LLM Reference

GLM-5.2 vs Nemotron 3 Ultra

GLM-5.2 (2026) and Nemotron 3 Ultra (2026) are frontier-tier reasoning models from Zhipu AI and NVIDIA AI. GLM-5.2 ships a 1m-token context window, while Nemotron 3 Ultra ships a 1m-token context window. On pricing, Nemotron 3 Ultra costs $0.50/1M input tokens versus $1.40/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Nemotron 3 Ultra is ~180% cheaper at $0.50/1M; pay for GLM-5.2 only for coding workflow support.

Decision scorecard

Local evidence first
SignalGLM-5.2Nemotron 3 Ultra
Best forreasoning-heavy apps, tool-calling agents, and long-context analysisreasoning-heavy apps and long-context analysis
Decision fitCoding, RAG, and AgentsLong context
Context window1m1m
Cheapest output$4.40/1M tokens$2.20/1M tokens
Provider routes1 tracked1 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose GLM-5.2 when...
  • GLM-5.2 uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
  • Local decision data tags GLM-5.2 for Coding, RAG, and Agents.
Choose Nemotron 3 Ultra when...
  • Nemotron 3 Ultra has the lower cheapest tracked output price at $2.20/1M tokens.
  • Local decision data tags Nemotron 3 Ultra for Long context.

Monthly cost at traffic

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

Lower estimate Nemotron 3 Ultra

GLM-5.2

$2,220

Cheapest tracked route/tier: OpenRouter

Nemotron 3 Ultra

$950

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $1,270. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GLM-5.2 -> Nemotron 3 Ultra
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Nemotron 3 Ultra is $2.20/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
Nemotron 3 Ultra -> GLM-5.2
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • GLM-5.2 is $2.20/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • GLM-5.2 adds Function calling, Tool use, and Structured outputs in local capability data.

Specs

Specification
Released2026-06-132026-06-04
Context window1m1m
Parameters753B total, 40B active550B
ArchitectureMixture of ExpertsMixture of Experts
LicenseMITOSI-approvedNVIDIA Open Model
OpennessOpen sourceOpen weights
Commercial useCommercial use: permittedCommercial use: permitted
Knowledge cutoff--

Pricing and availability

Pricing attributeGLM-5.2Nemotron 3 Ultra
Input price$1.40/1M tokens$0.50/1M tokens
Output price$4.40/1M tokens$2.20/1M tokens
Providers

Capabilities

CapabilityGLM-5.2Nemotron 3 Ultra
VisionNoNo
MultimodalNoNo
ReasoningYesYes
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
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: GLM-5.2, tool use: GLM-5.2, structured outputs: GLM-5.2, and code execution: GLM-5.2. Both models share reasoning mode, 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.

For cost, GLM-5.2 lists $1.40/1M input and $4.40/1M output tokens on the cheapest tracked provider, while Nemotron 3 Ultra lists $0.50/1M input and $2.20/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Nemotron 3 Ultra lower by about $1.29 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.

Choose GLM-5.2 when coding workflow support are central to the workload. Choose Nemotron 3 Ultra when provider fit and lower input-token cost 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.

FAQ

Which has a larger context window, GLM-5.2 or Nemotron 3 Ultra?

GLM-5.2 supports 1m tokens, while Nemotron 3 Ultra supports 1m tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, GLM-5.2 or Nemotron 3 Ultra?

Nemotron 3 Ultra is cheaper on tracked token pricing. GLM-5.2 costs $1.40/1M input and $4.40/1M output tokens. Nemotron 3 Ultra costs $0.50/1M input and $2.20/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GLM-5.2 or Nemotron 3 Ultra open source?

GLM-5.2 is listed under MIT. Nemotron 3 Ultra 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 reasoning mode, GLM-5.2 or Nemotron 3 Ultra?

Both GLM-5.2 and Nemotron 3 Ultra expose reasoning mode. 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.

Which is better for function calling, GLM-5.2 or Nemotron 3 Ultra?

GLM-5.2 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 GLM-5.2 and Nemotron 3 Ultra?

GLM-5.2 is available on OpenRouter. Nemotron 3 Ultra is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Continue comparing

Last reviewed: 2026-06-24. Data sourced from public model cards and provider documentation.