LLM Reference

Marin 32B Base vs Tencent Hunyuan Turbo S

Marin 32B Base (2025) and Tencent Hunyuan Turbo S (2026) are compact production models from Marin and Tencent AI Lab. Marin 32B Base ships a 4k-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 fits 49x more tokens; pick it for long-context work and Marin 32B Base for tighter calls.

Decision scorecard

Local evidence first
SignalMarin 32B BaseTencent Hunyuan Turbo S
Best forgeneral production evaluationgeneral production evaluation
Decision fitGeneralLong context
Context window4k200k
Cheapest output--
Provider routes0 tracked0 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Marin 32B Base when...
  • Use Marin 32B Base when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Choose Tencent Hunyuan Turbo S when...
  • 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.

Marin 32B Base

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

Marin 32B Base -> Tencent Hunyuan Turbo S
  • No overlapping tracked provider route is sourced for Marin 32B Base and Tencent Hunyuan Turbo S; plan for SDK, billing, or endpoint changes.
Tencent Hunyuan Turbo S -> Marin 32B Base
  • No overlapping tracked provider route is sourced for Tencent Hunyuan Turbo S and Marin 32B Base; plan for SDK, billing, or endpoint changes.

Specs

Specification
Released2025-10-252026-01-10
Context window4k200k
Parameters32.5B
Architecturedecoder only-
LicenseApache 2.0(OSI)Tencent Hunyuan Community License
OpennessOpen sourceOpen weights
Commercial useCommercial use allowedCommercial use with conditions
Knowledge cutoff2024-07-

Pricing and availability

Pricing attributeMarin 32B BaseTencent Hunyuan Turbo S
Input price--
Output price--
Providers--

Pricing not yet sourced for either model.

Capabilities

CapabilityMarin 32B BaseTencent Hunyuan Turbo S
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

Pricing coverage is uneven: Marin 32B Base 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 Marin 32B Base 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, Marin 32B Base or Tencent Hunyuan Turbo S?

Tencent Hunyuan Turbo S supports 200k tokens, while Marin 32B Base supports 4k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Marin 32B Base or Tencent Hunyuan Turbo S open source?

Marin 32B Base 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.

When should I pick Marin 32B Base over Tencent Hunyuan Turbo S?

Tencent Hunyuan Turbo S fits 49x more tokens; pick it for long-context work and Marin 32B Base for tighter calls. If your workload also depends on provider fit, start with Marin 32B Base; if it depends on long-context analysis, run the same evaluation with Tencent Hunyuan Turbo S.

What is the main difference between Marin 32B Base and Tencent Hunyuan Turbo S?

Marin 32B Base and Tencent Hunyuan Turbo S differ most on context, provider coverage, capabilities, or pricing depending on the data currently sourced. Use the specs table first, then validate the model behavior with your own prompts.

Continue comparing

Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.