LLM Reference

Nemotron 3 Ultra vs TxGemma

Nemotron 3 Ultra (2024) and TxGemma (2024) are compact production models from NVIDIA AI and Google DeepMind. Nemotron 3 Ultra ships a 128k-token context window, while TxGemma ships a not-yet-sourced 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 Ultra is safer overall; choose TxGemma when provider fit matters.

Decision scorecard

Local evidence first
SignalNemotron 3 UltraTxGemma
Best forgeneral production evaluationtool-calling agents
Decision fitLong contextAgents, Classification, and JSON / Tool use
Context window128k
Cheapest output--
Provider routes0 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Nemotron 3 Ultra when...
  • Nemotron 3 Ultra has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Nemotron 3 Ultra for Long context.
Choose TxGemma when...
  • TxGemma has broader tracked provider coverage for fallback and procurement flexibility.
  • TxGemma uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
  • Local decision data tags TxGemma for Agents, Classification, and JSON / Tool use.

Monthly cost at traffic

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

Nemotron 3 Ultra

Unavailable

No complete token price in local provider data

TxGemma

Unavailable

No complete token price in local provider data

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

Switch friction

Nemotron 3 Ultra -> TxGemma
  • No overlapping tracked provider route is sourced for Nemotron 3 Ultra and TxGemma; plan for SDK, billing, or endpoint changes.
  • TxGemma adds Function calling, Tool use, and Structured outputs in local capability data.
TxGemma -> Nemotron 3 Ultra
  • No overlapping tracked provider route is sourced for TxGemma and Nemotron 3 Ultra; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.

Specs

Specification
Released2024-09-102024-06-01
Context window128k
Parameters550B (55B active)2B
Architecturedecoder onlydecoder only
LicenseNVIDIA Open ModelProprietary
OpennessOpen weightsProprietary
Commercial useCommercial use allowedCommercial use with conditions
Knowledge cutoff--

Pricing and availability

Pricing attributeNemotron 3 UltraTxGemma
Input price--
Output price--
Providers-

Pricing not yet sourced for either model.

Capabilities

CapabilityNemotron 3 UltraTxGemma
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo
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 function calling: TxGemma, tool use: TxGemma, and structured outputs: TxGemma. Both models share the core language-model surface, 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: Nemotron 3 Ultra has no token price sourced yet and TxGemma has no token price sourced yet. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Nemotron 3 Ultra when provider fit are central to the workload. Choose TxGemma when provider fit 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

Is Nemotron 3 Ultra or TxGemma open source?

Nemotron 3 Ultra is listed under NVIDIA Open Model. TxGemma is listed under Proprietary. 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, Nemotron 3 Ultra or TxGemma?

TxGemma 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, Nemotron 3 Ultra or TxGemma?

TxGemma 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, Nemotron 3 Ultra or TxGemma?

TxGemma has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Nemotron 3 Ultra and TxGemma?

Nemotron 3 Ultra is available on the tracked providers still being sourced. TxGemma is available on GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Nemotron 3 Ultra over TxGemma?

Nemotron 3 Ultra is safer overall; choose TxGemma when provider fit matters. If your workload also depends on provider fit, start with Nemotron 3 Ultra; if it depends on provider fit, run the same evaluation with TxGemma.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.