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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. Muse Spark 1.3MetaRemove
  2. Claude Fable 5.1AnthropicRemove
  3. Gemma 4 31B (Free)GoogleRemove
muse-spark-1.3 vs claude-fable-5.1 vs gemma-4-31b-it:free
AttributeMuse Spark 1.3muse-spark-1.3Claude Fable 5.1claude-fable-5.1Gemma 4 31B (Free)gemma-4-31b-it:free
Pricing
Input$1.25 / 1M$10.00 / 1M$0 / 1M
Output$4.25 / 1M$50.00 / 1M$0 / 1M
Cache Write (5m)$1.25 / 1M$12.50 / 1M
Cache Write (1h)$1.25 / 1M$20.00 / 1M
Cache Read$1.25 / 1M$1.00 / 1M$0 / 1M
Web Search$0 / 1M$0 / 1M
Cache Write$0 / 1M
Context
Max context1M1M262.1K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMetaAnthropicGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoFree
Released
Description
SummaryMuse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.Claude Fable 5.1 is an upgraded version of Fable 5, delivering broad improvements with particularly strong gains in agentic coding, long-running workflows, and professional knowledge work. It excels at large code refactors, front-end and visual code generation, financial analysis, and complex analytical tasks. Compared with Fable 5, it also produces more concise plans and summaries while maintaining strong performance across extended tasks, making it a natural upgrade for existing Fable workflows and a strong option alongside Opus 5 for reasoning-intensive applications.Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model, supporting text and image inputs with text outputs. It features a 256K token context window, configurable thinking/reasoning modes, native function calling, and broad multilingual support across 140+ languages. The model delivers strong performance in coding, reasoning, and document understanding, making it well suited for developer workflows, multilingual applications, and structured knowledge tasks.