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. Nemotron 3.5 Super VL (Free)NVIDIARemove
  2. GPT-6.1 TerraOpenAIRemove
  3. Muse WonderMetaRemove
  4. MiniMax M2MiniMaxRemove

4 is the maximum. Remove one to add another.

nemotron-3.5-super-vl:free vs gpt-6.1-terra vs muse-wonder vs minimax-m2
AttributeNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeGPT-6.1 Terragpt-6.1-terraMuse Wondermuse-wonderMiniMax M2minimax-m2
Pricing
Input$0 / 1M$1.00 / 1M$4.00 / 1M$0.15 / 1M
Output$0 / 1M$5.00 / 1M$20.00 / 1M$0.45 / 1M
Cache Write$0 / 1M———
Cache Read$0 / 1M$1.00 / 1M$4.00 / 1M$0.15 / 1M
Cache Write (5m)—$1.00 / 1M$4.00 / 1M$0.15 / 1M
Cache Write (1h)—$1.00 / 1M$4.00 / 1M$0.15 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M196.6K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesNoYesYes
Catalogue
ProviderNVIDIAOpenAIMetaMiniMax
Categorychatchatchatchat
Charge typeFreePay As You GoPay As You GoPay As You Go
Released————
Description
SummaryNVIDIA 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.GPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.MiniMax-M2 is a compact, high-efficiency model with 10B active (230B total) parameters, optimized for coding and agentic workflows. It delivers near-frontier reasoning and tool use, excels at multi-file coding tasks and compile-run-fix loops, and performs strongly on benchmarks like SWE-Bench and Terminal-Bench. It also handles long-horizon planning and recovery in agent evaluations, ranking among the top open models across reasoning domains. With fast inference and low cost, it’s ideal for large-scale agents and developer assistants — and works best when reasoning is preserved across turns.