Nemotron 3 Ultra vs Tencent Hunyuan Turbo S
Nemotron 3 Ultra (2026) and Tencent Hunyuan Turbo S (2026) are frontier reasoning models from NVIDIA AI and Tencent AI Lab. Nemotron 3 Ultra ships a 1m-token context window, while Tencent Hunyuan Turbo S ships a 200k-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.
Nemotron 3 Ultra fits 5x more tokens; pick it for long-context work and Tencent Hunyuan Turbo S for tighter calls.
Decision scorecard
Local evidence first| Signal | Nemotron 3 Ultra | Tencent Hunyuan Turbo S |
|---|---|---|
| Best for | reasoning-heavy apps and long-context analysis | general production evaluation |
| Decision fit | Long context | Long context |
| Context window | 1m | 200k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Nemotron 3 Ultra has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Nemotron 3 Ultra uniquely exposes Reasoning in local model data.
- Local decision data tags Nemotron 3 Ultra for Long context.
- Local decision data tags Tencent Hunyuan Turbo S for Long context.
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
Tencent Hunyuan Turbo S
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Nemotron 3 Ultra and Tencent Hunyuan Turbo S; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
- No overlapping tracked provider route is sourced for Tencent Hunyuan Turbo S and Nemotron 3 Ultra; plan for SDK, billing, or endpoint changes.
- Nemotron 3 Ultra adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-06-04 | 2026-01-10 |
| Context window | 1m | 200k |
| Parameters | 550B | — |
| Architecture | moe | - |
| License | NVIDIA Open Model | Tencent Hunyuan Community License |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nemotron 3 Ultra | Tencent Hunyuan Turbo S |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Nemotron 3 Ultra | Tencent Hunyuan Turbo S |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Nemotron 3 Ultra. 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 Tencent Hunyuan Turbo S has no token price sourced yet. Provider availability is 0 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Nemotron 3 Ultra when reasoning depth and larger context windows are central to the workload. Choose Tencent Hunyuan Turbo S when provider fit 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, Nemotron 3 Ultra or Tencent Hunyuan Turbo S?
Nemotron 3 Ultra supports 1m tokens, while Tencent Hunyuan Turbo S supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Nemotron 3 Ultra or Tencent Hunyuan Turbo S open source?
Nemotron 3 Ultra is listed under NVIDIA Open Model. Tencent Hunyuan Turbo S is listed under Tencent Hunyuan Community License. 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, Nemotron 3 Ultra or Tencent Hunyuan Turbo S?
Nemotron 3 Ultra 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.
When should I pick Nemotron 3 Ultra over Tencent Hunyuan Turbo S?
Nemotron 3 Ultra fits 5x more tokens; pick it for long-context work and Tencent Hunyuan Turbo S for tighter calls. If your workload also depends on reasoning depth, start with Nemotron 3 Ultra; if it depends on provider fit, run the same evaluation with Tencent Hunyuan Turbo S.
Continue comparing
Last reviewed: 2026-06-09. Data sourced from public model cards and provider documentation.