LLM Reference

DeepSeek V3 vs Kimi K2 Thinking Turbo

DeepSeek V3 (2024) and Kimi K2 Thinking Turbo (2025) are compact production models from DeepSeek and Moonshot AI. DeepSeek V3 ships a 64k-token context window, while Kimi K2 Thinking Turbo ships a 262k-token context window. On pricing, DeepSeek V3 costs $0.10/1M 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.

DeepSeek V3 is ~1050% cheaper at $0.10/1M; pay for Kimi K2 Thinking Turbo only for long-context analysis.

Decision scorecard

Local evidence first
SignalDeepSeek V3Kimi K2 Thinking Turbo
Best fortool-calling agents and provider-routed productiongeneral production evaluation
Decision fitCoding, Agents, and ClassificationLong context
Context window64k262k
Cheapest output$0.30/1M tokens$8/1M tokens
Provider routes13 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose DeepSeek V3 when...
  • DeepSeek V3 has the lower cheapest tracked output price at $0.30/1M tokens.
  • DeepSeek V3 has broader tracked provider coverage for fallback and procurement flexibility.
  • DeepSeek V3 uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
  • Local decision data tags DeepSeek V3 for Coding, Agents, and Classification.
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.

Monthly cost at traffic

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

Lower estimate DeepSeek V3

DeepSeek V3

$155

Cheapest tracked route/tier: Bitdeer AI

Kimi K2 Thinking Turbo

$2,920

Cheapest tracked route/tier: Vercel AI Gateway

Estimated monthly gap: $2,765. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

DeepSeek V3 -> Kimi K2 Thinking Turbo
  • Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
  • Kimi K2 Thinking Turbo is $7.70/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
Kimi K2 Thinking Turbo -> DeepSeek V3
  • Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
  • DeepSeek V3 is $7.70/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • DeepSeek V3 adds Function calling, Tool use, and Structured outputs in local capability data.

Specs

Specification
Released2024-12-262025-11-06
Context window64k262k
Parameters671B1T (32B active)
Architecturemixture of experts-
LicenseMIT(OSI)MIT(OSI)
OpennessOpen sourceOpen source
Commercial useCommercial use allowedCommercial use allowed
Knowledge cutoff2024-04-

Pricing and availability

Pricing attributeDeepSeek V3Kimi K2 Thinking Turbo
Input price$0.10/1M tokens$1.15/1M tokens
Output price$0.30/1M tokens$8/1M tokens
Providers

Capabilities

CapabilityDeepSeek V3Kimi K2 Thinking Turbo
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
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 function calling: DeepSeek V3, tool use: DeepSeek V3, and structured outputs: DeepSeek V3. 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, DeepSeek V3 lists $0.10/1M input and $0.30/1M output tokens on the cheapest tracked provider, while Kimi K2 Thinking Turbo lists $1.15/1M input and $8/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3 lower by about $3.04 per million blended tokens. Availability is 13 providers versus 1, so concentration risk also matters.

Choose DeepSeek V3 when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Kimi K2 Thinking Turbo 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.

FAQ

Which has a larger context window, DeepSeek V3 or Kimi K2 Thinking Turbo?

Kimi K2 Thinking Turbo supports 262k tokens, while DeepSeek V3 supports 64k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, DeepSeek V3 or Kimi K2 Thinking Turbo?

DeepSeek V3 is cheaper on tracked token pricing. DeepSeek V3 costs $0.10/1M input and $0.30/1M output tokens. Kimi K2 Thinking Turbo costs $1.15/1M input and $8/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is DeepSeek V3 or Kimi K2 Thinking Turbo open source?

DeepSeek V3 is listed under MIT. Kimi K2 Thinking Turbo is listed under MIT. 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, DeepSeek V3 or Kimi K2 Thinking Turbo?

DeepSeek V3 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, DeepSeek V3 or Kimi K2 Thinking Turbo?

DeepSeek V3 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.

Where can I run DeepSeek V3 and Kimi K2 Thinking Turbo?

DeepSeek V3 is available on DeepInfra, Fireworks AI, DeepSeek Platform, Microsoft Foundry, and OpenRouter. Kimi K2 Thinking Turbo is available on Vercel AI Gateway. 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.