LLM Reference

GPT-5.3-Codex-Spark vs Nemotron 3 Super-120B-A12B

GPT-5.3-Codex-Spark (2026) and Nemotron 3 Super-120B-A12B (2026) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex-Spark ships a 131k-token context window, while Nemotron 3 Super-120B-A12B ships a 1.05m-token context window. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: GPT-5.3-Codex-Spark is coding-specialized model, while Nemotron 3 Super-120B-A12B is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalGPT-5.3-Codex-SparkNemotron 3 Super-120B-A12B
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents, code generation, and tool loopslong-context analysis and provider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window131k1.05m
Cheapest output-$0.45/1M tokens
Provider routes1 tracked6 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose GPT-5.3-Codex-Spark when...
  • GPT-5.3-Codex-Spark uniquely exposes Function calling, Tool use, and Code execution in local model data.
  • Local decision data tags GPT-5.3-Codex-Spark for Coding, RAG, and Agents.
Choose Nemotron 3 Super-120B-A12B when...
  • Nemotron 3 Super-120B-A12B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Nemotron 3 Super-120B-A12B has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Nemotron 3 Super-120B-A12B for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

GPT-5.3-Codex-Spark

Unavailable

No complete token price in local provider data

Nemotron 3 Super-120B-A12B

$185

Cheapest tracked route/tier: OpenRouter

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

GPT-5.3-Codex-Spark -> Nemotron 3 Super-120B-A12B
  • No overlapping tracked provider route is sourced for GPT-5.3-Codex-Spark and Nemotron 3 Super-120B-A12B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling, Tool use, and Code execution before moving production traffic.
Nemotron 3 Super-120B-A12B -> GPT-5.3-Codex-Spark
  • No overlapping tracked provider route is sourced for Nemotron 3 Super-120B-A12B and GPT-5.3-Codex-Spark; plan for SDK, billing, or endpoint changes.
  • GPT-5.3-Codex-Spark adds Function calling, Tool use, and Code execution in local capability data.

Specs

Specification
Released2026-02-122026-03-11
Context window131k1.05m
Parameters120B
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryNVIDIA Open Model
OpennessProprietaryOpen weights
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff--

Pricing and availability

Pricing attributeGPT-5.3-Codex-SparkNemotron 3 Super-120B-A12B
Input price-$0.09/1M tokens
Output price-$0.45/1M tokens
Providers

Capabilities

CapabilityGPT-5.3-Codex-SparkNemotron 3 Super-120B-A12B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on function calling: GPT-5.3-Codex-Spark, tool use: GPT-5.3-Codex-Spark, and code execution: GPT-5.3-Codex-Spark. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: GPT-5.3-Codex-Spark has no token price sourced yet and Nemotron 3 Super-120B-A12B has $0.09/1M input tokens. Provider availability is 1 tracked routes versus 6. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose GPT-5.3-Codex-Spark when coding workflow support are central to the workload. Choose Nemotron 3 Super-120B-A12B when long-context analysis, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, GPT-5.3-Codex-Spark or Nemotron 3 Super-120B-A12B?

Nemotron 3 Super-120B-A12B supports 1.05m tokens, while GPT-5.3-Codex-Spark supports 131k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is GPT-5.3-Codex-Spark or Nemotron 3 Super-120B-A12B open source?

GPT-5.3-Codex-Spark is listed under Proprietary. Nemotron 3 Super-120B-A12B is listed under NVIDIA Open Model. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for function calling, GPT-5.3-Codex-Spark or Nemotron 3 Super-120B-A12B?

GPT-5.3-Codex-Spark has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for tool use, GPT-5.3-Codex-Spark or Nemotron 3 Super-120B-A12B?

GPT-5.3-Codex-Spark has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, GPT-5.3-Codex-Spark or Nemotron 3 Super-120B-A12B?

Both GPT-5.3-Codex-Spark and Nemotron 3 Super-120B-A12B expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run GPT-5.3-Codex-Spark and Nemotron 3 Super-120B-A12B?

GPT-5.3-Codex-Spark is available on OpenAI API. Nemotron 3 Super-120B-A12B is available on Cloudflare Workers AI, DeepInfra, NVIDIA NIM, OpenRouter, and Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.