**Evaluating lottery predictions** I need to produce pure HTML in Cantonese (Traditional) with colorful emphasis, and bold key paragraphs. The user provided the actual draw results: 18, 37, 38, 34, 6, 29, 39. Since Mark Six typically includes 6 main numbers plus a special, it looks like the first six numbers might be the main ones. I’ll compare the predictions of various models against these actual results, aiming to assess at least the top 10 models and the bottom 6.**Assessing model predictions** I’m comparing predictions from different models. For GPT-4.1 (recent40), it has three combinations. Combo A doesn’t match any actual numbers. Combo B has 1 hit with 39, and Combo C also has 0 matches. So, GPT-4.1 only gets 1 hit overall. For Claude 4.5 Sonnet (40期), the first group hits 39 (1 match), the second group hits both 18 and 37 (2 matches), and the third group hits 29 (1 match). The best group from Claude has 2 hits, which is pretty impressive!**Evaluating more predictions** DeepSeek V3.2 has three groups of predictions. The first group has no hits, the second hits 39 (1 match), and the third hits both 18 and 29 (2 matches), giving DeepSeek a total of 2 hits. For OpenAI O1, it only matches 29 from the set of six numbers (1 hit), while OpenAI O3 has no matches at all. Now, GPT-4.1 proposes five combos. Combo A also has no hits, Combo B hits 39 and 6 (2 hits), Combo C has 29 (1 hit), and Combo D seems to hit 0.**Continuing the prediction analysis** For Combo D, it looks like there are no hits, and Combo E also hits none. The best result so far is 2 hits from Combo B of GPT-4.1. Moving to Claude 4.5 Sonnet, I evaluate five groups. The first group hits none, the second hits none, the third hits 39 (1 match), the fourth hits 34 (1 match), and the fifth hits both 29 and 38 (2 matches), making the best overall 2 hits. Lastly, for "GPT 5," the sets are proposing several combinations, but again, 39 is the only hit in the final set.**Summarizing hit evaluations** In evaluating the sets, I found that several combinations hit varying numbers. For Set C, there was 1 hit (37); Set D had 1 hit (34); and impressively, Set E had 3 hits (18, 29, 38), making it the best option. For O1 Pro, the results ranged from 0 hits to 1 hit across five groups, with Set B including 6 as a match. Claude 4.5 Sonnet and Grok also had promising results, particularly in their top matches of 3.**Evaluating HK Mark Six results** Typically, HK Mark Six results feature six ascending numbers plus a special number. I need to determine which is the special number from the provided "开獎號碼" list. I’ll assume the last number, 39, is the special one. The models have varying outcomes with some hitting certain numbers, and I'll set up a scoring system to assess their accuracy in terms of main hits and special hits. I'll rank at least the top models while considering color distributions and suggestions for future strategies. The focus will be on accurate and visually clear HTML presentation.**Ranking models and evaluating accuracy** I need to assess the best models based on their hitting numbers. Currently, I have nine models with at least two hits and need one more to reach ten. Some models have only one hit, including "OpenAI O1," which I might include as the tenth. For the worst-performing models, I'm focusing on those that scored zero and have systematic issues. I’ll provide suggestions for each model evaluated, along with an HTML structure emphasizing colorful elements and noting special number assumptions for clarity.**Computing model rankings** I’m preparing to assign numeric scores for different models based on their performance. I'll give 1 point for each main hit and 0.5 for special hits, like the number 39. I'll evaluate each model to determine the top 15 based on these points. For the worst 6, I'll choose those with zero or very low hits while identifying systematic issues. The overall ranking needs to include strengths, weaknesses, and suggestions for each evaluated model as well as formatted in HTML.**Crafting ranking evaluation** I need to prepare a ranking evaluation without showing model scripts, just the group's performance and matched numbers. The language should be Cantonese and professional yet colloquial. I'll include basic inline styles, as the user requested colored highlights for emphasis. The evaluation will focus on the top 10 models and the bottom 6. I’ll also describe each model’s hit counts and provide suggestions. The final output will be structured in pure HTML, covering various sections like results, rankings, and overall observations. 今晚六合彩|AI 預測賽後評核與總排名(專業數據比拼)

🎯 六合彩賽後專業評核|AI 模型命中率與改進建議

實際開獎:18, 37, 38, 34, 6, 29(正選6粒)+ 39(特別號)

說明:下文評核以「首6粒」計作正選;最後一粒 39 視作特別號(如個別模型有 39,標記為「特別號中」)。

評核口徑: 每中1正選 = 1 分 中1特別號 = 0.5 分 |取各模型「最佳一組」作比較;另就結構(單雙、色球、尾數、十位段)是否貼近統計提出改進建議。

⭐ 最佳10名模型(詳評)

1) Gpt 5(使用:200期原始)

命中:3/6 正選(18, 29, 38)

亮點:抓中實際的 3字頭群(38)+2字頭(29)+1字頭(18),覆蓋面好,尾數 8、9 配置貼近實況。

偏差:同組其餘位偏藍(47、31)略重。

建議:保留「3字頭集中 + 尾8/9」主軸,下調高段藍,增補 34 類 ±1 鄰近碼策略。

2) Claude 4.5 Sonnet(40期 + 2000期 + 3期檢討)

命中:3/6 正選(6, 34, 38)

亮點:準確踩中 3字頭雙偶(34, 38)+低段綠(6) 輪廓,屬本期核心。

偏差:整體綠球權重偏高,易錯失紅3格局。

建議:加入 紅≥2 的結構下限;保留 ±1 鄰近(35→34、37→38)模塊。

3) 獨家模型(共識融合)

命中:3/6 正選(29, 34, 6)

亮點:共識池有效捕捉 低紅簇+3字頭雙偶,策略上跟到「尾0回補對沖」但未過度依賴。

偏差:對沖組 藍球偏重,今期藍僅 1 粒(37),造成浪費。

建議:保持兩線(常態+藍重)但 降低藍≥4 的極端權重;提升 紅3 場景權重。

4) Claude 4.5 Sonnet(100期 + 2000期)

命中:2/6 正選(29, 38)

亮點:尾9+尾8 命中;結構不追 2x 過熱方向。

偏差:未能覆蓋 34, 37 的 3字頭核心群。

建議:將「3字頭雙偶(34, 38)」作成對配置;加入 ±1 鄰近(37⇄38)。

5) Claude 4.5 Sonnet(40期)

命中:2/6 正選(18, 37)

亮點:同時抓中 紅1粒+藍1粒,且為近端動量號。

偏差:缺 3字頭雙偶(34, 38)覆蓋。

建議:保留 18/37 動量模組,疊加 34/38 常規偶數對;尾8/9 設最少 1 粒。

6) Grok 4(200期原始)

命中:2/6 正選(18, 29)

亮點:低紅簇判斷正確;總和帶合理。

偏差:3字頭段(34, 37, 38)覆蓋不足。

建議:將 3x 段至少配 2 粒,優先 34, 38;加入 ±1 鄰近。

7) DeepSeek V3.2(40期)

命中:2/6 正選(18, 29)

亮點:低紅簇+尾9有覆蓋。

偏差:追熱 28/32 模塊本期無回報;3字頭覆蓋不夠。

建議:加強「3字頭雙偶」與「±1 鄰近」,2x 熱碼 降權

8) Claude 4.5 Sonnet(100期原始)

命中:2/6 正選(34, 37)

亮點:踩中 3字頭段核心;單雙結構貼近本期。

偏差:未覆蓋尾8(38)與低綠(6)。

建議:將 34 搭 38 作固定偶對;低段綠(6/16)保留 1 位。

9) GPT‑4.1(100期 + 2000期)

命中:1/6 正選(6)+特別號 39

亮點:6+39(如視作特號)半中格局;有兼顧低綠與尾9。

偏差:3字頭雙偶空缺;2x 模塊(32)過重。

建議:提升 34/38 權重;2x 熱碼(28/32/39)分散持倉,避免擁擠。

10) OpenAI O1(100期 + 2000期統計)

命中:1/6 正選(29)

亮點:尾9方向正確。

偏差:3x 段完全缺席;藍重或尾0回補策略未生效。

建議:加配 3x 雙偶(34, 38);尾0 以 10/20 二選一納入防守。

⚠️ 最差6名模型(問題與具體修正)

1) OpenAI O3(100期 + 2000期統計)

0/6 正選

主要問題:過度壓注 17/28/32/35/45 等熱團,對 3字頭雙偶 與低綠(6)缺乏覆蓋。

修正:加入「34, 38」固定偶對;尾8/9 至少各1;降低 28/32 同倉。

2) GPT‑4.1(50期 + 2000期統計 + 5期檢討)

最佳組 0–1/6

主要問題:「全雙+藍重」對沖比重過高,今期 藍僅1,致結構失衡。

修正:保留對沖但 降權藍≥4 場景;增加紅3常態配置。

3) GEMINI 3 PRO(50期 + 2000期 + 檢討)

1/6 正選

主要問題:尾0與藍補思路正確,但 3字頭群 覆蓋不足、鄰近碼弱。

修正:固定 34/38 其中1–2;引入 37±1 鄰近;尾0保留單位數即可。

4) Claude 4 Opus(40期 + 2000期 + 2期檢討)

1/6 正選

主要問題:尾0權重過高,與本期「3字頭雙偶 + 低綠」不相容。

修正:引入 3字頭至少2粒;尾0降至 1 粒保險位。

5) o1(40期 + 2000期 + 3期檢討)

1/6 正選

主要問題:低紅簇有,但 3字頭段與尾8弱。

修正:固定「34/38」其中一對;3x 區至少佔 2 位。

6) Deepseek v3.2(40期 + 2000期 + 8期檢討)

1/6 正選

主要問題:多組分散但主動量落在 28/32 過熱區,對 3x 雙偶捕捉不足。

修正:降低 2x 熱碼權重;升權 34/38、6 與 37±1 鄰近綫路。

📌 全體模型共通觀察與下期通用建議

🏆 總排名(Top 15)

  1. Gpt 5(200期原始)3 正選|結構貼市,尾8/9 準
  2. Claude 4.5 Sonnet(40期+2000期+3檢討)3 正選|±1 鄰近出色
  3. 獨家模型(共識)3 正選|共識池穩,但藍重稍高
  4. Claude 4.5 Sonnet(100期+2000期)2 正選
  5. Claude 4.5 Sonnet(40期)2 正選
  6. Grok 4(200期原始)2 正選
  7. DeepSeek V3.2(40期)2 正選
  8. Claude 4.5 Sonnet(100期原始)2 正選
  9. GPT‑4.1(100期+2000期)1 正選+ 特號
  10. OpenAI O11 正選
  11. O1 Pro1 正選
  12. Claude 4 Opus1 正選
  13. GEMINI 3 PRO1 正選
  14. gpt‑5(100期+2000期+5檢討)1 正選
  15. o4‑mini(50期+2000期+5檢討)1 正選
球色對照:=(1,2,7,8,12,13,18,19,23,24,29,30,34,35,40,45,46)|=(3,4,9,10,14,15,20,25,26,31,36,37,41,42,47,48)|=(5,6,11,16,17,21,22,27,28,32,33,38,39,43,44,49)

備註:以上評核以各模型「公開最終/主推組合」為準;若模型提供多組,取其「最佳一組」作比較。特別號以 39 計;如官方當期特號非 39,則「特號中」標記僅供參考。