GLM-5.2

Evidence in the last complete seven days

Source mentions

2

Previous seven days 1

Distinct sources

2

Previous 1

Comparable growth

Not comparable

Ranking appearances

0

Collection observations and undated records are separate from dated publication counts. Observed in 7d：1 · Undated records：0

Daily history · up to 90 days

Bars show dated source mentions. The latest UTC day may be incomplete. Zero mentions and missing collection coverage are different conditions.

Dotted markers indicate days with no record. They are not counted as zero mentions.

Source evidence

Sources in the evidence shown：HF Daily Papers 1 · V2EX 2 · GitHub Releases 1

1. HF Daily Papers · Published Nov 2, 2026

   Multi-layer Indexer: Overlapping Selection and Attention in DeepSeek Sparse Attention

   Sparse attention cuts the cost of long-context inference by making the attention matrix sparse: each query attends only a subset of the sequence, chosen by a fixed pattern or, in recent production LLMs, learned per query. In DeepSeek Sparse Attention (DSA), the attention of DeepSeek-V3.2 and the GLM-5 family, every layer is preceded by a lightning indexer th

2. V2EX · Published Oct 29, 2026

   [问与答] 奇怪，豆包的版本号隐身了？

   现在社区里聊大模型，基本都能脱口而出： 御三家: gpt6.0 6.1 、 claude5.5 5.1 、 gemini3.1 4.0 国模： glm5.2 、 ds4.1 1017 、 qwen3.7 3.8 、 mimo2.6 hy4 但是豆包呢？ 给人感觉存在感特别低：既不刷版本号，也不打榜， 也不开源 开源不开源对个人用户意义不大 毕竟无法部署 。 更矛盾的是字节作为最有实力的宇宙大厂+Xpert(字节跳动大模型专家数据平台)又一直不间断的在发骚扰短信招各个垂直领域的专家。 所以豆包的优势/长处在哪儿？豆姐在哪发财呢?

   View source record →

3. V2EX · Published Oct 23, 2026

   [程序员] 为什么很多人都把 DeepSeek 神化了，看不起国内豆包和其它 LLM？

   我认为 DeepSeek 、MiniMax 、Kimi 、GLM 这些 LLM 公司被严重高估了： 月活（ MAU ） ： 豆包 4.2 亿，千问 1.7 亿，DeepSeek 1.2 亿，智谱 2000 万，Kimi 1000 万； 商业化（ ARR ） ： 豆包 272 亿，智谱 68 亿、阿里 80 亿、DeepSeek 27-34 亿、Kimi 20 亿； 开源贡献 ： Qwen：开源了超过 460 个模型，衍生模型超 30 万个，全球下载量破 20 亿次； GLM：开源 50 余款模型，GLM-5.2 以 51 分位居全球开源智能指数榜首； DeepSeek：开源了 DeepSeek-V4 、DeepSeek-R1 、DeepSeek-VL 等模型。 豆包的战略和 Google 的 Gemini 是很

   View source record →

4. GitHub Releases · Published Aug 26, 2026

   Release v5.16.1

   Release v5.16.1 This is a special release as we include GLM! (and a few small fixes) GLM-5.3-Flash GLM-5.3-Flash, the first natively multimodal model in the GLM-5 series. With 320B total parameters and just 18B active parameters, it outperforms GLM-5.2 across benchmarks and real-world workloads at one-tenth the price, while approaching Claude Opus 4.8 on cod

   View source record →

Review priority 53 / 100

This score orders research candidates. It is not search volume, a forecast or verified commercial demand.

• Evidence

  12.7 / 30

  Distinct dated articles or first observations; repeat crawling adds nothing.

• Publisher diversity

  16 / 25

  Conservative owner grouping; syndicated copies count once.

• Comparable change

  0 / 20

  Comparable complete weeks only; no percentage from a zero baseline.

• Recent evidence

  14.9 / 15

  Latest publication or first observation, not repeated fetch time.

• Name specificity

  9.4 / 10

  Explicit entities and technical concepts outrank ambiguous acronyms.

Limitations and interpretation

• First observation is a collection milestone, not proof that a word or product is new to the world.
• Counts describe monitored public sources, not the whole web or search demand.
• First observed here is not the invention date of a name or idea.
• Candidates come from public titles, summaries and entity URLs, not verified full-text analysis.
• Owner grouping is conservative; undisclosed syndication may remain.
• Repeat ranking appearances are observations, not new articles or independent endorsements.
• Both weeks need adequate, comparable collection coverage.
• Sources behind this term changed or lack a comparable baseline.
• Recent evidence includes collection over three days after publication.
• The previous week is too small for a reliable percentage change.