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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. GPT-6 AstraOpenAIRemove
  2. Muse Spark 1.3MetaRemove
  3. Gemma 4 31B (Free)GoogleRemove
gpt-6-astra vs muse-spark-1.3 vs gemma-4-31b-it:free
AttributeGPT-6 Astragpt-6-astraMuse Spark 1.3muse-spark-1.3Gemma 4 31B (Free)gemma-4-31b-it:free
Pricing
Input$10.00 / 1M$1.25 / 1M$0 / 1M
Output$50.00 / 1M$4.25 / 1M$0 / 1M
Cache Write (5m)$10.00 / 1M$1.25 / 1M
Cache Write (1h)$10.00 / 1M$1.25 / 1M
Cache Read$10.00 / 1M$1.25 / 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
ProviderOpenAIMetaGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoFree
Released
Description
SummaryGPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.Muse 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.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.