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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. Muse Spark 1.3MetaRemove
  2. GPT-6 Astra ProOpenAIRemove
  3. Qwen3.8 27BAlibabaRemove
  4. Veo 3 FastGoogleRemove

4 is the maximum. Remove one to add another.

muse-spark-1.3 vs gpt-6-astra-pro vs qwen3.8-27b vs veo3-fast
AttributeMuse Spark 1.3muse-spark-1.3GPT-6 Astra Progpt-6-astra-proQwen3.8 27Bqwen3.8-27bVeo 3 Fastveo3-fast
Pricing
Input$1.25 / 1M$10.00 / 1M$0.45 / 1M
Output$4.25 / 1M$50.00 / 1M$3.20 / 1M
Cache Write (5m)$1.25 / 1M$10.00 / 1M$0.45 / 1MNot applicable
Cache Write (1h)$1.25 / 1M$10.00 / 1M$0.45 / 1MNot applicable
Cache Read$1.25 / 1M$10.00 / 1M$0.45 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M
Request$1.26 / request
BillingPay Per Request
Context
Max context1M1M262KN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderMetaOpenAIAlibabaGoogle
Categorychatchatchatvideo
Charge typePay As You GoPay As You GoPay As You GoPay Per Request
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.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.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.