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Head-to-head comparison

Kimi K2 Thinking vs Laguna S 2.1

Kimi K2 Thinking (Moonshot AI) and Laguna S 2.1 (Poolside) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.

Snapshot as of 9 September 2026

As of 9 September 2026, Laguna S 2.1 holds the stronger ModelCap Index position (#40 vs #42); Laguna S 2.1 is 13.9× cheaper per output token ($0.18/1M vs $2.50/1M); and Laguna S 2.1 offers the longer context window (1M vs 262K tokens).

Which should you choose?

Choose Kimi K2 Thinking if…

  • you want provider choice — 2 listed API providers against 1.

Choose Laguna S 2.1 if…

  • you want the stronger overall ModelCap Index position — #40 against #42 (63.3 vs 62.3 points).
  • API cost matters — $0.18/1M output tokens against $2.50/1M, about 13.9× cheaper.
  • your workload is prompt-heavy — input tokens cost $0.09/1M against $0.60/1M.
  • you need the longer context window — 1M tokens against 262K.
  • you want the more recently listed model — Laguna S 2.1 was listed 21 July 2026, Kimi K2 Thinking 6 November 2025.

Kimi K2 Thinking vs Laguna S 2.1: specs, pricing and context

Specification comparison of Kimi K2 Thinking and Laguna S 2.1
FieldKimi K2 ThinkingMoonshot AILaguna S 2.1Poolside
ModelCap Index position#42#40
Index score62.363.3
EvidenceMeasuredEstimated
Input price / 1M tokens$0.60$0.09
Output price / 1M tokens$2.50$0.18
Context window262K tokens1M tokens
Max output tokens236K131K
API providers listed21
Weight accessRestricted licenseRestricted license
Input modalitiesTextText
First listed6 November 202521 July 2026
PublisherMoonshot AIPoolside

Evidence: 2 public benchmark observations across 2 boards · 5 reported rows against measured corpus ladders (67%); global-corpus-prior over 182 held-out anchors (33%); shrunk 4.8 toward the measured corpus. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.

Benchmark scores: Kimi K2 Thinking vs Laguna S 2.1

Public benchmark boards where Kimi K2 Thinking or Laguna S 2.1 has a published result
BoardKimi K2 ThinkingLaguna S 2.1Leads
Arena codingArena (LMArena)14861481–1492TurboOnly one result
SWE-benchSWE-bench (Princeton / SWE-agent team)63.4%ThinkingOnly one result
AA τ²-Bench TelecomArtificial Analysis93.0%tau2:telecom:dual-control:pass-at-1:3-repeats:source-model="Kimi K2 Thinking":reasoning=trueOnly one result
AA Humanity's Last ExamArtificial Analysis23.8%hle:may-2025:text-only-2158:no-tools:pass-at-1:source-model="Kimi K2 Thinking":reasoning=trueOnly one result

Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.

Want a different pairing? Open the interactive comparison tool to swap either model for any current ranked language model.

Kimi K2 Thinking vs Laguna S 2.1: common questions

Is Kimi K2 Thinking better than Laguna S 2.1?

Laguna S 2.1 ranks higher on the ModelCap Index as of 9 September 2026: #40 against #42. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.

Is Kimi K2 Thinking cheaper than Laguna S 2.1?

Laguna S 2.1 is cheaper on output tokens: $0.18/1M against $2.50/1M. Input tokens are $0.60/1M for Kimi K2 Thinking and $0.09/1M for Laguna S 2.1. Prices are the lowest listed API offer ModelCap observed, in USD per million tokens. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $2.45 for Kimi K2 Thinking versus $0.27 for Laguna S 2.1. Laguna S 2.1 costs 89.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.

Which has the bigger context window, Kimi K2 Thinking or Laguna S 2.1?

Laguna S 2.1 has the larger context window: 1M tokens against 262K.

Which is better for coding, Kimi K2 Thinking or Laguna S 2.1?

The two models do not share a coding benchmark board on ModelCap yet, so no head-to-head coding score is published; the ModelCap Index position is the closest overall signal.

Are Kimi K2 Thinking and Laguna S 2.1 open-weight models?

Kimi K2 Thinking: Restricted license. Laguna S 2.1: Restricted license. Open weights mean the checkpoint can be downloaded and self-hosted under its licence; API-only models are available solely through hosted endpoints.

Where can I run Kimi K2 Thinking and Laguna S 2.1?

ModelCap currently lists 2 API providers for Kimi K2 Thinking and 1 for Laguna S 2.1, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.

How current is this Kimi K2 Thinking vs Laguna S 2.1 comparison?

Every figure comes from the sealed ModelCap dataset published 9 September 2026; the page re-renders within a minute of each data refresh, and the ModelCap Index positions are the same ones shown on the live rankings.

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