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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. GPT-5.3-CodexOpenAIRemove
  2. Nemotron 3.5 Super VLNVIDIARemove
  3. Muse Spark OpenMetaRemove
gpt-5.3-codex vs nemotron-3.5-super-vl vs muse-spark-open
AttributeGPT-5.3-Codexgpt-5.3-codexNemotron 3.5 Super VLnemotron-3.5-super-vlMuse Spark Openmuse-spark-open
Pricing
Input$1.75 / 1M$0.10 / 1M$1.25 / 1M
Output$14.00 / 1M$0.40 / 1M$4.25 / 1M
Cache Write (5m)$1.75 / 1M$0.10 / 1M$1.25 / 1M
Cache Write (1h)$1.75 / 1M$0.10 / 1M$1.25 / 1M
Cache Read$1.75 / 1M$0.10 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context400K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAINVIDIAMeta
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryGPT-Codex-5.3 is OpenAI's most advanced agentic coding model, designed for software engineering workflows that extend beyond single prompts into long-running, tool-driven execution. It combines the frontier coding performance of earlier Codex models with stronger reasoning and professional knowledge capabilities, enabling reliable handling of complex refactors, multi-step debugging, research-driven development, and autonomous task execution. Optimized for developer productivity, GPT-Codex-5.3 supports interactive collaboration during execution, allowing users to steer tasks in real time without losing context. With improved agentic reliability, faster inference, and stronger performance on long-horizon engineering tasks, it is well suited for coding agents, IDE and CLI workflows, and end-to-end software development pipelines where persistence, tool use, and execution continuity are critical.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.