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Kimi K2 Base vs Kimi K2 Instruct

Kimi K2 Instruct leads the LLM Stats Score 21.1 to 12.7.

Moonshot AI · Moonshot AI · Updated for 2026

Which is better?

Kimi K2 Instruct leads the overall LLM Stats Score 21.1 to 12.7, ranking #229 overall.

In the 8 individual benchmarks reported for both models, Kimi K2 Instruct wins 7; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Kimi K2 Base

  • you are already invested in the Moonshot AI ecosystem

Choose Kimi K2 Instruct

  • overall performance matters — it scores 21.1 and ranks #229 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 7 of 8 exact shared results

At a glance

The differences that matter most.

Core performance indexes
12.7
#291
21.1
#229
11.8
#290
21.3
#216
10.5
#201
12.1
#185
Cost, coverage & limits
Benchmark wins
1 of 8
7 of 8
Input price
— / M
$0.50 / M
Output price
— / M
$0.50 / M
Context window
—
200,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Kimi K2 Base
Kimi K2 Instruct
14.3#241
22.1#156
16.4#119
24.1#65
16.4#102
24.1#53
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

13 reported for Kimi K2 Base · 38 for Kimi K2 Instruct

8 shared

Kimi K2 Base outperforms in 1 benchmarks (SimpleQA), while Kimi K2 Instruct is better at 7 benchmarks (CSimpleQA, GPQA, GSM8k, LiveCodeBench v6, MMLU, MMLU-Pro, SuperGPQA).

Kimi K2 Instruct significantly outperforms across most benchmarks.

Fri Nov 13 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

0.0M diff

Kimi K2 Instruct has 0.0B more parameters than Kimi K2 Base, making it 0.0% larger.

Moonshot AI
Kimi K2 Base
1.0Tparameters
Moonshot AI
Kimi K2 Instruct
1.0Tparameters
1000.0B
Kimi K2 Base
1000.0B
Kimi K2 Instruct

Context Window

Maximum input and output token capacity

Only Kimi K2 Instruct specifies input context (200,000 tokens). Only Kimi K2 Instruct specifies output context (200,000 tokens).

Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Moonshot AI
Kimi K2 Instruct
Input200,000 tokens
Output200,000 tokens
Fri Nov 13 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

Kimi K2 Base

MIT

Open weights

Kimi K2 Instruct

MIT

Open weights

Release Timeline

When each model was launched

Both models were released on 2025-07-11.

They likely represent similar generations of model development.

Kimi K2 Base

Jul 11, 2025

1.3 years ago

Kimi K2 Instruct

Jul 11, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Kimi K2 Base and Kimi K2 Instruct side-by-side, then vote on the output you prefer.

Kimi K2 Base
✓ Preferred
Kimi K2 Instruct
Open in Playground

FAQ

Common questions about Kimi K2 Base vs Kimi K2 Instruct.

Which is better, Kimi K2 Base or Kimi K2 Instruct?

Kimi K2 Instruct leads the LLM Stats Score 21.1 to 12.7. Kimi K2 Base is made by Moonshot AI and Kimi K2 Instruct is made by Moonshot AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Kimi K2 Base compare to Kimi K2 Instruct in benchmarks?

Kimi K2 Base scores C-Eval: 92.5%, GSM8k: 92.1%, MMLU-redux-2.0: 90.2%, MMLU: 87.8%, TriviaQA: 85.1%. Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%.

What are the context window sizes for Kimi K2 Base and Kimi K2 Instruct?

Kimi K2 Base supports an unknown number of tokens and Kimi K2 Instruct supports 200K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Kimi K2 Base and Kimi K2 Instruct?

Key differences include LLM Stats Score (12.7 vs 21.1). See the full comparison above for benchmark-by-benchmark results.