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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. GPT-5.6 Sol ProOpenAIRemove
  2. Muse Spark 1.3MetaRemove
  3. Grok 4.7SpaceXAIRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

gpt-5.6-sol-pro vs muse-spark-1.3 vs grok-4.7 vs glm-5.3
AttributeGPT-5.6 Sol Progpt-5.6-sol-proMuse Spark 1.3muse-spark-1.3Grok 4.7grok-4.7GLM 5.3glm-5.3
Pricing
Input$5.00 / 1M$1.25 / 1M$1.60 / 1M$1.40 / 1M
Output$30.00 / 1M$4.25 / 1M$4.80 / 1M$4.40 / 1M
Cache Write (5m)$5.00 / 1M$1.25 / 1M$1.60 / 1M$1.40 / 1M
Cache Write (1h)$5.00 / 1M$1.25 / 1M$1.60 / 1M$1.40 / 1M
Cache Read$5.00 / 1M$1.25 / 1M$1.60 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M500K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderOpenAIMetaSpaceXAIZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGPT-5.6 Sol Pro uses the same underlying model as GPT-5.6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning and more reliable execution, it is particularly well suited for advanced coding, long-horizon problem solving, and agentic workflows where accuracy and solution quality take priority over speed and cost.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.Grok 4.7 is SpaceXAI's flagship model for coding, agentic workflows, and professional knowledge work, succeeding Grok 4.6. It is particularly strong at long-running software engineering, self-verification, and long-context execution, while improving capabilities in document drafting, presentations, and other professional tasks. Trained with extended reinforcement learning focused on multi-hour problems, Grok 4.7 is optimized for sustained, complex task execution and natively supports the Grok Bot harness for conversational workflows. It also introduces an enhanced safeguard stack designed to combine strong jailbreak resistance with low refusal rates for legitimate technical work. Reported benchmark results use xhigh reasoning effort.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.