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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. Qwen3.8 2.4T A95BAlibabaRemove
  2. Muse Spark 1.3MetaRemove
  3. Gemini 3.7 FlashGoogleRemove
qwen3.8-2.4t-a95b vs muse-spark-1.3 vs gemini-3.7-flash
AttributeQwen3.8 2.4T A95Bqwen3.8-2.4t-a95bMuse Spark 1.3muse-spark-1.3Gemini 3.7 Flashgemini-3.7-flash
Pricing
Input$1.80 / 1M$1.25 / 1M$0.375 / 1M
Output$5.40 / 1M$4.25 / 1M$1.88 / 1M
Cache Write (5m)$1.80 / 1M$1.25 / 1M$0.375 / 1M
Cache Write (1h)$1.80 / 1M$1.25 / 1M$0.375 / 1M
Cache Read$1.80 / 1M$1.25 / 1M$0.375 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context262K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAlibabaMetaGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryQwen3.8 2.4T A95B is Qwen's open-weight sparse Mixture-of-Experts (MoE) model and the open-weight counterpart to Qwen3.8 Max. It features 2.4T total parameters with 95B activated per token, combining frontier-scale capacity with efficient sparse inference. Designed for coding, research, complex reasoning, and agentic workflows, the model is well suited for demanding long-horizon tasks and advanced autonomous systems while providing the flexibility and customization benefits of open weights.Muse 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.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.