LLM Reference

GPT-4 vs Nemotron 3 Nano Omni

GPT-4 (2023) and Nemotron 3 Nano Omni (2026) are compact production models from OpenAI and NVIDIA AI. GPT-4 ships a 8k-token context window, while Nemotron 3 Nano Omni ships a 262k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

Nemotron 3 Nano Omni fits 33x more tokens; pick it for long-context work and GPT-4 for tighter calls.

Decision scorecard

Local evidence first
SignalGPT-4Nemotron 3 Nano Omni
Best formultimodal apps, tool-calling agents, and provider-routed productionmultimodal apps
Decision fitCoding, Agents, and VisionLong context, Vision, and Classification
Context window8k262k
Cheapest output$60/1M tokens-
Provider routes4 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-4 when...
  • GPT-4 has broader tracked provider coverage for fallback and procurement flexibility.
  • GPT-4 uniquely exposes Vision, Function calling, and Structured outputs in local model data.
  • Local decision data tags GPT-4 for Coding, Agents, and Vision.
Choose Nemotron 3 Nano Omni when...
  • Nemotron 3 Nano Omni has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Nemotron 3 Nano Omni for Long context, Vision, and Classification.

Monthly cost at traffic

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

GPT-4

$39,000

Cheapest tracked route/tier: OpenAI API

Nemotron 3 Nano Omni

Unavailable

No complete token price in local provider data

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

Switch friction

GPT-4 -> Nemotron 3 Nano Omni
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Check replacement coverage for Vision, Function calling, and Structured outputs before moving production traffic.
Nemotron 3 Nano Omni -> GPT-4
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • GPT-4 adds Vision, Function calling, and Structured outputs in local capability data.

Specs

Specification
Released2023-03-142026-04-28
Context window8k262k
Parameters1.76T (8x222B MoE)*30B
Architecturemixture of expertsHybrid Mamba-Transformer MoE
LicenseProprietaryNVIDIA Open Model
OpennessProprietaryOpen weights
Commercial useCommercial use with conditionsCommercial use allowed
Knowledge cutoff2021-09-

Pricing and availability

Pricing attributeGPT-4Nemotron 3 Nano Omni
Input price$30/1M tokens-
Output price$60/1M tokens-
Providers

Capabilities

CapabilityGPT-4Nemotron 3 Nano Omni
VisionYesNo
MultimodalYesYes
ReasoningNoNo
Function callingYesNo
Tool useNoNo
Structured outputsYesNo
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: GPT-4, function calling: GPT-4, structured outputs: GPT-4, and code execution: GPT-4. Both models share multimodal input, 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-4 has $30/1M input tokens and Nemotron 3 Nano Omni has no token price sourced yet. Provider availability is 4 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose GPT-4 when coding workflow support and broader provider choice are central to the workload. Choose Nemotron 3 Nano Omni when long-context analysis and larger context windows 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-4 or Nemotron 3 Nano Omni?

Nemotron 3 Nano Omni supports 262k tokens, while GPT-4 supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is GPT-4 or Nemotron 3 Nano Omni open source?

GPT-4 is listed under Proprietary. Nemotron 3 Nano Omni 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 vision, GPT-4 or Nemotron 3 Nano Omni?

GPT-4 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, GPT-4 or Nemotron 3 Nano Omni?

Both GPT-4 and Nemotron 3 Nano Omni expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for function calling, GPT-4 or Nemotron 3 Nano Omni?

GPT-4 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.

Where can I run GPT-4 and Nemotron 3 Nano Omni?

GPT-4 is available on OpenAI API, Azure OpenAI, Salesforce Einstein Generative AI, and OpenRouter. Nemotron 3 Nano Omni is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.