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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. Gemini 4 ArgonGoogleRemove
  2. Muse Spark OpenMetaRemove
  3. Voxtral Small 24B 2507Mistral AIRemove
gemini-4-argon vs muse-spark-open vs voxtral-small-24b-2507
AttributeGemini 4 Argongemini-4-argonMuse Spark Openmuse-spark-openVoxtral Small 24B 2507voxtral-small-24b-2507
Pricing
Input$2.00 / 1M$1.25 / 1M$0.125 / 1M
Output$10.00 / 1M$4.25 / 1M$0.375 / 1M
Cache Write (5m)$2.00 / 1M$1.25 / 1MNot applicable
Cache Write (1h)$2.00 / 1M$1.25 / 1MNot applicable
Cache Read$2.00 / 1M$1.25 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M32K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesYes
Catalogue
ProviderGoogleMetaMistral AI
Categorychatchatvoice
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.Voxtral Small is an upgraded version of Mistral Small 3 that adds advanced audio understanding while preserving strong text performance. It handles speech transcription, translation, and audio comprehension, with audio input billed per million seconds.