Sarvam 30B vs Tencent Hunyuan Turbo S
Sarvam 30B (2026) and Tencent Hunyuan Turbo S (2026) are compact production models from Sarvam.ai and Tencent AI Lab. Sarvam 30B ships a 66k-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. It focuses on practical selection signals rather than broad model-family marketing.
Sarvam 30B is safer overall; choose Tencent Hunyuan Turbo S when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Sarvam 30B | Tencent Hunyuan Turbo S |
|---|---|---|
| Best for | tool-calling agents | general production evaluation |
| Decision fit | Agents and JSON / Tool use | Long context |
| Context window | 66k | 200k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Sarvam 30B uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Sarvam 30B for Agents and JSON / Tool use.
- 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.
Sarvam 30B
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 Sarvam 30B and Tencent Hunyuan Turbo S; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Tencent Hunyuan Turbo S and Sarvam 30B; plan for SDK, billing, or endpoint changes.
- Sarvam 30B adds Function calling and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-22 | 2026-01-10 |
| Context window | 66k | 200k |
| Parameters | 30B (2.4B active) | — |
| Architecture | moe | - |
| License | Apache 2.0(OSI) | Tencent Hunyuan Community License |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | 2025-06 | - |
Pricing and availability
| Pricing attribute | Sarvam 30B | Tencent Hunyuan Turbo S |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Sarvam 30B | Tencent Hunyuan Turbo S |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | 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 function calling: Sarvam 30B and tool use: Sarvam 30B. 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: Sarvam 30B 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 Sarvam 30B when provider fit 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, Sarvam 30B or Tencent Hunyuan Turbo S?
Tencent Hunyuan Turbo S supports 200k tokens, while Sarvam 30B supports 66k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Sarvam 30B or Tencent Hunyuan Turbo S open source?
Sarvam 30B is listed under Apache 2.0. 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 function calling, Sarvam 30B or Tencent Hunyuan Turbo S?
Sarvam 30B 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, Sarvam 30B or Tencent Hunyuan Turbo S?
Sarvam 30B 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.
When should I pick Sarvam 30B over Tencent Hunyuan Turbo S?
Sarvam 30B is safer overall; choose Tencent Hunyuan Turbo S when long-context analysis matters. If your workload also depends on provider fit, start with Sarvam 30B; if it depends on long-context analysis, run the same evaluation with Tencent Hunyuan Turbo S.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.