Llama Guard 4 12B vs Tencent Hunyuan Turbo S
Llama Guard 4 12B (2025) and Tencent Hunyuan Turbo S (2026) are general-purpose language models from AI at Meta and Tencent AI Lab. Llama Guard 4 12B ships a 164k-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.
Tencent Hunyuan Turbo S is safer overall; choose Llama Guard 4 12B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Llama Guard 4 12B | Tencent Hunyuan Turbo S |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | RAG, Long context, and Classification | Long context |
| Context window | 164k | 200k |
| Cheapest output | $0.18/1M tokens | - |
| Provider routes | 3 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama Guard 4 12B has broader tracked provider coverage for fallback and procurement flexibility.
- Llama Guard 4 12B uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama Guard 4 12B for RAG, Long context, and Classification.
- Tencent Hunyuan Turbo S has the larger context window for long prompts, retrieval packs, or transcript analysis.
- 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.
Llama Guard 4 12B
$189
Cheapest tracked route/tier: OpenRouter
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 Llama Guard 4 12B and Tencent Hunyuan Turbo S; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Tencent Hunyuan Turbo S and Llama Guard 4 12B; plan for SDK, billing, or endpoint changes.
- Llama Guard 4 12B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2026-01-10 |
| Context window | 164k | 200k |
| Parameters | 12B | — |
| Architecture | decoder only | - |
| License | Llama 2 Community | Tencent Hunyuan Community License |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2024-08 | - |
Pricing and availability
| Pricing attribute | Llama Guard 4 12B | Tencent Hunyuan Turbo S |
|---|---|---|
| Input price | $0.18/1M tokens | - |
| Output price | $0.18/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Llama Guard 4 12B | Tencent Hunyuan Turbo S |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | 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 structured outputs: Llama Guard 4 12B. 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: Llama Guard 4 12B has $0.18/1M input tokens and Tencent Hunyuan Turbo S has no token price sourced yet. Provider availability is 3 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama Guard 4 12B when provider fit and broader provider choice are central to the workload. Choose Tencent Hunyuan Turbo S 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. 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, Llama Guard 4 12B or Tencent Hunyuan Turbo S?
Tencent Hunyuan Turbo S supports 200k tokens, while Llama Guard 4 12B supports 164k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama Guard 4 12B or Tencent Hunyuan Turbo S open source?
Llama Guard 4 12B is listed under Llama 2 Community. 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 structured outputs, Llama Guard 4 12B or Tencent Hunyuan Turbo S?
Llama Guard 4 12B 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 Llama Guard 4 12B and Tencent Hunyuan Turbo S?
Llama Guard 4 12B is available on NVIDIA NIM, Replicate API, and OpenRouter. Tencent Hunyuan Turbo S is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama Guard 4 12B over Tencent Hunyuan Turbo S?
Tencent Hunyuan Turbo S is safer overall; choose Llama Guard 4 12B when provider fit matters. If your workload also depends on provider fit, start with Llama Guard 4 12B; if it depends on long-context analysis, run the same evaluation with Tencent Hunyuan Turbo S.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.