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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. Muse Spark OpenMetaRemove
  2. Kimi K3.1 ProMoonShot AIRemove
  3. Qwen3 30B A3B ThinkAlibabaRemove
muse-spark-open vs kimi-k3.1-pro vs qwen3-30b-a3b-think
AttributeMuse Spark Openmuse-spark-openKimi K3.1 Prokimi-k3.1-proQwen3 30B A3B Thinkqwen3-30b-a3b-think
Pricing
Input$1.25 / 1M$2.00 / 1M$0.051 / 1M
Output$4.25 / 1M$10.00 / 1M$0.34 / 1M
Cache Write (5m)$1.25 / 1M$2.00 / 1M$0.051 / 1M
Cache Write (1h)$1.25 / 1M$2.00 / 1M$0.051 / 1M
Cache Read$1.25 / 1M$2.00 / 1M$0.051 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M32.8K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMetaMoonShot AIAlibaba
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryMuse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution.Qwen3-30B-A3B-Thinking-2507 is a 30B-parameter Mixture-of-Experts (MoE) reasoning model optimized for complex tasks that require extended, multi-step reasoning. It is purpose-built for thinking mode, where internal reasoning traces are explicitly separated from final outputs, enabling more structured and reliable problem solving. Compared to earlier Qwen3-30B variants, this release delivers notable gains across logical reasoning, mathematics, science, coding, and multilingual benchmarks, while also strengthening instruction following, tool usage, and alignment with human preferences. With improved reasoning efficiency and larger output budgets, Qwen3-30B-A3B-Thinking-2507 is well suited for advanced research, competitive problem solving, and agentic applications that demand robust long-context and structured reasoning capabilities.