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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. Gemini 4 ArgonGoogleRemove
  2. Gemini 4 CarbonGoogleRemove
  3. Muse Spark OpenMetaRemove
  4. S1Fish AudioRemove

4 is the maximum. Remove one to add another.

gemini-4-argon vs gemini-4-carbon vs muse-spark-open vs s1
AttributeGemini 4 Argongemini-4-argonGemini 4 Carbongemini-4-carbonMuse Spark Openmuse-spark-openS1s1
Pricing
Input$2.00 / 1M$2.00 / 1M$1.25 / 1M— Not priced per input token
Output$10.00 / 1M$10.00 / 1M$4.25 / 1M— Not priced per output token
Cache Write (5m)$2.00 / 1M$2.00 / 1M$1.25 / 1MNot applicable
Cache Write (1h)$2.00 / 1M$2.00 / 1M$1.25 / 1MNot applicable
Cache Read$2.00 / 1M$2.00 / 1M$1.25 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1MN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderGoogleGoogleMetaFish Audio
Categorychatchatchatvoice
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released———2026-07-29
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.Gemini 4 Carbon is Google's frontier multimodal reasoning model, designed for advanced coding, agentic workflows, and complex multi-step problem solving. It supports text, image, audio, video, and file inputs, enabling integrated reasoning and analysis across diverse modalities. Optimized for long-horizon execution and demanding professional workloads, Gemini 4 Carbon supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high) to balance reasoning depth, latency, and cost. It is well suited for autonomous agents, software engineering, multimodal analysis, and large-scale workflow automation.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.Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.