What this is
Chinese AI labs ship distinct reasoning model lines parallel to their general-purpose flagships, mirroring OpenAI's o-series split. This page is a 2026-05-15 head-to-head of the major Chinese reasoning models.
Chinese Reasoning Models (2026)
| Model | BenchLM Chinese score | Parent line | Architecture | License |
|---|---|---|---|---|
| DeepSeek V4-Pro (Max) | 87 (leader) | DeepSeek V4 | 1.6T MoE | MIT |
| Kimi K2.6 | 84 | Kimi K2 | 1T MoE / 32B active | Open weights |
| GLM-5 (Reasoning) | 83 | GLM-5 | 744B MoE / 40B active | Open weights (5.1) |
| GLM-5.1 | 83 | GLM-5.1 | Refined GLM-5 | Open weights |
| Qwen 3.5 397B (Reasoning) | 79 | Qwen 3.5 | 397B MoE / 17B active | Apache 2.0 base |
| QwQ-32B | ~76 | Qwen 2.5 reasoning | 32B dense | Apache 2.0 |
| ERNIE X1.1 | ~74 | ERNIE 4.5 → X1 | Proprietary | Proprietary |
| Step 3.5 Flash | ~73 | Step (Stepfun) | Compact reasoning | Open weights |
| Hy3preview (Tencent) | ~72 | Hunyuan | 295B MoE / 21B active | Open-source |
Strengths by Sub-Task
| Sub-task | Best pick |
|---|---|
| Math + logic (AIME-style) | QwQ-32B (best small model) or DeepSeek V4-Pro (best overall) |
| Long-chain agentic reasoning | Kimi K2.6 (300-agent swarm) |
| Scientific reasoning (GPQA Diamond) | Qwen 3.5 (88.4% GPQA Diamond) |
| Lowest cost per reasoning query | Step 3.5 Flash |
| Chinese-language reasoning + Q&A | ERNIE X1.1 |
| Enterprise compliance + Cambricon | GLM-5 / GLM-5.1 |
| Fast + slow thinking modes | Hy3preview (Tencent Hunyuan) |
| Permissive licence (MIT) | DeepSeek V4-Pro reasoning |
Six Things the Comparison Tells You
- DeepSeek V4-Pro leads the Chinese reasoning leaderboard at 87 (BenchLM). Kimi K2.6 at 84 is the closest competitor.
- QwQ-32B punches above its weight at 32B params. Best small reasoning model from any Chinese lab.
- Qwen 3.5 leads scientific reasoning at 88.4% GPQA Diamond. Best-in-class open weights and competitive with proprietary frontier.
- Hy3preview (Tencent) is the first to ship native fast + slow thinking in a single model — routing inference depth dynamically.
- The Chinese reasoning leaderboard is denser than the Western one. Five Chinese models above BenchLM 80; only two Western models (Claude Opus 4.7, GPT-5.4 Pro) at that tier.
- Cost-per-reasoning-query has collapsed. Step 3.5 Flash and ByteDance Doubao reasoning variants undercut OpenAI o-series by 5-10x.
What This Means for AI Visibility
Reasoning-mode AI assistants increasingly drive long-form citation answers — research, technical writeups, analyst reports. As Chinese reasoning models absorb a growing share of agentic and analytical workloads, brands should test how they appear inside reasoning-mode outputs from DeepSeek, Kimi, and GLM — not just the chat-mode outputs of ChatGPT and Claude.
Methodology
BenchLM scores from BenchLM's best Chinese LLMs 2026. QwQ-32B benchmarks from the Qwen team. Hy3preview specs from Tencent's release. Step 3.5 Flash, GLM-5 reasoning, and DeepSeek V4-Pro from each lab's release docs. Cross-checked against TokenMix's Q2 2026 update and Index.dev's Kimi/Qwen/DeepSeek comparison.
How Presenc AI Helps
Presenc AI runs brand prompts on each Chinese reasoning model alongside ChatGPT o-series and Claude reasoning modes. Reasoning-mode outputs cite differently from chat-mode outputs, so brand visibility per reasoning surface is its own measurement axis.