LLM Reference

GPT-4.1 vs Nemotron 3 Nano Omni

GPT-4.1 (2025) and Nemotron 3 Nano Omni (2026) are general-purpose language models from OpenAI and NVIDIA AI. GPT-4.1 ships a 1.05m-token context window, while Nemotron 3 Nano Omni ships a 262k-token context window. On MMLU PRO, GPT-4.1 leads by 10 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Nemotron 3 Nano Omni is safer overall; choose GPT-4.1 when coding workflow support matters.

Decision scorecard

Local evidence first
SignalGPT-4.1Nemotron 3 Nano Omni
Best formultimodal apps, tool-calling agents, and long-context analysismultimodal apps
Decision fitCoding, RAG, and AgentsLong context, Vision, and Classification
Context window1.05m262k
Cheapest output$8/1M tokens-
Provider routes4 tracked1 tracked
Shared benchmarksMMLU PRO leader1 shared

Decision tradeoffs

Choose GPT-4.1 when...
  • GPT-4.1 holds a shared-benchmark lead on MMLU PRO, ahead by 10 points.
  • GPT-4.1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GPT-4.1 has broader tracked provider coverage for fallback and procurement flexibility.
  • GPT-4.1 uniquely exposes Vision, Function calling, and Tool use in local model data.
  • Local decision data tags GPT-4.1 for Coding, RAG, and Agents.
Choose Nemotron 3 Nano Omni when...
  • 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-4.1

$3,600

Cheapest tracked route/tier: OpenRouter

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-4.1 -> Nemotron 3 Nano Omni
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Check replacement coverage for Vision, Function calling, and Tool use before moving production traffic.
Nemotron 3 Nano Omni -> GPT-4.1
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • GPT-4.1 adds Vision, Function calling, and Tool use in local capability data.

Specs

Specification
Released2025-04-012026-04-28
Context window1.05m262k
Parameters30B
ArchitectureDecoder OnlyMoE + SSM Hybrid
LicenseProprietaryNVIDIA Open Model
OpennessProprietaryOpen weights
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff2025-01-

Pricing and availability

Pricing attributeGPT-4.1Nemotron 3 Nano Omni
Input price$2/1M tokens-
Output price$8/1M tokens-
Providers

Capabilities

CapabilityGPT-4.1Nemotron 3 Nano Omni
VisionYesNo
MultimodalYesYes
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGPT-4.1Nemotron 3 Nano Omni
MMLU PRO81.871.8

Deep dive

On shared benchmark coverage, MMLU PRO has GPT-4.1 at 81.8 and Nemotron 3 Nano Omni at 71.8, with GPT-4.1 ahead by 10 points. The largest visible gap is 10 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on vision: GPT-4.1, function calling: GPT-4.1, tool use: GPT-4.1, structured outputs: GPT-4.1, and code execution: GPT-4.1. 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-4.1 has $2/1M 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-4.1 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Nemotron 3 Nano Omni when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, GPT-4.1 or Nemotron 3 Nano Omni?

GPT-4.1 supports 1.05m tokens, while Nemotron 3 Nano Omni supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is GPT-4.1 or Nemotron 3 Nano Omni open source?

GPT-4.1 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-4.1 or Nemotron 3 Nano Omni?

GPT-4.1 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-4.1 or Nemotron 3 Nano Omni?

Both GPT-4.1 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-4.1 or Nemotron 3 Nano Omni?

GPT-4.1 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-4.1 and Nemotron 3 Nano Omni?

GPT-4.1 is available on OpenRouter, Azure OpenAI, OpenAI API, and Vercel AI Gateway. Nemotron 3 Nano Omni is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

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