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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. Gemini 4 ArgonGoogleRemove
  3. GPT-6.1 TerraOpenAIRemove
  4. MiniMax M2MiniMaxRemove

4 is the maximum. Remove one to add another.

muse-spark-open vs gemini-4-argon vs gpt-6.1-terra vs minimax-m2
AttributeMuse Spark Openmuse-spark-openGemini 4 Argongemini-4-argonGPT-6.1 Terragpt-6.1-terraMiniMax M2minimax-m2
Pricing
Input$1.25 / 1M$2.00 / 1M$1.00 / 1M$0.15 / 1M
Output$4.25 / 1M$10.00 / 1M$5.00 / 1M$0.45 / 1M
Cache Write (5m)$1.25 / 1M$2.00 / 1M$1.00 / 1M$0.15 / 1M
Cache Write (1h)$1.25 / 1M$2.00 / 1M$1.00 / 1M$0.15 / 1M
Cache Read$1.25 / 1M$2.00 / 1M$1.00 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M196.6K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesNoYes
Catalogue
ProviderMetaGoogleOpenAIMiniMax
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
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.Gemini 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.GPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost.MiniMax-M2 is a compact, high-efficiency model with 10B active (230B total) parameters, optimized for coding and agentic workflows. It delivers near-frontier reasoning and tool use, excels at multi-file coding tasks and compile-run-fix loops, and performs strongly on benchmarks like SWE-Bench and Terminal-Bench. It also handles long-horizon planning and recovery in agent evaluations, ranking among the top open models across reasoning domains. With fast inference and low cost, it’s ideal for large-scale agents and developer assistants — and works best when reasoning is preserved across turns.