Skip to content

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. Qwen3.5 Plus 2026-04-20AlibabaRemove
  2. Nemotron 3.5 Super VLNVIDIARemove
  3. Muse Spark OpenMetaRemove
qwen3.5-plus-20260420 vs nemotron-3.5-super-vl vs muse-spark-open
AttributeQwen3.5 Plus 2026-04-20qwen3.5-plus-20260420Nemotron 3.5 Super VLnemotron-3.5-super-vlMuse Spark Openmuse-spark-open
Pricing
Input$0.40 / 1M$0.10 / 1M$1.25 / 1M
Output$2.40 / 1M$0.40 / 1M$4.25 / 1M
Cache Write (5m)$0.40 / 1M$0.10 / 1M$1.25 / 1M
Cache Write (1h)$0.40 / 1M$0.10 / 1M$1.25 / 1M
Cache Read$0.40 / 1M$0.10 / 1M$1.25 / 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
ProviderAlibabaNVIDIAMeta
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryQwen3.5 Plus (April 2026) is a large-scale multimodal language model from Alibaba, supporting text, image, and video inputs with text output. It features a 1M-token context window, enabling large-scale reasoning and multimodal workflows within a single interaction. This updated version of Qwen3.5 Plus introduces tiered pricing beyond 256K tokens, making it suitable for high-context applications while maintaining flexibility for cost optimization in long-input scenarios.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.