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Kimi K2 Instruct vs Kimi K2-Instruct-0905

Kimi K2 Instruct and Kimi K2-Instruct-0905 are closely matched at 22.0 and 21.7 on the LLM Stats Score.

Moonshot AI · Moonshot AI · Updated for 2026

Which is better?

Kimi K2 Instruct and Kimi K2-Instruct-0905 are closely matched on the overall LLM Stats Score at 22.0 and 21.7.

In the 27 individual benchmarks reported for both models, Kimi K2-Instruct-0905 wins 26; 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 Instruct

  • you want predictable pricing at $0.50/M input and $0.50/M output

Choose Kimi K2-Instruct-0905

  • you value its reported benchmark strengths — it wins 26 of 27 exact shared results
  • you want the most recent training data — it shipped Sep 2025

At a glance

The differences that matter most.

Core performance indexes
22.0
#171
21.7
#176
22.1
#163
22.0
#164
12.6
#138
10.0
#160
-0.9
#164
-4.2
#169
Cost, coverage & limits
Benchmark wins
1 of 27
26 of 27
Input price
$0.50 / M
— / M
Output price
$0.50 / M
— / M
Context window
200,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

5 shared
Index
Kimi K2 Instruct
Kimi K2-Instruct-0905
22.5#131
21.8#137
7.4#136
7.4#135
11.8#61
11.9#59
24.4#58
24.6#57
24.4#48
24.6#47
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

38 reported for Kimi K2 Instruct · 29 for Kimi K2-Instruct-0905

27 shared

Kimi K2 Instruct outperforms in 1 benchmarks (Terminal-Bench), while Kimi K2-Instruct-0905 is better at 0 benchmarks.

Kimi K2 Instruct has a slight edge in benchmark performance.

Fri Sep 04 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-0905 has 0.0B more parameters than Kimi K2 Instruct, making it 0.0% larger.

Moonshot AI
Kimi K2 Instruct
1.0Tparameters
Moonshot AI
Kimi K2-Instruct-0905
1.0Tparameters
1000.0B
Kimi K2 Instruct
1000.0B
Kimi K2-Instruct-0905

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 Instruct
Input200,000 tokens
Output200,000 tokens
Moonshot AI
Kimi K2-Instruct-0905
Input- tokens
Output- tokens
Fri Sep 04 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 Instruct

MIT

Open weights

Kimi K2-Instruct-0905

MIT

Open weights

Release Timeline

When each model was launched

Kimi K2 Instruct was released on 2025-07-11, while Kimi K2-Instruct-0905 was released on 2025-09-05.

Kimi K2-Instruct-0905 is 2 months newer than Kimi K2 Instruct.

Kimi K2 Instruct

Jul 11, 2025

1.1 years ago

Kimi K2-Instruct-0905

Sep 5, 2025

12 months ago

1mo newer

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?Start an Issue discussion

Judge for yourself.

Run your own prompts against Kimi K2 Instruct and Kimi K2-Instruct-0905 side-by-side, then vote on the output you prefer.

Kimi K2 Instruct
✓ Preferred
Kimi K2-Instruct-0905
Open in Playground

FAQ

Common questions about Kimi K2 Instruct vs Kimi K2-Instruct-0905.

Which is better, Kimi K2 Instruct or Kimi K2-Instruct-0905?

Kimi K2 Instruct and Kimi K2-Instruct-0905 are closely matched on the LLM Stats Score at 22.0 and 21.7. Kimi K2 Instruct is made by Moonshot AI and Kimi K2-Instruct-0905 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 Instruct compare to Kimi K2-Instruct-0905 in benchmarks?

Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%. Kimi K2-Instruct-0905 scores MATH-500: 97.4%, MMLU-Redux: 92.7%, IFEval: 89.8%, AutoLogi: 89.5%, MMLU: 89.5%.

What are the context window sizes for Kimi K2 Instruct and Kimi K2-Instruct-0905?

Kimi K2 Instruct supports 200K tokens and Kimi K2-Instruct-0905 supports an unknown number of 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 Instruct and Kimi K2-Instruct-0905?

Key differences include LLM Stats Score (22.0 vs 21.7). See the full comparison above for benchmark-by-benchmark results.