GLM-5 vs Nemotron 3 Nano Omni
GLM-5 (2026) and Nemotron 3 Nano Omni (2026) are frontier reasoning models from Zhipu AI and NVIDIA AI. GLM-5 ships a 200k-token context window, while Nemotron 3 Nano Omni ships a 262k-token context window. On MMLU PRO, GLM-5 leads by 14.2 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 GLM-5 when reasoning depth matters.
Decision scorecard
Local evidence first| Signal | GLM-5 | Nemotron 3 Nano Omni |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | multimodal apps |
| Decision fit | Coding, RAG, and Agents | Long context, Vision, and Classification |
| Context window | 200k | 262k |
| Cheapest output | $2.08/1M tokens | - |
| Provider routes | 7 tracked | 1 tracked |
| Shared benchmarks | MMLU PRO leader | 1 shared |
Decision tradeoffs
- GLM-5 holds a shared-benchmark lead on MMLU PRO, ahead by 14.2 points.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- Nemotron 3 Nano Omni has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Nemotron 3 Nano Omni uniquely exposes Multimodal in local model data.
- 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.
GLM-5
$1,000
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
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- Nemotron 3 Nano Omni adds Multimodal in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Check replacement coverage for Multimodal before moving production traffic.
- GLM-5 adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-11 | 2026-04-28 |
| Context window | 200k | 262k |
| Parameters | 744B total, 40B active | 30B |
| Architecture | Mixture of Experts | MoE + SSM Hybrid |
| License | MITOSI-approved | NVIDIA Open Model |
| Openness | Open source | Open weights |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | 2025-11 | - |
Pricing and availability
| Pricing attribute | GLM-5 | Nemotron 3 Nano Omni |
|---|---|---|
| Input price | $0.60/1M tokens | - |
| Output price | $2.08/1M tokens | - |
| Providers |
Capabilities
| Capability | GLM-5 | Nemotron 3 Nano Omni |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5 | Nemotron 3 Nano Omni |
|---|---|---|
| MMLU PRO | 86.0 | 71.8 |
Deep dive
On shared benchmark coverage, MMLU PRO has GLM-5 at 86 and Nemotron 3 Nano Omni at 71.8, with GLM-5 ahead by 14.2 points. The largest visible gap is 14.2 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 multimodal input: Nemotron 3 Nano Omni, reasoning mode: GLM-5, function calling: GLM-5, tool use: GLM-5, and structured outputs: GLM-5. 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: GLM-5 has $0.60/1M input tokens and Nemotron 3 Nano Omni has no token price sourced yet. Provider availability is 7 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GLM-5 when reasoning depth 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.
FAQ
Which has a larger context window, GLM-5 or Nemotron 3 Nano Omni?
Nemotron 3 Nano Omni supports 262k tokens, while GLM-5 supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is GLM-5 or Nemotron 3 Nano Omni open source?
GLM-5 is listed under MIT. 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 multimodal input, GLM-5 or Nemotron 3 Nano Omni?
Nemotron 3 Nano Omni has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for reasoning mode, GLM-5 or Nemotron 3 Nano Omni?
GLM-5 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, GLM-5 or Nemotron 3 Nano Omni?
GLM-5 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 and Nemotron 3 Nano Omni?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. 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.