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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. Muse Spark OpenMetaRemove
  2. Muse WonderMetaRemove
  3. Gemini 3.5 TranscribeGoogleRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

muse-spark-open vs muse-wonder vs gemini-3.5-transcribe vs deepseek-v4.1-flash
AttributeMuse Spark Openmuse-spark-openMuse Wondermuse-wonderGemini 3.5 Transcribegemini-3.5-transcribeDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$1.25 / 1M$4.00 / 1M— Not priced per input token$0.30 / 1M
Output$4.25 / 1M$20.00 / 1M— Not priced per output token$1.20 / 1M
Cache Write (5m)$1.25 / 1M$4.00 / 1MNot applicable$0.30 / 1M
Cache Write (1h)$1.25 / 1M$4.00 / 1MNot applicable$0.30 / 1M
Cache Read$1.25 / 1M$4.00 / 1MNot applicable$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M98.3K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesNoYes
StreamingYesYesNoYes
Catalogue
ProviderMetaMetaGoogleDeepSeek
Categorychatchatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
SummaryMuse 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.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.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.