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Kimi K2.7 Code vs Qwen3.8-27B

Kimi K2.7 Code and Qwen3.8-27B are closely matched at 39.6 and 46.1 on the LLM Stats Score.

Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Kimi K2.7 Code and Qwen3.8-27B are closely matched on the overall LLM Stats Score at 39.6 and 46.1.

In the 1 individual benchmarks reported for both models, Qwen3.8-27B wins 1; 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 K2.7 Code

  • you want predictable pricing at $0.74/M input and $3.50/M output

Choose Qwen3.8-27B

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Kimi K2.7 Code
Moonshot AI
Qwen3.8-27B
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
39.6
#49
46.1
#24
Reasoning
35.2
#74
45.6
#24
Coding
32.2
#42
34.5
#29
Agents
28.0
#37
32.9
#24
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.74 / M
— / M
Output price
$3.50 / M
— / M
Context window
262,144
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Kimi K2.7 Code
Qwen3.8-27B
Tool use
25.6#26
25.0#30
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for Kimi K2.7 Code · 26 for Qwen3.8-27B

1 shared

Kimi K2.7 Code outperforms in 0 benchmarks, while Qwen3.8-27B is better at 1 benchmark (DeepSWE 1.1).

Qwen3.8-27B significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

972.2B diff

Kimi K2.7 Code has 972.2B more parameters than Qwen3.8-27B, making it 3499.5% larger.

Moonshot AI
Kimi K2.7 Code
1.0Tparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
1000.0B
Kimi K2.7 Code
27.8B
Qwen3.8-27B

Context Window

Maximum input and output token capacity

Only Kimi K2.7 Code specifies input context (262,144 tokens). Only Kimi K2.7 Code specifies output context (131,072 tokens).

Moonshot AI
Kimi K2.7 Code
Input262,144 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Kimi K2.7 Code and Qwen3.8-27B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Kimi K2.7 Code

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2.7 Code is licensed under Modified MIT License, while Qwen3.8-27B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Kimi K2.7 Code

Modified MIT License

Open weights

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2.7 Code was released on 2026-06-12, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 2 months newer than Kimi K2.7 Code.

Kimi K2.7 Code

Jun 12, 2026

2 months ago

Qwen3.8-27B

Aug 14, 2026

2 weeks ago

2mo 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 K2.7 Code and Qwen3.8-27B side-by-side, then vote on the output you prefer.

Kimi K2.7 Code
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about Kimi K2.7 Code vs Qwen3.8-27B.

Which is better, Kimi K2.7 Code or Qwen3.8-27B?

Kimi K2.7 Code and Qwen3.8-27B are closely matched on the LLM Stats Score at 39.6 and 46.1. Kimi K2.7 Code is made by Moonshot AI and Qwen3.8-27B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Kimi K2.7 Code compare to Qwen3.8-27B in benchmarks?

Kimi K2.7 Code scores MCP-Mark: 81.1%, MCP Atlas: 76.0%, LiveBench: 71.9%, Kimi Code Bench v2: 62.0%, Program Bench: 53.6%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the context window sizes for Kimi K2.7 Code and Qwen3.8-27B?

Kimi K2.7 Code supports 262K tokens and Qwen3.8-27B 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 K2.7 Code and Qwen3.8-27B?

Key differences include LLM Stats Score (39.6 vs 46.1), licensing (Modified MIT License vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2.7 Code and Qwen3.8-27B?

Kimi K2.7 Code is developed by Moonshot AI and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.

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