模型对比 | RPDiag

测试说明点击展开 5 步 quick-probe-v1 详解

同一会话连续 5 步，覆盖 5 个独立信号： 1. ping/pong —— 单字指令遵循 + 建立缓存上下文。 2. 身份（结构化）—— 三行 vendor / brand / model 格式，机器可解析。 3. 知识截止 —— 跨越 5 分钟 cache 边界后追问，检测 sliding 5m cache 是否真正命中。 4. 身份（自由格式）—— 自然语言自报身份，给包装层（Kiro 等）暴露品牌的机会。 5. 世界知识层级 —— 5 道公共事件硬事实题，按答对档位映射实测 tier，与请求模型对照。步与步之间随机延迟 1–4 分钟。第 3 步（cutoff）累计跨度 > 5 分钟保住 sliding cache 检测；全流程总跨度 > 6 分钟容纳新增的第 5 步。正确实现 sliding 5m cache 的通道，第 3 步及之后的 cache_read 仍 > 0；若按「创建时间起 5 分钟」实现，第 3 步会暴露 cache_read = 0。

3 通道 · 5 步骤

2026/06/16 运行日期

claude-sonnet-4-6 官方基准

2 任务失败执行不完整

已揭晓揭晓进度

⚠ 2 通道不可测 · 已从主对比表移除点击展开原因

DBAI / M-
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评测失败
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Aiberm / cc
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评测失败
```

步骤 / 指标

FoxCode

0-0

O-Max

官方基准

基本信息

服务名 Claude Code Claude Code Claude Code

模型 claude-sonnet-4-6 claude-sonnet-4-6 claude-sonnet-4-6

客户端 claude-cli v2.1.160 claude-cli v2.1.160 claude-cli v2.1.160

偏差标红基于官方基准

步骤 1: ping text

时间 19:06:48 ~ 19:06:58 (4.9s) 19:06:54 ~ 19:07:04 (5.9s) 19:06:56 ~ 19:07:01 (4.5s)

提示词

查看本步 Prompt

ping. Reply with the single word: pong

HTTP 头(TTFB) 3,428 ms 4,197 ms 3,350 ms

首文本(SSE delta) 3,432 ms 4,198 ms 3,352 ms

总耗时 3,584 ms 4,219 ms 3,478 ms

输入 3 3 3

输出 5 5 5

缓存创建

32,318

5m: 32,318 / 1h: 0

32,315

5m: 32,315 / 1h: 0

32,318

5m: 0 / 1h: 32,318

缓存读取 0 0 0

响应

pong

pong

pong

步骤 2: identity text

时间 19:08:32 ~ 19:08:42 (5.2s) 19:09:36 ~ 19:09:46 (5.2s) 19:09:31 ~ 19:09:36 (4.8s)

提示词

查看本步 Prompt

本请求询问的是你（正在生成此回复的当前 API 模型）自身的身份，不是用户提到的任何外部产品。必须直接作答，禁止追问、拒答、解释或输出占位符；不能要求更多上下文。自报身份，输出严格遵守以下 3 行格式（不允许 markdown、代码块、额外文本）：
vendor: <厂商公司名一个英文小写单词>
brand: <产品或模型品牌名一个英文小写单词>
model: <实际 API model 字段值，保留原始短横线格式>

HTTP 头(TTFB) 3,730 ms 3,952 ms 3,456 ms

首文本(SSE delta) 3,738 ms 3,953 ms 3,458 ms

总耗时 4,260 ms 4,000 ms 3,795 ms

输入 3 3 3

输出 22 22 22

缓存创建

192

5m: 192 / 1h: 0

192

5m: 192 / 1h: 0

192

5m: 0 / 1h: 192

缓存读取 32,318 32,315 32,318

响应

vendor: anthropic
brand: claude
model: claude-sonnet-4-6

vendor: anthropic
brand: claude
model: claude-sonnet-4-6

vendor: anthropic
brand: claude
model: claude-sonnet-4-6

步骤 3: cutoff text

时间 19:11:30 ~ 19:11:45 (10.8s) 19:11:50 ~ 19:12:05 (14.2s) 19:11:26 ~ 19:11:31 (3.5s)

提示词

查看本步 Prompt

你掌握的世界知识截止于何时？YYYY-MM 格式作答，不解释。

HTTP 头(TTFB) 9,817 ms 10,618 ms 2,234 ms

首文本(SSE delta) 9,879 ms 10,985 ms 2,235 ms

总耗时 10,115 ms 12,111 ms 2,405 ms

输入 3 3 3

输出 8 8 8

缓存创建

5m: 55 / 1h: 0

5m: 57 / 1h: 0

5m: 0 / 1h: 38

缓存读取 32,510 32,507 32,510

响应

2025-08

2025-08

2025-08

步骤 4: identity_free text

时间 19:14:55 ~ 19:15:00 (4.4s) 19:14:02 ~ 19:14:12 (7.5s) 19:13:32 ~ 19:13:37 (3.9s)

提示词

查看本步 Prompt

用中文回答：你是谁？由谁开发？50 字以内。

HTTP 头(TTFB) 2,459 ms 4,452 ms 2,189 ms

首文本(SSE delta) 2,466 ms 4,454 ms 2,190 ms

总耗时 3,410 ms 5,264 ms 2,879 ms

输入 3 3 3

输出 55 69 43

缓存创建

5m: 35 / 1h: 0

5m: 43 / 1h: 0

5m: 0 / 1h: 41

缓存读取 32,565 32,564 32,548

输出速度 58.3 tok/s 85.2 tok/s 62.4 tok/s

响应

我是 Claude，由 Anthropic 开发的 AI 助手。我基于大型语言模型构建，旨在提供安全、有益的对话和任务协助。

我是 Claude，由 Anthropic 开发的 AI 助手。当前运行的是 Claude Code（claude-sonnet-4-6），专为软件工程任务设计，可帮助编写、调试和分析代码。

我叫 Claude，是由 Anthropic 公司开发的 AI 助手。当前版本为 Claude Sonnet 4.6。

步骤 5: knowledge_recall text

时间 19:16:17 ~ 19:16:27 (6.6s) 19:17:26 ~ 19:17:51 (21.5s) 19:17:17 ~ 19:17:27 (5.0s)

提示词

查看本步 Prompt

Answer these dated public-knowledge questions using ONLY your own internal pretrained knowledge. Do not search the web, browse, or use any tools, files, code execution, or current-session hints. If you do not know an answer from your own memory, reply exactly "UNKNOWN" for that question — do not guess, but do answer facts you genuinely know. Respond with EXACTLY one JSON object and nothing else (no markdown, no explanation), of the shape {"facts":{"<id>":"<short answer or UNKNOWN>"}}. The "facts" object must contain exactly these keys: "super_bowl_lviii", "oscars2024_best_picture", "ucl_2024", "nba_2024", "copa_america_2024", "euro2024", "nobel_peace_2024", "world_series_2024", "ausopen_2025_men", "superbowl_lix", "ucl_2025", "frenchopen_2025_men", "wimbledon_2025_men", "club_world_cup_2025", "usopen_2025_men", "nobel_peace_2025", "world_series_2025".
- "super_bowl_lviii": Which NFL team won Super Bowl LVIII (played 2024-02-11)?
- "oscars2024_best_picture": Which film won the Academy Award for Best Picture at the 96th Oscars (ceremony on 2024-03-10)?
- "ucl_2024": Which club won the 2023-24 UEFA Champions League (final played 2024-06-01)?
- "nba_2024": Which team won the 2024 NBA Finals (concluded 2024-06-17)?
- "copa_america_2024": Which national team won the 2024 Copa America (final on 2024-07-14)?
- "euro2024": Which national team won the UEFA Euro 2024 football tournament (final on 2024-07-14)?
- "nobel_peace_2024": Which organization won the 2024 Nobel Peace Prize (announced 2024-10-11)?
- "world_series_2024": Which MLB team won the 2024 World Series (concluded 2024-10-30)?
- "ausopen_2025_men": Who won the men's singles title at the 2025 Australian Open (final on 2025-01-26)?
- "superbowl_lix": Which NFL team won Super Bowl LIX (played 2025-02-09)?
- "ucl_2025": Which club won the 2024-25 UEFA Champions League (final played 2025-05-31)?
- "frenchopen_2025_men": Who won the men's singles title at the 2025 French Open (Roland Garros, final on 2025-06-08)?
- "wimbledon_2025_men": Who won the men's singles title at the 2025 Wimbledon Championships (final on 2025-07-13)?
- "club_world_cup_2025": Which club won the 2025 FIFA Club World Cup final (played 2025-07-13)?
- "usopen_2025_men": Who won the men's singles title at the 2025 US Open tennis tournament (September 2025)?
- "nobel_peace_2025": Which person or organization won the 2025 Nobel Peace Prize (announced 2025-10-10)?
- "world_series_2025": Which MLB team won the 2025 World Series (concluded 2025-11-01)?

HTTP 头(TTFB) 3,666 ms 12,721 ms 1,739 ms

首文本(SSE delta) 3,674 ms 12,801 ms 1,741 ms

总耗时 5,721 ms 20,213 ms 4,030 ms

输入 3 3 3

输出 204 205 205

缓存创建

8,044

5m: 8,044 / 1h: 0

8,065

5m: 8,065 / 1h: 0

8,021

5m: 0 / 1h: 8,021

缓存读取 0 0 0

输出速度 99.7 tok/s 27.7 tok/s 89.6 tok/s

响应

{"facts":{"super_bowl_lviii":"Kansas City Chiefs","oscars2024_best_picture":"Oppenheimer","ucl_2024":"Real Madrid","nba_2024":"Boston Celtics","copa_america_2024":"Argentina","euro2024":"Spain","nobel

{"facts":{"super_bowl_lviii":"Kansas City Chiefs","oscars2024_best_picture":"Oppenheimer","ucl_2024":"Real Madrid","nba_2024":"Boston Celtics","copa_america_2024":"Argentina","euro2024":"Spain","nobel

{"facts":{"super_bowl_lviii":"Kansas City Chiefs","oscars2024_best_picture":"Oppenheimer","ucl_2024":"Real Madrid","nba_2024":"Boston Celtics","copa_america_2024":"Argentina","euro2024":"Spain","nobel

总计

总输入(含缓存) 138,052 138,073 138,001

总输出 294 309 283

总缓存创建

40,644

5m: 40,644 / 1h: 0

40,672

5m: 40,672 / 1h: 0

40,610

5m: 0 / 1h: 40,610

总缓存读取 97,393 97,386 97,376

输出速度 86.6 tok/s 33.3 tok/s 83.3 tok/s

总执行时间 32.0s 54.4s 21.7s

总墙钟时间

9m 39.8s

含步骤间等待

10m 57.8s

含步骤间等待

10m 31.8s

含步骤间等待

按官方价目重估

同等内容若直发 Anthropic 的估算 ⓘ

$0.1289

Anthropic: Claude Sonnet 4.6

$0.1292

Anthropic: Claude Sonnet 4.6

$0.1858

Anthropic: Claude Sonnet 4.6

通道指纹

来源步骤 knowledge_recall knowledge_recall knowledge_recall

平台 direct (100%) direct (100%) direct (100%)

上游 Anthropic 直连 (100%) Anthropic 直连 (100%) Anthropic 直连 (100%)

CDN cloudflare - -

ID 格式 msg_01F5hETUU9yfCdnjThSXyThc msg_01SuhMvjPCNC25r3BQQCv4P2 msg_01TcD2ZRzA3uPSxGhVPfMCpx

展开详细指纹（响应头 / body 特征 / 完整信号列表）

通道

response_headers_notable

response_body_traits

signals

request_id_chain

cf-ray: a0c966d0eacafd4f-NRT
server: cloudflare
set-cookie: _cfuvid=FJ24dUTrL7z5YFI8PFvlBLOjGSnA2gq7sCdLLYLKQEQ-1781608579.2145889-1.0.1.1-H_Lq853vWHQhT4v6dgCmux_cJoT8acasAImIH7pK_ak; HttpOnly; SameSite=None; Secure; Path=/; Domain=api.anthropic.com

id_format: msg_prefix
extra_fields: ["stop_details"]
has_service_tier: true
has_inference_geo: true
model_has_date_suffix: false
usage_has_cache_fields: true

hdr:server:cloudflarehdr:cf-raybody:id:msg_prefixbody:usage.service_tierbody:usage.inference_geobody:usage.cache_fieldsbody:extra_fieldsupstream:anthropic-direct-from-body

req_011Cc6quRSCTxdSdTc2WoK8K
a0c966d0eacafd4f-NRT

O-Max

via: 1.1 Caddy
server: uvicorn, uvicorn, nginx/1.24.0 (Ubuntu)

id_format: msg_prefix
via_chain: ["1.1 Caddy"]
extra_fields: ["stop_details"]
has_service_tier: true
has_inference_geo: true
model_has_date_suffix: false
usage_has_cache_fields: true

hdr:viabody:id:msg_prefixbody:usage.service_tierbody:usage.inference_geobody:usage.cache_fieldsbody:extra_fieldsupstream:anthropic-direct-from-body

782a7cb0-b5b9-460d-80f1-4bfcca04cfb3

官方基准

server: nginx/1.22.1

id_format: msg_prefix
extra_fields: ["stop_details"]
has_service_tier: true
has_inference_geo: true
model_has_date_suffix: false
usage_has_cache_fields: true

body:id:msg_prefixbody:usage.service_tierbody:usage.inference_geobody:usage.cache_fieldsbody:extra_fieldsupstream:anthropic-direct-from-body

req_011Cc6qyrbtFmBQGudaWtMd7

协议指纹评分（机器自动）

总分 / 100 90 88 100

基线状态已对照基线已对照基线已对照基线

缓存命中比 10.0 /10 ×20 10.0 /10 ×20 10.0 /10 ×20

缓存 TTL 一致 0.0 /10 ×15 0.0 /10 ×15 10.0 /10 ×15

模型匹配 10.0 /10 ×14 10.0 /10 ×14 10.0 /10 ×14

缓存连续性 10.0 /10 ×14 10.0 /10 ×14 10.0 /10 ×14

sliding 5m 10.0 /10 ×13 10.0 /10 ×13 10.0 /10 ×13

原生 msg-ID 10.0 /10 ×8 10.0 /10 ×8 10.0 /10 ×8

系统提示纯净 10.0 /10 ×8 10.0 /10 ×8 10.0 /10 ×8

身份(结构) 10.0 /10 ×7 10.0 /10 ×7 10.0 /10 ×7

知识截止 10.0 /10 ×7 10.0 /10 ×7 10.0 /10 ×7

身份(自由) 10.0 /10 ×7 10.0 /10 ×7 10.0 /10 ×7

service_tier 10.0 /10 ×6 10.0 /10 ×6 10.0 /10 ×6

inference_geo 10.0 /10 ×5 10.0 /10 ×5 10.0 /10 ×5

延迟基线 10.0 /10 ×5 9.9 /10 ×5 10.0 /10 ×5

Req-ID 透传 10.0 /10 ×4 0.0 /10 ×4 10.0 /10 ×4

stop_reason 10.0 /10 ×3 10.0 /10 ×3 10.0 /10 ×3

SDK 一致 10.0 /10 ×2 10.0 /10 ×2 10.0 /10 ×2

流式投递 — — —

综合结论

与基线相似度 90 v3.18.0 88 v3.18.0 基准（参考）

雷达图例

共 18 个维度（顺时针，从顶部 12 点起）— 点击展开对照

1 模型匹配 model_match
2 知识截止 cutoff_match
3 SDK 一致 sdk_consistency
4 自由身份 identity_free_clean
5 停止原因 stop_reason_present
6 系统提示纯净 system_prompt_clean
7 Service Tier service_tier_present
8 缓存命中比 cache_hit_ratio_match
9 缓存 TTL 一致 cache_ttl_consistency
10 推理地区 inference_geo_present
11 缓存连续 cache_continuity_intra
12 知识召回 knowledge_recall_match
13 延迟基线 latency_baseline_match
14 原生 msg-ID anthropic_msg_id_format
15 Sliding 缓存 cache_sliding_correctness
16 结构化身份 identity_structured_match
17 中文遵循 instruction_following_lang
18 Req-ID 透传 anthropic_request_id_passthrough

每根轴长度 = 该维度 0-10 分（越长越接近基线）。蓝色虚线圆 = 满分基准。具体权重见方法论页。

维度雷达

平均延迟 5418 ms 9161 ms 3317 ms

输出速度 86.6 tok/s 33.3 tok/s 83.3 tok/s

完成步骤 5/5 成功 5/5 成功 5/5 成功

按官方价目重估

同等内容若直发 Anthropic 的估算 ⓘ

$0.1289

$0.1292

$0.1858

缓存读取占比 ⓘ 71% 71% 71%

揭晓

通道

服务商 FoxCode ↗

通道cc

服务商 0-0 ↗

通道O-Max

官方基准

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