Kimi K2 vs Tencent Hunyuan Turbo S
Kimi K2 (2025) and Tencent Hunyuan Turbo S (2026) are general-purpose language models from Moonshot AI and Tencent AI Lab. Kimi K2 ships a 262k-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.
Tencent Hunyuan Turbo S is safer overall; choose Kimi K2 when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Kimi K2 | Tencent Hunyuan Turbo S |
|---|---|---|
| Best for | tool-calling agents and provider-routed production | general production evaluation |
| Decision fit | RAG, Agents, and Long context | Long context |
| Context window | 262k | 200k |
| Cheapest output | $2/1M tokens | - |
| Provider routes | 3 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Kimi K2 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2 has broader tracked provider coverage for fallback and procurement flexibility.
- Kimi K2 uniquely exposes Function calling and Structured outputs in local model data.
- Local decision data tags Kimi K2 for RAG, Agents, and 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.
Kimi K2
$900
Cheapest tracked route/tier: AWS Bedrock
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 Kimi K2 and Tencent Hunyuan Turbo S; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling and Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Tencent Hunyuan Turbo S and Kimi K2; plan for SDK, billing, or endpoint changes.
- Kimi K2 adds Function calling and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-07-11 | 2026-01-10 |
| Context window | 262k | 200k |
| Parameters | 1K | — |
| Architecture | - | - |
| License | MIT(OSI) | Tencent Hunyuan Community License |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Kimi K2 | Tencent Hunyuan Turbo S |
|---|---|---|
| Input price | $0.50/1M tokens | - |
| Output price | $2/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Kimi K2 | Tencent Hunyuan Turbo S |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | 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 function calling: Kimi K2 and structured outputs: Kimi K2. 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: Kimi K2 has $0.50/1M 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 Kimi K2 when long-context analysis, larger context windows, and broader provider choice 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, Kimi K2 or Tencent Hunyuan Turbo S?
Kimi K2 supports 262k 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 Kimi K2 or Tencent Hunyuan Turbo S open source?
Kimi K2 is listed under MIT. 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, Kimi K2 or Tencent Hunyuan Turbo S?
Kimi K2 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 structured outputs, Kimi K2 or Tencent Hunyuan Turbo S?
Kimi K2 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 Kimi K2 and Tencent Hunyuan Turbo S?
Kimi K2 is available on OpenRouter, AWS Bedrock, and GCP Vertex AI. 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 Kimi K2 over Tencent Hunyuan Turbo S?
Tencent Hunyuan Turbo S is safer overall; choose Kimi K2 when long-context analysis matters. If your workload also depends on long-context analysis, start with Kimi K2; if it depends on provider fit, run the same evaluation with Tencent Hunyuan Turbo S.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.