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Kimi K2 Thinking vs Weaver (alpha)

Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Kimi K2 ThinkingMoonshot AI
Coding
No data
Overall
22.0
Output $/M
$2.50
M Weaver (alpha)Mancer
Coding
No data
Overall
No data
Output $/M
$0.75
vs $2.50 vs $0.75 per 1M output tokens. Weaver (alpha) is 3.3x cheaper.

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Kimi K2 Thinking has the edge where the context window is larger, 262K against 8K tokens.

Shared results
0
Kimi K2 Thinking only
30
Weaver (alpha) only
0
Like-for-like categories
0 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Kimi K2 Thinking not benchmarked, Weaver (alpha) not benchmarked.
Widest category
No category has a result for both models.
Widest single gap
No benchmark has a result for both models.
Output price
Kimi K2 Thinking $2.50 against Weaver (alpha) $0.75 per million output tokens, 3.3x apart.
Context window
Kimi K2 Thinking takes 262K tokens, Weaver (alpha) 8K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
Coding benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
SWE-bench Verified63.4%Not measuredOnly Kimi K2 Thinking measured
LiveCodeBench (Vals AI)63.1%Not measuredOnly Kimi K2 Thinking measured
SWE-bench Verified (Vals AI)60.2%Not measuredOnly Kimi K2 Thinking measured
LiveCodeBench (Artificial Analysis run)85.3%Not measuredOnly Kimi K2 Thinking measured
Terminal-Bench Hard (Artificial Analysis run)31.1%Not measuredOnly Kimi K2 Thinking measured
Terminal-Bench35.7%Not measuredOnly Kimi K2 Thinking measured
WeirdML42.8%Not measuredOnly Kimi K2 Thinking measured
ALE-Bench597.5Not measuredOnly Kimi K2 Thinking measured
Neither model has a result on the other 30 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
AA Intelligence Index22.0Not measuredOnly Kimi K2 Thinking measured
Epoch Capabilities Index145.8Not measuredOnly Kimi K2 Thinking measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
τ²-Bench Telecom93.0%Not measuredOnly Kimi K2 Thinking measured
METR time horizons59.2%Not measuredOnly Kimi K2 Thinking measured
Neither model has a result on the other 37 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Reasoning benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
GPQA Diamond78.5%Not measuredOnly Kimi K2 Thinking measured
GPQA Diamond (Artificial Analysis run)83.8%Not measuredOnly Kimi K2 Thinking measured
Humanity's Last Exam (Artificial Analysis run)23.8%Not measuredOnly Kimi K2 Thinking measured
Neither model has a result on the other 18 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
AIME85.4%Not measuredOnly Kimi K2 Thinking measured
MGSM (Vals AI)90.2%Not measuredOnly Kimi K2 Thinking measured
AA Math Index94.7Not measuredOnly Kimi K2 Thinking measured
AIME 2025 (Artificial Analysis run)94.7%Not measuredOnly Kimi K2 Thinking measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
MMLU Pro81.1%Not measuredOnly Kimi K2 Thinking measured
LegalBench (Vals AI)80.2%Not measuredOnly Kimi K2 Thinking measured
CaseLaw (Vals AI)65.7%Not measuredOnly Kimi K2 Thinking measured
CorpFin (Vals AI)60.6%Not measuredOnly Kimi K2 Thinking measured
TaxEval (Vals AI)71.7%Not measuredOnly Kimi K2 Thinking measured
MedQA (Vals AI)92.6%Not measuredOnly Kimi K2 Thinking measured
MMLU Pro (Artificial Analysis run)84.8%Not measuredOnly Kimi K2 Thinking measured
Neither model has a result on the other 10 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Web design benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
Design Arena: websites1113Not measuredOnly Kimi K2 Thinking measured
Neither model has a result on the other 8 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
General benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
IFBench68.1%Not measuredOnly Kimi K2 Thinking measured
Long context reasoning (AA-LCR)72.0%Not measuredOnly Kimi K2 Thinking measured
CL-bench17.6%Not measuredOnly Kimi K2 Thinking measured
Neither model has a result on the other 43 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Kimi K2 Thinking and Weaver (alpha)
BenchmarkKimi K2 ThinkingWeaver (alpha)Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Kimi K2 Thinking$0.0019Fits in one request
Weaver (alpha)$0.0008Fits in one request

Weaver (alpha) costs less

Repository review

50K input + 3K output tokens

Kimi K2 Thinking$0.037Fits in one request
Weaver (alpha)$0.022Exceeds the context window

Weaver (alpha) costs less

Agent loop

200K input + 10K output tokens

Kimi K2 Thinking$0.145Fits in one request
Weaver (alpha)$0.087Exceeds the context window

Weaver (alpha) costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Kimi K2 Thinking and Weaver (alpha)
SpecificationMoonshotAI Kimi K2 ThinkingMancer Weaver (alpha)
MakerMoonshot AIMancer
WeightsOpen weightsNo public weights listed
ReleasedNovember 6, 2025August 2, 2023
Context window262K8K
Input $/Mtok$0.60$0.40
Output $/Mtok$2.50$0.75
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved task$0.61Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Kimi K2 Thinking better than Weaver (alpha) for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Kimi K2 Thinking has the edge where the context window is larger, 262K against 8K tokens.

Which is cheaper, Kimi K2 Thinking or Weaver (alpha)?

Kimi K2 Thinking costs $0.60 per million input tokens and $2.50 per million output tokens; Weaver (alpha) costs $0.40 and $0.75. Cost per solved task is known for Kimi K2 Thinking only.

Which has the bigger context window, Kimi K2 Thinking or Weaver (alpha)?

Kimi K2 Thinking, with 262K tokens against 8K.

How many benchmarks is the Kimi K2 Thinking vs Weaver (alpha) comparison based on?

0 benchmarks have a result for both models as of October 21, 2026. Kimi K2 Thinking's coding index rests on 1 independent benchmark and Weaver (alpha)'s on 0. Where only one model has a result, the page says so instead of naming a winner.

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