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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-6 Astra ProOpenAIRemove
  2. Veo 3GoogleRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
  4. Muse Spark 1.3MetaRemove

4 is the maximum. Remove one to add another.

gpt-6-astra-pro vs veo3 vs deepseek-v4.1-flash vs muse-spark-1.3
AttributeGPT-6 Astra Progpt-6-astra-proVeo 3veo3DeepSeek V4.1 Flashdeepseek-v4.1-flashMuse Spark 1.3muse-spark-1.3
Pricing
Input$10.00 / 1M$0.30 / 1M$1.25 / 1M
Output$50.00 / 1M$1.20 / 1M$4.25 / 1M
Cache Write (5m)$10.00 / 1MNot applicable$0.30 / 1M$1.25 / 1M
Cache Write (1h)$10.00 / 1MNot applicable$0.30 / 1M$1.25 / 1M
Cache Read$10.00 / 1MNot applicable$0.30 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Request$1.26 / request
BillingPay Per Request
Context
Max context1MN/A1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderOpenAIGoogleDeepSeekMeta
Categorychatvideochatchat
Charge typePay As You GoPay Per RequestPay As You GoPay As You Go
Released
Description
SummaryGPT-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.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.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.