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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. Gemma 4 26B A4B (Free)GoogleRemove
  2. Gemini 4 ArgonGoogleRemove
  3. Muse Spark OpenMetaRemove
gemma-4-26b-a4b-it:free vs gemini-4-argon vs muse-spark-open
AttributeGemma 4 26B A4B (Free)gemma-4-26b-a4b-it:freeGemini 4 Argongemini-4-argonMuse Spark Openmuse-spark-open
Pricing
Input$0 / 1M$2.00 / 1M$1.25 / 1M
Output$0 / 1M$10.00 / 1M$4.25 / 1M
Cache Write$0 / 1M——
Cache Read$0 / 1M$2.00 / 1M$1.25 / 1M
Cache Write (5m)—$2.00 / 1M$1.25 / 1M
Cache Write (1h)—$2.00 / 1M$1.25 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context262.1K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderGoogleGoogleMeta
Categorychatchatchat
Charge typeFreePay As You GoPay As You Go
Released———
Description
SummaryGemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind, featuring 25.2B total parameters with only 3.8B activated per token—delivering near 31B-class quality at a fraction of the compute cost. It supports multimodal inputs including text, images, and video (up to 60s at 1fps). The model includes a 256K token context window, native function calling, configurable thinking/reasoning modes, and structured output support. Released under the Apache 2.0 license, it is well suited for efficient, production-ready multimodal and agentic applications.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.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.