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Kimi K2-Instruct-0905 vs Qwen3.8 Max

Qwen3.8 Max leads the LLM Stats Score 51.9 to 21.6.

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

Which is better?

Qwen3.8 Max leads the overall LLM Stats Score 51.9 to 21.6, ranking #11 overall.

In the 2 individual benchmarks reported for both models, Qwen3.8 Max wins 2; 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-0905

  • you are already invested in the Moonshot AI ecosystem

Choose Qwen3.8 Max

  • overall performance matters — it scores 51.9 and ranks #11 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Kimi K2-Instruct-0905
Moonshot AI
Qwen3.8 Max
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
21.6
#185
51.9
#11
Reasoning
21.8
#175
50.6
#11
Coding
9.8
#168
39.6
#14
Agents
-4.1
#179
37.7
#12
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
— / M
$1.65 / M
Output price
— / M
$4.95 / M
Context window
—
256,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Kimi K2-Instruct-0905
Qwen3.8 Max
Math
21.5#144
33.8#52
Tool use
6.6#144
31.9#8
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

29 reported for Kimi K2-Instruct-0905 · 42 for Qwen3.8 Max

2 shared

Kimi K2-Instruct-0905 outperforms in 0 benchmarks, while Qwen3.8 Max is better at 2 benchmarks (GPQA, Humanity's Last Exam).

Qwen3.8 Max significantly outperforms across most benchmarks.

Mon Sep 14 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1400.0B diff

Qwen3.8 Max has 1400.0B more parameters than Kimi K2-Instruct-0905, making it 140.0% larger.

Moonshot AI
Kimi K2-Instruct-0905
1.0Tparameters
Alibaba Cloud / Qwen Team
Qwen3.8 Max
2.4Tparameters
1000.0B
Kimi K2-Instruct-0905
2400.0B
Qwen3.8 Max

Context Window

Maximum input and output token capacity

Only Qwen3.8 Max specifies input context (256,000 tokens). Only Qwen3.8 Max specifies output context (256,000 tokens).

Moonshot AI
Kimi K2-Instruct-0905
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3.8 Max
Input256,000 tokens
Output256,000 tokens
Mon Sep 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8 Max supports multimodal inputs, whereas Kimi K2-Instruct-0905 does not.

Qwen3.8 Max can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi K2-Instruct-0905

Text
Images
Audio
Video

Qwen3.8 Max

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2-Instruct-0905 is licensed under MIT, while Qwen3.8 Max uses Qwen3.8-Max License.

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

Kimi K2-Instruct-0905

MIT

Open weights

Qwen3.8 Max

Qwen3.8-Max License

Open weights

Release Timeline

When each model was launched

Kimi K2-Instruct-0905 was released on 2025-09-05, while Qwen3.8 Max was released on 2026-08-02.

Qwen3.8 Max is 11 months newer than Kimi K2-Instruct-0905.

Kimi K2-Instruct-0905

Sep 5, 2025

1.0 years ago

Qwen3.8 Max

Aug 2, 2026

1 months ago

11mo 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-0905 and Qwen3.8 Max side-by-side, then vote on the output you prefer.

Kimi K2-Instruct-0905
✓ Preferred
Qwen3.8 Max
Open in Playground

FAQ

Common questions about Kimi K2-Instruct-0905 vs Qwen3.8 Max.

Which is better, Kimi K2-Instruct-0905 or Qwen3.8 Max?

Qwen3.8 Max leads the LLM Stats Score 51.9 to 21.6. Kimi K2-Instruct-0905 is made by Moonshot AI and Qwen3.8 Max 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-Instruct-0905 compare to Qwen3.8 Max in benchmarks?

Kimi K2-Instruct-0905 scores MATH-500: 97.4%, MMLU-Redux: 92.7%, IFEval: 89.8%, AutoLogi: 89.5%, MMLU: 89.5%. Qwen3.8 Max scores PaperBench: 93.0%, MRCR v2 (8-needle): 92.9%, GPQA: 92.6%, VideoMME w sub.: 90.4%, RealWorldQA: 88.0%.

What are the context window sizes for Kimi K2-Instruct-0905 and Qwen3.8 Max?

Kimi K2-Instruct-0905 supports an unknown number of tokens and Qwen3.8 Max supports 256K 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-0905 and Qwen3.8 Max?

Key differences include LLM Stats Score (21.6 vs 51.9), multimodal support (no vs yes), licensing (MIT vs Qwen3.8-Max License). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2-Instruct-0905 and Qwen3.8 Max?

Kimi K2-Instruct-0905 is developed by Moonshot AI and Qwen3.8 Max is developed by Alibaba Cloud / Qwen Team.

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