LLM Reference

Kimi K2 Thinking Turbo vs Ling-2.6-1T

Kimi K2 Thinking Turbo (2025) and Ling-2.6-1T (2026) are frontier reasoning models from Moonshot AI and InclusionAI. Kimi K2 Thinking Turbo ships a 262k-token context window, while Ling-2.6-1T ships a 262k-token context window. On pricing, Ling-2.6-1T costs $0.07/1M input tokens versus $1.15/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Ling-2.6-1T is ~1433% cheaper at $0.07/1M; pay for Kimi K2 Thinking Turbo only for long-context analysis.

Decision scorecard

Local evidence first
SignalKimi K2 Thinking TurboLing-2.6-1T
Best forgeneral production evaluationreasoning-heavy apps, tool-calling agents, and provider-routed production
Decision fitLong contextRAG, Agents, and Long context
Context window262k262k
Cheapest output$8/1M tokens$0.63/1M tokens
Provider routes1 tracked2 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Kimi K2 Thinking Turbo when...
  • Kimi K2 Thinking Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Kimi K2 Thinking Turbo for Long context.
Choose Ling-2.6-1T when...
  • Ling-2.6-1T has the lower cheapest tracked output price at $0.63/1M tokens.
  • Ling-2.6-1T has broader tracked provider coverage for fallback and procurement flexibility.
  • Ling-2.6-1T uniquely exposes Reasoning, Function calling, and Tool use in local model data.
  • Local decision data tags Ling-2.6-1T for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Ling-2.6-1T

Kimi K2 Thinking Turbo

$2,920

Cheapest tracked route/tier: Vercel AI Gateway

Ling-2.6-1T

$216

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $2,704. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Kimi K2 Thinking Turbo -> Ling-2.6-1T
  • No overlapping tracked provider route is sourced for Kimi K2 Thinking Turbo and Ling-2.6-1T; plan for SDK, billing, or endpoint changes.
  • Ling-2.6-1T is $7.38/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Ling-2.6-1T adds Reasoning, Function calling, and Tool use in local capability data.
Ling-2.6-1T -> Kimi K2 Thinking Turbo
  • No overlapping tracked provider route is sourced for Ling-2.6-1T and Kimi K2 Thinking Turbo; plan for SDK, billing, or endpoint changes.
  • Kimi K2 Thinking Turbo is $7.38/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.

Specs

Specification
Released2025-11-062026-04-23
Context window262k262k
Parameters1T (32B active)1T
Architecture-moe
LicenseMIT(OSI)Apache 2.0(OSI)
OpennessOpen sourceOpen source
Commercial useCommercial use allowedCommercial use allowed
Knowledge cutoff--

Pricing and availability

Pricing attributeKimi K2 Thinking TurboLing-2.6-1T
Input price$1.15/1M tokens$0.07/1M tokens
Output price$8/1M tokens$0.63/1M tokens
Providers

Capabilities

CapabilityKimi K2 Thinking TurboLing-2.6-1T
VisionNoNo
MultimodalNoNo
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on reasoning mode: Ling-2.6-1T, function calling: Ling-2.6-1T, tool use: Ling-2.6-1T, and structured outputs: Ling-2.6-1T. 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.

For cost, Kimi K2 Thinking Turbo lists $1.15/1M input and $8/1M output tokens on the cheapest tracked provider, while Ling-2.6-1T lists $0.07/1M input and $0.63/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Ling-2.6-1T lower by about $2.96 per million blended tokens. Availability is 1 providers versus 2, so concentration risk also matters.

Choose Kimi K2 Thinking Turbo when long-context analysis and larger context windows are central to the workload. Choose Ling-2.6-1T when reasoning depth, lower input-token cost, and broader provider choice 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.

FAQ

Which has a larger context window, Kimi K2 Thinking Turbo or Ling-2.6-1T?

Kimi K2 Thinking Turbo supports 262k tokens, while Ling-2.6-1T supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Kimi K2 Thinking Turbo or Ling-2.6-1T?

Ling-2.6-1T is cheaper on tracked token pricing. Kimi K2 Thinking Turbo costs $1.15/1M input and $8/1M output tokens. Ling-2.6-1T costs $0.07/1M input and $0.63/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Kimi K2 Thinking Turbo or Ling-2.6-1T open source?

Kimi K2 Thinking Turbo is listed under MIT. Ling-2.6-1T is listed under Apache 2.0. 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, Kimi K2 Thinking Turbo or Ling-2.6-1T?

Ling-2.6-1T 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.

Which is better for function calling, Kimi K2 Thinking Turbo or Ling-2.6-1T?

Ling-2.6-1T 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.

Where can I run Kimi K2 Thinking Turbo and Ling-2.6-1T?

Kimi K2 Thinking Turbo is available on Vercel AI Gateway. Ling-2.6-1T is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.