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Best Chinese AI Models in 2026

MiMo-V2.6-Pro is first among Chinese AI models by point estimate on the October 2026 ranking at 73.7, followed by Kimi K3 at 70 and Qwen3.8 Max at 69.7. Conditional score ranges do not establish rank confidence. Each row shows its evidence status and conditional 90% score interval.

Bottom line: start with the live overall leader when broad benchmark performance is the constraint. Switch to the highest open-weight row when deployment control matters, and do not use a narrow point gap as the only tie-breaker.

Full Rankings (67 ranked)

1
MiMo-V2.6-Pro
Xiaomi·Open Weight·1M

73.7

BenchAlign v5.8

Estimated

Conditional range 63.95–83.39

2
Kimi K3
Moonshot AI·Pending·1.05M

70

BenchAlign v5.8

Supported

90% interval 65.85–74.04

3
Qwen3.8 Max
Alibaba·Open Weight·1M

69.7

BenchAlign v5.8

Supported

90% interval 65.65–73.81

4
Step 5 Preview
StepFun·Open Weight·1M

69.6

BenchAlign v5.8

Estimated

Conditional range 59.85–79.29

5
Ling 3.1 Flash
InclusionAI·Open Weight·262K

68.1

BenchAlign v5.8

Estimated

Conditional range 53.73–82.43

6
GLM-5.3
Z.AI·Open Weight·1M

68

BenchAlign v5.8

Supported

90% interval 63.49–72.43

7
MiniMax M3.1 Flash
MiniMax·Proprietary·1M

67.1

BenchAlign v5.8

Estimated

Conditional range 52.75–81.45

8
DeepSeek V4.1 Flash 1017
DeepSeek·Open Weight·1M

65.7

BenchAlign v5.8

Supported

90% interval 60.68–70.66

9
MiMo-V2.6-Flash
Xiaomi·Open Weight·1M

64.6

BenchAlign v5.8

Estimated

Conditional range 54.87–74.31

10
DeepSeek V4 Pro 0813
DeepSeek·Open Weight·1M

63.2

BenchAlign v5.8

Estimated

Conditional range 48.85–77.55

11
Qwen3.8-Flash-Next
Alibaba·Open Weight·262K

62.9

BenchAlign v5.8

Estimated

Conditional range 48.51–77.21

12
Qwen3.7 Max
Alibaba·Proprietary·1M

62.6

BenchAlign v5.8

Supported

90% interval 52.85–72.33

13
Hy4 preview
Tencent·Open Weight·1M

61.4

BenchAlign v5.8

Estimated

Conditional range 47.00–75.70

14
GLM-5.2
Z.AI·Open Weight·1M

60.5

BenchAlign v5.8

Supported

90% interval 52.61–68.45

15
Qwen3.8-27B
Alibaba·Open Weight·262K

59.6

BenchAlign v5.8

Supported

90% interval 53.72–65.53

16
GLM-5.3-Flash
Z.AI·Open Weight·1M

58.5

BenchAlign v5.8

Estimated

Conditional range 48.81–68.25

17
Kimi K2.6
Moonshot AI·Open Weight·256K

58.4

BenchAlign v5.8

Estimated

Conditional range 48.68–68.13

18
GLM-5.1
Z.AI·Open Weight·203K

56.3

BenchAlign v5.8

Supported

90% interval 45.58–67.01

19
Kimi K2.5 (Reasoning)
Moonshot AI·Proprietary·128K

56.2

BenchAlign v5.8

Estimated

Conditional range 41.83–70.53

20
Qwen3.5 397B
Alibaba·Open Weight·128K

55.4

BenchAlign v5.8

Estimated

Conditional range 41.07–69.77

21
Qwen 3.6 Max (preview)
Alibaba·Proprietary·256K

55.1

BenchAlign v5.8

Estimated

Conditional range 45.35–64.79

22
MiniMax M3
MiniMax·Open Weight·1M

55

BenchAlign v5.8

Supported

90% interval 45.58–64.36

23
GLM-5
Z.AI·Open Weight·200K

54.9

BenchAlign v5.8

Supported

90% interval 44.17–65.53

24
Qwen3.6 Plus
Alibaba·Proprietary·1M

53.8

BenchAlign v5.8

Supported

90% interval 44.19–63.40

25
Qwen3.7 Plus
Alibaba·Proprietary·1M

53.8

BenchAlign v5.8

Supported

90% interval 42.69–64.83

26
GLM-5-Turbo
Z.AI·Proprietary·200K

53.2

BenchAlign v5.8

Estimated

Conditional range 43.52–62.96

27
Kimi K2.5
Moonshot AI·Open Weight·256K

53.1

BenchAlign v5.8

Supported

90% interval 44.43–61.67

28
MiMo-V2.5-Pro
Xiaomi·Proprietary·1M

53

BenchAlign v5.8

Supported

90% interval 36.04–69.98

29
MiMo-V2-Pro
Xiaomi·Proprietary·1M

52.9

BenchAlign v5.8

Estimated

Conditional range 43.22–62.66

30
Hy3
Tencent·Open Weight·256K

52.5

BenchAlign v5.8

Estimated

Conditional range 42.76–62.20

31
Hy3 Preview
Tencent·Open Weight·256K

52.2

BenchAlign v5.8

Estimated

Conditional range 37.88–66.58

32
DeepSeek V3.2
DeepSeek·Open Weight·128K

50.2

BenchAlign v5.8

Supported

90% interval 36.74–63.64

33
MiMo-V2-Omni
Xiaomi·Proprietary·262K

50

BenchAlign v5.8

Estimated

Conditional range 40.31–59.75

34
MiniMax M2.5
MiniMax·Proprietary·128K

50

BenchAlign v5.8

Supported

90% interval 40.77–59.14

35
GLM-5V-Turbo
Z.AI·Proprietary·200K

49.6

BenchAlign v5.8

Estimated

Conditional range 39.91–59.36

36
Kimi K2.7 Code
Moonshot AI·Open Weight·256K

49.4

BenchAlign v5.8

Supported

90% interval 42.17–56.53

37
Qwen3.5 Plus
Alibaba·Proprietary·1M

48.9

BenchAlign v5.8

Estimated

Conditional range 34.55–63.25

38
GLM-4.7
Z.AI·Open Weight·200K

48.8

BenchAlign v5.8

Supported

90% interval 36.70–60.99

39
Qwen3.5-27B
Alibaba·Open Weight·262K

48.6

BenchAlign v5.8

Estimated

Conditional range 38.92–58.36

40
Qwen3.6-27B
Alibaba·Open Weight·262K

48.6

BenchAlign v5.8

Estimated

Conditional range 34.23–62.92

41
MiniMax M2.7
MiniMax·Open Weight·200K

48.2

BenchAlign v5.8

Supported

90% interval 36.82–59.55

42
Qwen3.7 Flash
Alibaba·Proprietary·1M

47

BenchAlign v5.8

Estimated

Conditional range 32.63–61.33

43
Ling 3.0 Flash VL
InclusionAI·Open Weight·262K

46.8

BenchAlign v5.8

Estimated

Conditional range 32.47–61.16

44
Qwen3.5-35B-A3B
Alibaba·Open Weight·262K

45.8

BenchAlign v5.8

Supported

90% interval 34.82–56.78

45
Ling 3.0 Flash
InclusionAI·Open Weight·262K

45.1

BenchAlign v5.8

Estimated

Conditional range 30.76–59.46

46
Step 3.7 Flash
StepFun·Open Weight·256K

43.7

BenchAlign v5.8

Estimated

Conditional range 29.30–58.00

47
Qwen3.6-35B-A3B
Alibaba·Open Weight·262K

43.5

BenchAlign v5.8

Estimated

Conditional range 29.15–57.85

48
Qwen3.5 Flash
Alibaba·Proprietary·1M

42.8

BenchAlign v5.8

Estimated

Conditional range 33.04–52.48

49
Step 3.5 Flash
StepFun·Open Weight·256K

42.1

BenchAlign v5.8

Estimated

Conditional range 32.40–51.85

50
Qwen3.5-122B-A10B
Alibaba·Open Weight·262K

41.7

BenchAlign v5.8

Estimated

Conditional range 31.99–51.43

51
DeepSeek-R1
DeepSeek·Open Weight·128K

41.1

BenchAlign v5.8

Supported

90% interval 26.81–55.30

52
MiMo-V2-Flash
Xiaomi·Open Weight·256K

41

BenchAlign v5.8

Estimated

Conditional range 31.27–50.71

53
DeepSeek V3.1
DeepSeek·Open Weight·128K

40.8

BenchAlign v5.8

Supported

90% interval 24.22–57.30

54
GLM-4.6
Z.AI·Open Weight·200K

40

BenchAlign v5.8

Estimated

Conditional range 30.28–49.72

55
Qwen3 Max
Alibaba·Proprietary·1M

39.6

BenchAlign v5.8

Estimated

Conditional range 25.22–53.92

56
DeepSeek V3.1 (Reasoning)
DeepSeek·Open Weight·128K

39.1

BenchAlign v5.8

Estimated

Conditional range 29.42–48.87

57
GLM-4.7-Flash
Z.AI·Open Weight·200K

39.1

BenchAlign v5.8

Estimated

Conditional range 29.41–48.85

58
DeepSeek V3 0324
DeepSeek·Open Weight·128K

36.5

BenchAlign v5.8

Supported

90% interval 20.02–52.89

59
GLM-4.5-Air
Z.AI·Proprietary·128K

34.9

BenchAlign v5.8

Estimated

Conditional range 25.19–44.64

60
Kimi K2
Moonshot AI·Proprietary·128K

33.5

BenchAlign v5.8

Estimated

Conditional range 23.74–43.18

61
Ling 2.6 Flash
InclusionAI·Open Weight·262K

32.5

BenchAlign v5.8

Estimated

Conditional range 18.12–46.82

62
DeepSeek V3
DeepSeek·Open Weight·128K

31.9

BenchAlign v5.8

Supported

90% interval 15.47–48.26

63
DeepSeek R1 Distill Qwen 32B
DeepSeek·Open Weight·128K

30.8

BenchAlign v5.8

Estimated

Conditional range 16.44–45.14

64
Qwen2.5-72B
Alibaba·Open Weight·128K

28.7

BenchAlign v5.8

Estimated

Conditional range 18.99–38.43

65
Qwen3-Omni-30B-A3B-Instruct
Alibaba·Open Weight·N/A

28.1

BenchAlign v5.8

Estimated

Conditional range 13.76–42.46

66
MiniMax M1 80k
MiniMax·Proprietary·80K

27.6

BenchAlign v5.8

Estimated

Conditional range 17.84–37.28

67
Qwen2.5 Coder 32B Instruct
Alibaba·Open Weight·128K

26.6

BenchAlign v5.8

Estimated

Conditional range 16.85–36.29

How to choose

Key Takeaways

The top model is MiMo-V2.6-Pro by Xiaomi with a BenchAlign v5.8 score of 73.7 and Estimated evidence.

The best open-weight model is MiMo-V2.6-Pro at position #1.

67 models are included in this ranking.

Score in Context

What these scores mean

Rows use the same current public overall contract as the main leaderboard. On BenchAlign v5.8 builds, Supported and Estimated describe the evidence behind a position; they are not separate score scales.

Known limitations

Lab origin is a catalog classification, not a Chinese-language evaluation. The ranking does not score license terms, serving cost, throughput, data residency, regional API availability, or fit for a private workload.

About this ranking

Ranking data as of October 19, 2026

Use this page for the current Chinese-model order. The table rebuilds from the active public ranking lane rather than preserving a copied winner, so the first row changes with the same contract used by the overall leaderboard.

This is the public BenchAlign v5.8 overall lane filtered to tracked Chinese labs. “Chinese” describes lab origin here; it is not a score of Chinese-language quality.

The live Chinese-lab slice currently starts with MiMo-V2.6-Pro, followed by Kimi K3 and Qwen3.8 Max. All three use the same BenchAlign v5.8 contract as the overall leaderboard. Every row above shows its evidence label and conditional 90% score interval because narrow point gaps should not look decisive.

The best open-weight option is MiMo-V2.6-Pro (ranked #1 with a score of 73.7). Open-weight models are highly competitive in this category — self-hosting is a viable alternative to proprietary APIs.

This ranking uses the public BenchAlign v5.8 overall contract. For detailed model profiles, click any model name above. To compare two specific models head-to-head, use the "vs #" links.

Questions

What is the best Chinese AI model right now?

The answer box and first row above are the current decision receipt. They rebuild from the active public ranking lane, so use them instead of a copied winner sentence. When BenchAlign v5.8 is active, check the row’s evidence label and score interval before treating a narrow lead as decisive.

Which Chinese AI model is best for coding?

Use the coding leaderboard rather than this overall slice. Coding applies a different evidence mix, so its first row can differ from the broad leader shown here. A production choice should also account for repository language, tool use, latency, context needs, and the evidence available for that position.

Are the leading Chinese AI models open source?

Some leading rows are open weight and others are proprietary. Open weight means downloadable parameters are available under a model-specific license; it does not guarantee an OSI-approved license, unrestricted commercial use, reproducible training data, or inexpensive deployment. Read the license before choosing a self-hosted path.

Why is this page different from the Chinese LLM article?

This page owns the current ranking and regenerates with the data. The article is a dated analysis of why two scoring paths once produced different leaders. It remains useful as an audit trail, but it should not be read as a second live leaderboard or a competing recommendation page.

Explore More

Last updated: October 19, 2026

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