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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. DeepSeek V4 Pro 0813DeepSeekRemove
  2. Muse Spark 1.3MetaRemove
  3. GPT-6 Astra ProOpenAIRemove
deepseek-v4-pro-0813 vs muse-spark-1.3 vs gpt-6-astra-pro
AttributeDeepSeek V4 Pro 0813deepseek-v4-pro-0813Muse Spark 1.3muse-spark-1.3GPT-6 Astra Progpt-6-astra-pro
Pricing
Input$0.435 / 1M$1.25 / 1M$10.00 / 1M
Output$0.87 / 1M$4.25 / 1M$50.00 / 1M
Cache Write (5m)$0.435 / 1M$1.25 / 1M$10.00 / 1M
Cache Write (1h)$0.435 / 1M$1.25 / 1M$10.00 / 1M
Cache Read$0.435 / 1M$1.25 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderDeepSeekMetaOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryDeepSeek V4 Pro 0813 is DeepSeek's large-scale Mixture-of-Experts (MoE) model and the general availability (GA) release of DeepSeek V4 Pro. It is designed for high-capability workloads requiring advanced reasoning, coding, and agentic task execution. As the production-ready V4 Pro release, it is well suited for complex software engineering, long-horizon agent workflows, and demanding reasoning tasks where reliability and model capability are critical.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.GPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.