Which Chinese LLM is best in 2026? We rank DeepSeek V4, Kimi K2.6, GLM-5, GLM-5.1, Qwen3.5, MiMo, and more using current BenchLM data across coding, math, reasoning, and agentic work.
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The Chinese frontier is stronger and more crowded than the old GLM-vs-Qwen-vs-DeepSeek framing suggests. DeepSeek V4 Pro (Max) now leads this slice at 87, Kimi K2.6 follows at 84, and Z.AI still has two top-tier rows with GLM-5 (Reasoning) and GLM-5.1 at 83. Alibaba still has the broadest lineup, and Moonshot's Kimi rows remain important, especially for coding.
| Rank | Model | Creator | Score | Type | Open Weight | Context |
|---|---|---|---|---|---|---|
| 1 | DeepSeek V4 Pro (Max) | DeepSeek | 87 | Reasoning | Yes | 1M |
| 2 | Kimi K2.6 | Moonshot AI | 84 | Non-Reasoning | Yes | 256K |
| 3 | GLM-5 (Reasoning) | Z.AI | 83 | Reasoning | Yes | 200K |
| 4 | GLM-5.1 | Z.AI | 83 | Non-Reasoning | Yes | 203K |
| 5 | DeepSeek V4 Pro (High) | DeepSeek | 83 | Reasoning | Yes | 1M |
| 6 | Qwen3.5 397B (Reasoning) | Alibaba | 79 | Reasoning | Yes | 128K |
| 7 | Kimi K2.5 (Reasoning) | Moonshot AI | 77 | Reasoning | No | 128K |
| 8 | DeepSeek V4 Flash (Max) | DeepSeek | 77 | Reasoning | Yes | 1M |
| 9 | Qwen3.6-27B | Alibaba | 75 | Non-Reasoning | Yes | 262K |
| 10 | Qwen3.6 Plus | Alibaba | 74 | Non-Reasoning | No | 1M |
The most important change here is that DeepSeek V4 and Kimi K2.6 have reset the top of the Chinese leaderboard. The second is that the Chinese leaderboard is no longer just one or two labs deep. DeepSeek, Moonshot, Z.AI, and Alibaba all have serious rows in the upper tier.
| Model | Creator | Score |
|---|---|---|
| Gemini 3.1 Pro | 93 | |
| GPT-5.4 Pro | OpenAI | 92 |
| Claude Opus 4.6 | Anthropic | 88 |
| DeepSeek V4 Pro (Max) | DeepSeek | 87 |
| Kimi K2.6 | Moonshot AI | 84 |
| GLM-5 (Reasoning) | Z.AI | 83 |
| Qwen3.5 397B (Reasoning) | Alibaba | 79 |
The gap is still real. The best Chinese row is 6 points behind the current 93-point mainstream proprietary leader. But that gap is much smaller than it used to be, and the Chinese rows keep one structural advantage: many of them are still open weight.
DeepSeek V4 Pro (Max) is the strongest Chinese all-rounder on BenchLM's current data. It combines the best overall score in the slice with elite coding and strong agentic performance.
Kimi K2.6 is now the second-strongest Chinese row overall and remains open weight. That makes it one of the most important Chinese releases in the current catalog.
The current coding picture is tighter than the old Kimi-only narrative.
If you care most about the broader coding category score, DeepSeek, Kimi, and Qwen remain the most interesting Chinese rows to inspect first.
GLM-5 (Reasoning) remains the strongest Chinese math-heavy row in the current ranking slice. It is still the cleanest pick when the work is reasoning-first rather than only chat-oriented.
The strongest self-hostable rows are still:
That remains one of the biggest differentiators between the Chinese frontier and the top closed Western API rows.
DeepSeek is back at the top of this slice. DeepSeek V4 Pro (Max) at 87, DeepSeek V4 Pro (High) at 83, and DeepSeek V4 Flash (Max) at 77 give the family strong coverage across coding-heavy and agentic workloads. Older DeepSeek V3.2 (Thinking) is lower at 63, so variant choice matters.
Z.AI remains a top-tier Chinese lab. GLM-5 (Reasoning) and GLM-5.1 both score 83, and GLM-5 plus GLM-4.7 still provide depth underneath.
Alibaba still has the broadest family. Qwen3.5 397B (Reasoning) remains the strongest Qwen row at 79, while Qwen3.6-27B, Qwen3.6 Plus, Qwen3.5-122B-A10B, and Qwen3.5 397B give Alibaba a wide spread of options.
Moonshot remains highly relevant because Kimi K2.6 now scores 84 overall and 88.7 on the coding category. Kimi K2.5 (Reasoning) is still one of the stronger Chinese coding-oriented rows, and the non-reasoning Kimi K2.5 remains a useful open-weight deployment option.
MiMo-V2-Flash still shows up as a credible mid-tier Chinese row at 63, but it is no longer close to the very top of this slice.
The Chinese ecosystem still keeps one major edge over the top proprietary Western rows: access.
| Model | Score | Weights available |
|---|---|---|
| DeepSeek V4 Pro (Max) | 87 | Yes |
| Kimi K2.6 | 84 | Yes |
| GLM-5 (Reasoning) | 83 | Yes |
| GLM-5.1 | 83 | Yes |
| DeepSeek V4 Pro (High) | 83 | Yes |
| Qwen3.5 397B (Reasoning) | 79 | Yes |
| Qwen3.6-27B | 75 | Yes |
If you need downloadable weights, self-hosting, or deeper control of the inference stack, the Chinese frontier is still structurally stronger than the closed Western API tier.
The current Chinese leaderboard is no longer a one-row story.
The top Chinese rows are now genuinely competitive mid-to-high frontier systems, even if they still trail the very top proprietary leaders on overall score.
Check the full rankings at /best/chinese-models for the live table as new benchmark rows land.
What is the best Chinese LLM in 2026? DeepSeek V4 Pro (Max) currently leads BenchLM's Chinese leaderboard at 87, followed by Kimi K2.6 at 84, GLM-5 (Reasoning) and GLM-5.1 at 83, and Qwen3.5 397B (Reasoning) at 79.
Is DeepSeek better than GPT-5.4? The newer DeepSeek V4 Pro (Max) is much closer, scoring 87 versus GPT-5.4 at 88 and Gemini 3.1 Pro at 93 on BenchLM's current data. Older DeepSeek V3.2 (Thinking) scores 63.
Which Chinese LLM is best for coding? DeepSeek V4 Pro (Max), Kimi K2.6, DeepSeek V4 Pro (High), and Qwen3.5 397B (Reasoning) are among the strongest Chinese coding rows, with GLM-5.1 also firmly in the conversation.
Are Chinese LLMs open source? Many of the strongest rows are open weight, but that is not the same as strict OSI-open-source status.
How do Chinese LLMs compare to ChatGPT and Claude? They are closer than they were a year ago, but the best Chinese row still trails the current 93-point mainstream proprietary leader by 6 points.
All benchmark data comes from BenchLM's live dataset. Rankings reflect the current site data rather than older pre-v4 scoring snapshots.
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