodal and agent-driven applications.Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.