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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. DeepSeek V4.1 FlashDeepSeekRemove
  3. Gemini 3.1 Pro PreviewGoogleRemove
muse-spark-1.3 vs deepseek-v4.1-flash vs gemini-3.1-pro-preview
AttributeMuse Spark 1.3muse-spark-1.3DeepSeek V4.1 Flashdeepseek-v4.1-flashGemini 3.1 Pro Previewgemini-3.1-pro-preview
Pricing
Input$1.25 / 1M$0.30 / 1M$2.00 / 1M
Output$4.25 / 1M$1.20 / 1M$12.00 / 1M
Cache Write (5m)$1.25 / 1M$0.30 / 1M$2.00 / 1M
Cache Write (1h)$1.25 / 1M$0.30 / 1M$2.00 / 1M
Cache Read$1.25 / 1M$0.30 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1.0M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMetaDeepSeekGoogle
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.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.Gemini 3.1 Pro Preview is Google's frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Built on the multimodal foundation of the Gemini 3 series, it combines high-precision reasoning across text, image, video, audio, and code with a 1M-token context window for large-scale tasks. The 3.1 update introduces measurable gains on SWE benchmarks and real-world coding environments, along with stronger autonomous execution in structured domains such as finance and spreadsheet-based workflows. Designed for advanced development and agentic systems, it improves long-horizon stability and tool orchestration while adding a new medium thinking level to better balance cost, speed, and performance. Gemini 3.1 Pro Preview is well suited for agentic coding, structured planning, multimodal analysis, financial modeling, spreadsheet automation, and high-context enterprise applications.