Claude Haiku 5.5
mercury-3 ，这是一款面向重视响应速度的应用场景的扩散式语言模型。与逐个词元生成文本的常见模型不同，扩散模型先生成答案的大致草稿，再经过多轮迭代不断修改，因此能够一次生成多个词语。据称该模型在英伟达显卡上的吞吐量为每秒 1068 个词元 ，相比之下，Claude Haiku 5.5 约为 240 个 ，GPT-6 Luna 约为 130 个 。 mercury-3 ，重点面向人工智能代理、搜索、客服、辅导等应用推广该模型，因为这些场景中的多次交互会让细小延迟不断累积。 请先注册 ： https://aiask.me/ 开通方法 ：API 密钥 -> 创建密钥 -> 分组选择 组合，再选“默认”分组 默认分组 API 价格查看 ： https://aiask.me/model-plaza
This explanation quotes or summarizes the cited source record. Saving creates a bookmark on this device, with no automatic account sync.
- First observed in our collection
- Nov 2, 2026, 6:30 AM UTC
- Earliest cited publication
- Nov 2, 2026, 6:25 AM UTC
- Last observed
- Nov 5, 2026, 3:41 PM UTC
Evidence in the last complete seven days
- Source mentions
- 1 Previous seven days 0
- Distinct sources
- 1 Previous 0
- Comparable growth
- Not comparable
- Ranking appearances
- 0
Collection observations and undated records are separate from dated publication counts. Observed in 7d：1 · Undated records：1
Collection coverage · Limited historyCurrent / previous observed days 7 / 3
Counts use complete UTC days. First observed means first seen by this collection, not when a term was coined.
Current window：2026-10-29 → 2026-11-05 (end excluded) · History 11 days
| Source | Current days | Previous days | Last success |
|---|---|---|---|
| arXiv | 6 | 3 | Nov 5, 2026, 10:00 AM UTC |
| arXiv | 7 | 2 | Nov 5, 2026, 10:01 AM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 3:00 PM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 3:00 PM UTC |
| Ask HN | 7 | 3 | Nov 5, 2026, 3:00 PM UTC |
| GitHub | 7 | 3 | Nov 5, 2026, 12:15 PM UTC |
| GitHub Issues | 7 | 3 | Nov 5, 2026, 10:01 AM UTC |
| GitHub Releases | 7 | 1 | Nov 5, 2026, 12:00 PM UTC |
| GitHub | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| GitHub Issues | 7 | 3 | Nov 5, 2026, 10:01 AM UTC |
| GitHub Releases | 7 | 3 | Nov 5, 2026, 3:14 PM UTC |
| GitHub | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| GitHub Issues | 7 | 3 | Nov 5, 2026, 10:01 AM UTC |
| GitHub Releases | 7 | 3 | Nov 5, 2026, 3:14 PM UTC |
| GitHub Discovery | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| GitHub Trending | 7 | 3 | Nov 5, 2026, 3:14 PM UTC |
| 7 | 2 | Nov 5, 2026, 10:00 AM UTC | |
| Hugging Face | 7 | 2 | Nov 5, 2026, 8:15 AM UTC |
| Hugging Face Spaces | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| Hacker News | 7 | 3 | Nov 5, 2026, 12:45 PM UTC |
| Hacker News | 7 | 3 | Nov 5, 2026, 3:30 PM UTC |
| Hacker News | 7 | 3 | Nov 5, 2026, 3:30 PM UTC |
| Hacker News | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| Show HN | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| MIT News | 7 | 2 | Nov 5, 2026, 10:01 AM UTC |
| OpenAI | 7 | 3 | Nov 5, 2026, 11:30 AM UTC |
| Product Hunt | 7 | 3 | Nov 5, 2026, 12:45 PM UTC |
| 量子位 | 7 | 3 | Nov 4, 2026, 10:15 AM UTC |
| OpenRouter | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| Hugging Face Models | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| HF Daily Papers | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| OpenRouter | 0 | 0 | Nov 5, 2026, 3:41 PM UTC |
| SEC EDGAR | 7 | 3 | Nov 5, 2026, 10:30 AM UTC |
| Sequoia Capital | 7 | 2 | Nov 5, 2026, 10:00 AM UTC |
| Simon Willison | 0 | 0 | Nov 5, 2026, 3:13 PM UTC |
| TechCrunch | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
| Contracts Finder | 7 | 3 | Nov 5, 2026, 10:00 AM UTC |
| V2EX | 7 | 3 | Nov 5, 2026, 2:30 PM UTC |
- Counts describe monitored public sources, not the whole web or search demand.
- Both weeks need adequate, comparable collection coverage.
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.
View accessible daily data
| UTC date | Mentions | Sources | Observations | Ranking appearances |
|---|---|---|---|---|
| 2026-10-22 | 0 | 0 | 0 | 0 |
| 2026-10-23 | 0 | 0 | 0 | 0 |
| 2026-10-24 | 0 | 0 | 0 | 0 |
| 2026-10-25 | 0 | 0 | 0 | 0 |
| 2026-10-26 | 0 | 0 | 0 | 0 |
| 2026-10-27 | 0 | 0 | 0 | 0 |
| 2026-10-28 | 0 | 0 | 0 | 0 |
| 2026-10-29 | 0 | 0 | 0 | 0 |
| 2026-10-30 | 0 | 0 | 0 | 0 |
| 2026-10-31 | 0 | 0 | 0 | 0 |
| 2026-11-01 | 0 | 0 | 0 | 0 |
| 2026-11-02 | 1 | 1 | 1 | 0 |
| 2026-11-03 | 0 | 0 | 0 | 0 |
| 2026-11-04 | 0 | 0 | 0 | 0 |
| 2026-11-05 | 0 | 0 | 1 | 1 |
Source evidence
Sources in the evidence shown：OpenRouter 1 · V2EX 1
OpenRouter · Published Not supplied
Claude Haiku 5.5 (Max)
V2EX · Published Nov 2, 2026
[推广] [AIask]上线新模型 mercury-3，以扩散生成推理方式加速模型响应速度
mercury-3 ，这是一款面向重视响应速度的应用场景的扩散式语言模型。与逐个词元生成文本的常见模型不同，扩散模型先生成答案的大致草稿，再经过多轮迭代不断修改，因此能够一次生成多个词语。据称该模型在英伟达显卡上的吞吐量为每秒 1068 个词元 ，相比之下，Claude Haiku 5.5 约为 240 个 ，GPT-6 Luna 约为 130 个 。 mercury-3 ，重点面向人工智能代理、搜索、客服、辅导等应用推广该模型，因为这些场景中的多次交互会让细小延迟不断累积。 请先注册 ： https://aiask.me/ 开通方法 ：API 密钥 -> 创建密钥 -> 分组选择 组合，再选“默认”分组 默认分组 API 价格查看 ： https://aiask.me/model-plaza
View source record →
Review priority 40 / 100
This score orders research candidates. It is not search volume, a forecast or verified commercial demand.
Evidence
8 / 30Distinct dated articles or first observations; repeat crawling adds nothing.
Publisher diversity
8 / 25Conservative owner grouping; syndicated copies count once.
Comparable change
0 / 20Comparable complete weeks only; no percentage from a zero baseline.
Recent evidence
15 / 15Latest publication or first observation, not repeated fetch time.
Name specificity
9.4 / 10Explicit 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.
- Undated observations cannot establish publication growth.
- 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.
- The previous week is too small for a reliable percentage change.
- Current evidence comes from one publisher or owner.