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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. Qwen3 MaxAlibabaRemove
  2. Nemotron 3.5 Super VLNVIDIARemove
  3. Muse Spark OpenMetaRemove
qwen3-max vs nemotron-3.5-super-vl vs muse-spark-open
AttributeQwen3 Maxqwen3-maxNemotron 3.5 Super VLnemotron-3.5-super-vlMuse Spark Openmuse-spark-open
Pricing
Input$1.20 / 1M$0.10 / 1M$1.25 / 1M
Output$6.00 / 1M$0.40 / 1M$4.25 / 1M
Cache Write (5m)$1.20 / 1M$0.10 / 1M$1.25 / 1M
Cache Write (1h)$1.20 / 1M$0.10 / 1M$1.25 / 1M
Cache Read$1.20 / 1M$0.10 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context256K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAlibabaNVIDIAMeta
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryQwen3-Max is an updated Qwen3 model with significant gains in reasoning, instruction following, multilingual support, and long-tail knowledge. It improves accuracy in math, coding, logic, and science, reduces hallucinations, and delivers higher-quality open-ended and conversational responses in over 100 languages. Optimized for RAG and tool use, it focuses on reliable final answers rather than a dedicated “thinking” mode.NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications.Muse 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.