Chinese Models Dominate OpenRouter Top 3
๐Ÿฆ™#leaderboard#token-usage#chinese-llmsFreshcollected in 2h

Chinese Models Dominate OpenRouter Top 3

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๐Ÿฆ™Read original on Reddit r/LocalLLaMA

๐Ÿ’กChinese LLMs crush US models on OpenRouter usageโ€”switch for cheaper, high-volume inference?

โšก 30-Second TL;DR

What changed

Top model hits 3T+ tokens/week on OpenRouter

Why it matters

Highlights rapid rise of Chinese LLMs in real-world usage, signaling shift in API provider preferences for cost-effective high-performers.

What to do next

Benchmark top OpenRouter Chinese models like Qwen for your inference workloads.

Who should care:Developers & AI Engineers

๐Ÿง  Deep Insight

Web-grounded analysis with 5 cited sources.

๐Ÿ”‘ Key Takeaways

  • โ€ขDeepSeek V3 and V3.1, along with Qwen3 and MoonshotAI's Kimi K2.5, are prominent Chinese models available on OpenRouter, featuring advanced capabilities like mixture-of-experts architecture and multimodal support[2][3][5].
  • โ€ขDeepSeek-V3.1 is a 671B parameter hybrid reasoning model with 37B active parameters, supporting up to 128K context length via two-phase training and FP8 microscaling for efficient inference[2].
  • โ€ขKimi K2.5 from Moonshot AI achieves 60.4% on SWE-bench Verified, leading open-source models in software bug fixing, code reasoning, visual coding, and agentic tool-calling after training on 15T mixed tokens[3].
๐Ÿ“Š Competitor Analysisโ–ธ Show
ModelOriginKey FeaturesBenchmarksPricing Notes
DeepSeek-V3.1Chinese671B params, 37B active MoE, 128K context, FP8 inference, reasoning modesStrong on various tasksNot specified
Kimi K2.5Chinese (Moonshot AI)Multimodal, visual coding, agent swarm60.4% SWE-bench VerifiedNot specified
Qwen3.5 PlusChinese (Alibaba)Embeddings, multilingual, reasoningAdvances in retrieval/classificationVaries >128K input
Mistral Large 3 2512FrenchSparse MoE, 41B active (675B total)Most capable to dateNot specified
Llama 3.1 8BUS (Meta)Instruct-tuned, efficientStrong vs closed models in evalsNot specified

๐Ÿ› ๏ธ Technical Deep Dive

  • DeepSeek V3/V3.1: 685B MoE (37B active in V3.1), hybrid reasoning with thinking/non-thinking modes, two-phase long-context training to 128K tokens, FP8 microscaling for inference efficiency[2].
  • Kimi K2.5: Native multimodal model built on Kimi K2 with 15T mixed visual/text pretraining, self-directed agent swarm, excels in visual coding and tool-calling[3].
  • Qwen3.5 Plus / Embedding: Proprietary for text embedding/ranking, multilingual (English, Chinese, etc.), long-text understanding, supports reasoning via reasoning parameter and reasoning_details[2][5].
  • General: Many support function calling, Apache 2.0 licensing for some distillable models[2].

๐Ÿ”ฎ Future ImplicationsAI analysis grounded in cited sources

Dominance of Chinese models like DeepSeek, Qwen, and Kimi on OpenRouter signals accelerated innovation in open-source AI from China, potentially increasing their global market share to 35%+ by April 2026 per forecasts, challenging US models like Grok and Llama in usage, efficiency, and specialized tasks such as reasoning and multimodal capabilities.

๐Ÿ“Ž Sources (5)

Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.

  1. metaculus.com
  2. openrouter.ai
  3. openrouter.ai
  4. openrouter.ai
  5. openrouter.ai

Chinese models claimed the top 3 spots on OpenRouter this week, with one exceeding 3 trillion tokens. Multiple models surpassed 1 trillion tokens for the first time. This marks a shift as they outperform US models like Grok 4 fast.

Key Points

  • 1.Top model hits 3T+ tokens/week on OpenRouter
  • 2.Multiple models exceed 1T tokens/week first time
  • 3.Chinese models outperform US counterparts
  • 4.Grok 4 fast previously led high-usage

Impact Analysis

Highlights rapid rise of Chinese LLMs in real-world usage, signaling shift in API provider preferences for cost-effective high-performers.

๐Ÿ“ฐ

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Original source: Reddit r/LocalLLaMA โ†—