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  "markdown": "Co-founder and Chief People Officer, Alibaba Group.\n\nJane Jiang joined Alibaba in 1999 as a member of its founding team and has been its chief people officer since April 2023, after six years as deputy. Over the years she has led China TrustPass product planning, global operations and marketing for Alibaba.com, and the company's credit system development.\n\n## What Jane builds\n\n- [Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/tools/qwen3-30b-a3b-instruct-2507.md), graded C, 56.6/100, in Open-weight models. Qwen3-30B-A3B-Instruct-2507 is Alibaba's open-weight mixture-of-experts text model, 30.5B parameters with 3.3B active, the non-thinking edition of the July 2025 Qwen3 update, with a 262,144-token context, published in BF16 and FP8 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.md), graded C, 55.7/100, in Open-weight models. Qwen3-4B-Instruct-2507 is Alibaba's open-weight dense text model of 4B parameters, the non-thinking edition of the July 2025 Qwen3 update, with a 262,144-token context, published on Hugging Face in BF16 and FP8 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3.5-122B-A10B](https://www.anchorterminal.com/tools/qwen3-5-122b-a10b.md), graded B, 63.6/100, in Open-weight models. Qwen3.5-122B-A10B is Alibaba's mid-size open-weight mixture-of-experts vision-language model, 122B parameters with 10B active, thinking on by default and a 262,144-token context, published on Hugging Face in BF16, FP8 and GPTQ 4-bit under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3.5-397B-A17B](https://www.anchorterminal.com/tools/qwen3-5-397b-a17b.md), graded B, 64.6/100, in Open-weight models. Qwen3.5-397B-A17B is Alibaba's largest open-weight Qwen3.5 model, a mixture-of-experts vision-language model of 397B parameters with 17B active, thinking on by default and a 262,144-token context, published on Hugging Face in BF16, FP8 and GPTQ 4-bit under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3.5-4B](https://www.anchorterminal.com/tools/qwen3-5-4b.md), graded C, 61.2/100, in Open-weight models. Qwen3.5-4B is Alibaba's small open-weight vision-language model, 4B language parameters with a vision encoder, thinking on by default and a 262,144-token context, published on Hugging Face in BF16 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3.5-9B](https://www.anchorterminal.com/tools/qwen3-5-9b.md), graded C, 60.5/100, in Open-weight models. Qwen3.5-9B is Alibaba's open-weight dense vision-language model of 9B parameters, with thinking on by default and a 262,144-token context, published on Hugging Face in BF16 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3.6-35B-A3B](https://www.anchorterminal.com/tools/qwen3-6-35b-a3b.md), graded B, 63.2/100, in Open-weight models. Qwen3.6-35B-A3B is Alibaba's open-weight mixture-of-experts vision-language model, 35B parameters with 3B active and a 262,144-token context, published on Hugging Face in BF16 and FP8 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3.8-Flash-Next](https://www.anchorterminal.com/tools/qwen3-8-flash-next.md), graded C, 61.8/100, in Open-weight models. Qwen3.8-Flash-Next is Alibaba's open-weight multimodal mixture-of-experts model and an experimental preview of the Qwen4 architecture, 125B parameters with 6B active plus a 51B n-gram embedding table, published on Hugging Face in BF16 and FP8. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-ASR-0.6B](https://www.anchorterminal.com/tools/qwen3-asr-0-6b.md), graded C, 61.2/100, in Speech-to-text. Qwen3-ASR-0.6B is Alibaba's compact open-weight speech recognition model for 30 languages and 22 Chinese dialects, with language identification, context hints and streaming, published on Hugging Face in BF16 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-ASR-1.7B](https://www.anchorterminal.com/tools/qwen3-asr-1-7b.md), graded B, 64.4/100, in Speech-to-text. Qwen3-ASR-1.7B is Alibaba's open-weight speech recognition model for 30 languages and 22 Chinese dialects, with language identification, context hints and streaming, published on Hugging Face in BF16 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct.md), graded C, 55.7/100, in Open-weight models. Qwen3-Coder-30B-A3B-Instruct is Alibaba's open-weight mixture-of-experts coding model, 30.5B parameters with 3.3B active, for agentic coding and tool use, with a 262,144-token context, published in BF16 and FP8 under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-Coder-Next](https://www.anchorterminal.com/tools/qwen3-coder-next.md), graded C, 57.6/100, in Open-weight models. Qwen3-Coder-Next is Alibaba's open-weight coding-agent model, an 80B mixture-of-experts with 3B active and no thinking mode, trained for tool calling across many agent scaffolds with a 262,144-token context, published on Hugging Face in BF16, FP8 and GGUF under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-Embedding-0.6B](https://www.anchorterminal.com/tools/qwen3-embedding-0-6b.md), graded B, 63.5/100, in Embeddings \u0026 rerankers. Qwen3-Embedding-0.6B is Alibaba's open-weight text embedding model of 0.6B parameters, built on Qwen3-0.6B-Base, for retrieval, classification and clustering in over 100 languages and code, with 1,024-dimension vectors and a 32K context, under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-Embedding-4B](https://www.anchorterminal.com/tools/qwen3-embedding-4b.md), graded BB, 72.9/100, in Embeddings \u0026 rerankers. Qwen3-Embedding-4B is Alibaba's open-weight text embedding model built on Qwen3-4B-Base, returning vectors of up to 2,560 dimensions for retrieval, code search and clustering in over 100 languages, under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-Embedding-8B](https://www.anchorterminal.com/tools/qwen3-embedding-8b.md), graded BB, 74.7/100, in Embeddings \u0026 rerankers. Qwen3-Embedding-8B is Alibaba's open-weight text embedding model built on Qwen3-8B-Base, returning vectors of up to 4,096 dimensions for retrieval, code search and clustering in over 100 languages, under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-TTS 12Hz 1.7B CustomVoice](https://www.anchorterminal.com/tools/qwen3-tts-1-7b-customvoice.md), graded C, 58/100, in Text-to-speech. Qwen3-TTS 12Hz 1.7B CustomVoice is Qwen's open-weight text-to-speech model with nine preset voices whose tone, emotion and pace follow a natural-language instruction, in ten languages and two Chinese dialects, with its 12 Hz speech tokenizer bundled, under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/tools/qwen3-vl-2b-instruct.md), graded C, 61/100, in Open-weight models. Qwen3-VL-2B-Instruct is Alibaba's open-weight dense vision-language model of about 2B parameters, taking text, images and video with a 262,144-token context, published on Hugging Face in BF16, FP8 and GGUF under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct.md), graded C, 58/100, in Open-weight models. Qwen3-VL-30B-A3B-Instruct is Alibaba's open-weight vision-language mixture of experts with about 31B parameters and 3B active, taking text, images and video with a 262,144-token context, published on Hugging Face in BF16, FP8 and GGUF under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct.md), graded C, 56.4/100, in Open-weight models. Qwen3-VL-32B-Instruct is Alibaba's open-weight dense vision-language model of about 32B parameters, taking text, images and video with a 262,144-token context, published on Hugging Face in BF16, FP8 and GGUF under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n- [Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/tools/qwen3-vl-4b-instruct.md), graded D, 52.6/100, in Open-weight models. Qwen3-VL-4B-Instruct is Alibaba's open-weight dense vision-language model of about 4B parameters, taking text, images and video with a 262,144-token context, published on Hugging Face in BF16, FP8 and GGUF under Apache 2.0. Co-founder and Chief People Officer, Alibaba Group, researched 2026-10-27.\n\n## Works with\n\n- [Eddie Wu](https://www.anchorterminal.com/people/eddie-wu/), Co-founder, Director and CEO, Alibaba Group\n- [Jack Ma](https://www.anchorterminal.com/people/jack-ma/), Co-founder, Alibaba Group\n- [Jin Xu](https://www.anchorterminal.com/people/jin-xu/), First author, Qwen3-Omni Technical Report\n- [Joe Tsai](https://www.anchorterminal.com/people/joe-tsai/), Co-founder and Chairman, Alibaba Group\n- [Yang Su](https://www.anchorterminal.com/people/yang-su/), Agent research lead, Qwen series\n\n## Questions\n\n### Who is Jane Jiang?\n\nJane Jiang joined Alibaba in 1999 as a member of its founding team and has been its chief people officer since April 2023, after six years as deputy. Over the years she has led China TrustPass product planning, global operations and marketing for Alibaba.com, and the company's credit system development.\n\n### What does Alibaba (Qwen team) make?\n\nAnchor Terminal lists Qwen3-30B-A3B-Instruct-2507, Qwen3-4B-Instruct-2507, Qwen3.5-122B-A10B, Qwen3.5-397B-A17B, Qwen3.5-4B, Qwen3.5-9B, Qwen3.6-35B-A3B, Qwen3.8-Flash-Next, Qwen3-ASR-0.6B, Qwen3-ASR-1.7B, Qwen3-Coder-30B-A3B-Instruct, Qwen3-Coder-Next, Qwen3-Embedding-0.6B, Qwen3-Embedding-4B, Qwen3-Embedding-8B, Qwen3-TTS 12Hz 1.7B CustomVoice, Qwen3-VL-2B-Instruct, Qwen3-VL-30B-A3B-Instruct, Qwen3-VL-32B-Instruct and Qwen3-VL-4B-Instruct from Alibaba (Qwen team). Qwen3-30B-A3B-Instruct-2507 is Alibaba's open-weight mixture-of-experts text model, 30.5B parameters with 3.3B active, the non-thinking edition of the July 2025 Qwen3 update, with a 262,144-token context, published in BF16 and FP8 under Apache 2.0.\n\n### How are Jane's tools graded?\n\nQwen3-30B-A3B-Instruct-2507 is graded C, 56.6 out of 100; Qwen3-4B-Instruct-2507 is graded C, 55.7 out of 100; Qwen3.5-122B-A10B is graded B, 63.6 out of 100; Qwen3.5-397B-A17B is graded B, 64.6 out of 100; Qwen3.5-4B is graded C, 61.2 out of 100; Qwen3.5-9B is graded C, 60.5 out of 100; Qwen3.6-35B-A3B is graded B, 63.2 out of 100; Qwen3.8-Flash-Next is graded C, 61.8 out of 100; Qwen3-ASR-0.6B is graded C, 61.2 out of 100; Qwen3-ASR-1.7B is graded B, 64.4 out of 100; Qwen3-Coder-30B-A3B-Instruct is graded C, 55.7 out of 100; Qwen3-Coder-Next is graded C, 57.6 out of 100; Qwen3-Embedding-0.6B is graded B, 63.5 out of 100; Qwen3-Embedding-4B is graded BB, 72.9 out of 100; Qwen3-Embedding-8B is graded BB, 74.7 out of 100; Qwen3-TTS 12Hz 1.7B CustomVoice is graded C, 58 out of 100; Qwen3-VL-2B-Instruct is graded C, 61 out of 100; Qwen3-VL-30B-A3B-Instruct is graded C, 58 out of 100; Qwen3-VL-32B-Instruct is graded C, 56.4 out of 100; Qwen3-VL-4B-Instruct is graded D, 52.6 out of 100, on Anchor Terminal's benchmark, which scores every listing against the same checklist.\n\n## Sources\n\n- https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507\n- https://raw.githubusercontent.com/QwenLM/Qwen3/main/README.md\n- https://qwenlm.github.io/about/\n- https://www.alibabagroup.com/en-US/about-alibaba\n- https://www.alibabagroup.com/en-US/about-alibaba-leadership-1493301768354791424\n- https://www.alibabagroup.com/en-US/about-alibaba-leadership-1637927598568767488\n- https://www.alibabagroup.com/en-US/about-alibaba-leadership-1619437000312487936\n- https://en.wikipedia.org/wiki/Jack_Ma\n- https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507\n- https://huggingface.co/Qwen/Qwen3.5-122B-A10B\n- https://raw.githubusercontent.com/QwenLM/Qwen3.8/main/README.md\n- https://huggingface.co/Qwen/Qwen3.5-397B-A17B\n- https://huggingface.co/Qwen/Qwen3.5-4B\n- https://huggingface.co/Qwen/Qwen3.5-9B\n- https://huggingface.co/Qwen/Qwen3.6-35B-A3B\n- https://huggingface.co/Qwen/Qwen3.8-Flash-Next\n- https://raw.githubusercontent.com/QwenLM/Qwen3.8-Flash-Next/main/README.md\n- https://huggingface.co/Qwen/Qwen3-ASR-0.6B\n- https://github.com/QwenLM/Qwen3-ASR\n- https://raw.githubusercontent.com/QwenLM/Qwen3-ASR/main/README.md\n- https://huggingface.co/Qwen/Qwen3-ASR-1.7B\n- https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct\n- https://raw.githubusercontent.com/QwenLM/Qwen3-Coder/main/README.md\n- https://huggingface.co/Qwen/Qwen3-Coder-Next\n- https://huggingface.co/Qwen/Qwen3-Embedding-0.6B\n- https://github.com/QwenLM/Qwen3-Embedding\n- https://raw.githubusercontent.com/QwenLM/Qwen3-Embedding/main/README.md\n- https://huggingface.co/Qwen/Qwen3-Embedding-4B\n- https://huggingface.co/Qwen/Qwen3-Embedding-8B\n- https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice\n- https://github.com/QwenLM/Qwen3-TTS\n- https://raw.githubusercontent.com/QwenLM/Qwen3-TTS/main/README.md\n- https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct\n- https://raw.githubusercontent.com/QwenLM/Qwen3-VL/main/README.md\n- https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct\n- https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct\n- https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct\n\nNot the same person as [Jane Jiang](https://www.anchorterminal.com/people/jane-jiang/) (Accio (Alibaba International, Alibaba Group)), [Jane Jiang](https://www.anchorterminal.com/people/jane-jiang-3/) (AgentScope (Alibaba Group)), as far as the research can tell.\n\nThese are the people building the tools we list, named for their public role in the company or project behind a listing, from public pages, with the date it was researched. They don't work for Anchor Terminal (our own team is on the about page, /about/#author). We show public roles, public profiles and what the listing pages show, nothing private. To correct something, send an about or a photo, or have a page removed, write to privacy@anchorterminal.com.\n",
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