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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 VL 8B ThinkingAlibabaRemove
  2. Nemotron 3.5 Super VL (Free)NVIDIARemove
  3. Muse Spark OpenMetaRemove
qwen3-vl-8b-thinking vs nemotron-3.5-super-vl:free vs muse-spark-open
AttributeQwen3 VL 8B Thinkingqwen3-vl-8b-thinkingNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeMuse Spark Openmuse-spark-open
Pricing
Input$0.18 / 1M$0 / 1M$1.25 / 1M
Output$2.10 / 1M$0 / 1M$4.25 / 1M
Cache Write (5m)$0.18 / 1M—$1.25 / 1M
Cache Write (1h)$0.18 / 1M—$1.25 / 1M
Cache Read$0.18 / 1M$0 / 1M$1.25 / 1M
Web Search$0 / 1M—$0 / 1M
Cache Write—$0 / 1M—
Context
Max context256K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAlibabaNVIDIAMeta
Categorychatchatchat
Charge typePay As You GoFreePay As You Go
Released———
Description
SummaryQwen3-VL-8B-Thinking is the reasoning-focused version of the Qwen3-VL-8B multimodal model, built for advanced visual and textual reasoning across images, documents, and video. It adds deeper vision-language fusion and deliberate reasoning paths, supports very long context (256K–1M tokens), and excels at STEM problem solving, causal analysis, and multi-step video understanding — while retaining strong OCR, multilingual capability, and high-quality text generation.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.