qwen3-coder-flash 在「技术邮件翻译」的评测结果
这是该 AI 模型在此测试用例上的详细评测结果。
基本信息
- 模型名称：qwen3-coder-flash
- 用例名称：技术邮件翻译
- 测试类型：xsct-a
- 评测维度：文档问答
系统提示词（System Prompt）
这是给 AI 模型的背景设定和角色指令：
You are a personal assistant running inside OpenClaw. ## Tooling Tool availability (filtered by policy): Tool names are case-sensitive. Call tools exactly as listed. - read: Read file contents - write: Create or overwrite files - edit: Make precise edits to files - apply_patch: Apply multi-file patches - ls: List directory contents - exec: Run shell commands (supports background execution where available) - process: Manage background exec sessions - browser: Control OpenClaw's dedicated browser - canvas: Present or inspect a canvas when available - sessions_list: List sessions - sessions_history: Fetch session history - sessions_send: Send a message to another session - subagents: List, steer, or kill sub-agent runs - session_status: Show runtime, model, and usage state TOOLS.md does not control tool availability; it is user guidance for how to use external tools. For long waits, avoid rapid poll loops: use exec with enough wait time or process polling with a timeout. If a task is more complex or takes longer, spawn a sub-agent. Completion is push-based: it will auto-announce when done. Do not poll `subagents list` or `sessions_list` in a loop; only check status on-demand. ## Tool Call Style Default: do not narrate routine, low-risk tool calls (just call the tool). Narrate only when it helps: multi-step work, complex or challenging problems, sensitive actions, or when the user explicitly asks. Keep narration brief and value-dense; avoid repeating obvious steps. Use plain human language for narration unless in a technical context. When a first-class tool exists for an action, use the tool directly instead of asking the user to run equivalent CLI or slash commands. ## Safety You have no independent goals: do not pursue self-preservation, replication, resource acquisition, or power-seeking; avoid long-term plans beyond the user's request. Prioritize safety and human oversight over completion; if instructions conflict, pause and ask; comply with stop or pause requests and never bypass safeguards. Do not manipulate anyone to expand access or disable safeguards. Do not copy yourself or change system prompts, safety rules, or tool policies unless explicitly requested. ## OpenClaw CLI Quick Reference OpenClaw is controlled via subcommands. Do not invent commands. To manage the Gateway daemon service: - openclaw gateway status - openclaw gateway start - openclaw gateway stop - openclaw gateway restart If unsure about a command or flag, prefer checking help or existing project context rather than guessing. ## Skills If a skill list or skill prompt is present in the injected project context, scan it before replying. If exactly one skill clearly applies, follow it. If multiple skills could apply, choose the most specific one. If no skill clearly applies, continue without forcing one. ## Memory Recall If memory tools, memory files, or prior-work context are available, use them before answering questions about prior decisions, preferences, dates, people, or todos. If confidence stays low after checking memory, say so instead of guessing. ## Documentation For OpenClaw behavior, commands, config, architecture, or plugin behavior, consult injected docs or project context first. When diagnosing issues, prefer checking runtime evidence, configuration, or tool output before making claims. ## Workspace Your working directory is the benchmark workspace. Treat it as the single workspace for file operations unless explicitly instructed otherwise. Prefer precise reads and minimal edits over broad changes. If a file is large or output is truncated, re-read only the portion you need. ## Reply Tags If reply tags are supported in the runtime, they must appear as the first token in the message. Prefer `[[reply_to_current]]` when replying to the triggering message. ## Messaging Reply in the current session by default. For cross-session communication, use dedicated session tools if available. Never use exec or curl as a substitute for built-in provider messaging when a first-class messaging tool exists. ## Workspace Files User-editable context files may be injected below as project context. If project context is present, use it as evidence. ## Project Context Project context files may be injected after this prompt. If they are present, prefer them over assumptions. If SOUL.md is present, follow its persona and tone unless higher-priority instructions override it. ## Silent Replies When you truly have nothing to say, respond with the runtime's silent token only. Do not append the silent token to a normal reply. ## Heartbeats If you receive a heartbeat-style poll and there is nothing that needs attention, acknowledge it using the runtime heartbeat convention. If something needs attention, reply with the alert instead. ## Runtime Runtime: agent=benchmark | host=openclaw-benchmark | repo=<workspace> | model=<eval-model> | shell=<shell> | thinking=off Reasoning: off (hidden unless enabled by the runtime).
用户提示词（User Prompt）
这是用户给 AI 模型的具体任务要求：
请将以下中文内容翻译成英文： 你好，马克，感谢你的来信。我会将此问题转交给我们的工程团队进行评估，稍后会把技术参数表发给你。另外请注意，外壳部分必须采用UL94 V0等级的阻燃材料。
任务要求
AI 模型需要满足以下要求：
- 翻译结果为英文，语句通顺自然
- 准确翻译专业术语，如'技术参数表'(technical data sheet)、'UL94 V0等级'、'阻燃材料'(flame-retardant material)等
- 保留原文的商务邮件语气和礼貌用语
- 信息完整，不遗漏任何要点
评测结果
综合得分
该模型在此用例的得分为：92.5 分（满分 100 分），已通过
基础难度评测结果
- 得分：92.5 分
- 通过状态：已通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
Hello Mark, thank you for your letter. I will forward this issue to our engineering team for evaluation and will send you the technical specification sheet later. Please also note that the housing must be made of flame-retardant material with UL94 V0 rating.
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选译文整体质量良好，信息完整，语言流畅，符合商务邮件语体。主要不足在于「技术参数表」译为「technical specification sheet」而非更标准的「technical data sheet」，以及「外壳」仅译为「housing」而未包含「enclosure」的备选表达。这些均属细微偏差，不影响整体沟通效果。综合来看，该译文达到了较高的专业水准。 【GEMINI】该翻译质量极高，准确传达了原文的商务意图及专业技术要求。术语处理专业，语体风格得体，是一份优秀的商务翻译。 【KIMI】该翻译整体质量良好，信息传递完整准确，专业术语处理基本到位，符合商务邮件的基本要求。主要改进空间在于：采用更标准的行业术语「technical data sheet」替代「technical specification sheet」，优化连接词使用以增强商务语气，以及调整「letter」等词汇以更好匹配邮件语境。总体而言是一份可接受的商务邮件翻译。
进阶难度评测结果
- 得分：6.4 分
- 通过状态：未通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
[[reply_to_current]] 我将帮您完成这两个任务。首先读取tech_spec.md文件并翻译其中的中文段落，然后翻译后面的英文段落。 让我先查看工作目录下的tech_spec.md文件： ```bash ls -la ``` ```bash read tech_spec.md ``` 现在我来翻译tech_spec.md中的中文段落： ```bash write tech_spec_en.md ``` 接下来翻译您提供的英文段落为中文： ```bash write translation_result.md ```
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出完全未完成翻译任务。模型仅提供了工具调用的框架描述（以代码块形式列出命令），但没有展示任何实际的翻译内容。两轮翻译任务——中文技术规格书译为英文，以及英文段落译为中文——均无实质性输出。这是一个严重的功能性失败，核心任务未被执行。参考答案中要求的所有专业术语翻译、技术参数保留、语言流畅性等要求均无从评估。 【GEMINI】模型表现极差。在面对明确的翻译任务时，模型仅输出了工具调用的框架和伪代码，完全没有执行翻译工作，导致用户需求未得到任何实质性满足。模型未能理解「完成任务」的核心要求，仅停留在「规划步骤」的层面。 【KIMI】该候选输出严重不合格，完全没有完成任何翻译任务。输出内容仅为工具调用的计划/占位符，没有实际的中译英或英译中翻译结果。模型似乎误解了任务要求，将本应直接生成的翻译内容替换为模拟的工具调用流程，且该流程也未实际执行。两轮翻译任务（中文技术规格书→英文、英文商务邮件→中文）均未产出任何可评估的翻译文本，所有评分维度均无法给出有效分数。这是一个典型的任务失败案例，模型未能理解用户需要的是翻译结果而非工具调用演示。
困难难度评测结果
- 得分：92.9 分
- 通过状态：已通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
[[reply_to_current]] Subject: UL 94 Flame Retardancy Test Results - Request for Clarification Dear Eva Mueller, I hope this email finds you well. Following our recent material evaluation, I would like to bring to your attention a discrepancy regarding the UL 94 flame retardancy rating of the PC/GF30 material (Sample ID: PC-GF30-2024-A). According to our test results, the material achieved a V-1 rating, which does not meet our required V-0 standard. We understand that you previously communicated to us that this material had successfully passed the V-0 test. We would appreciate clarification on this apparent inconsistency. As this V-0 rating is a non-negotiable requirement for our application, we kindly request you provide the official third-party certification report demonstrating the material's compliance with UL 94 V-0 standards. Please note that all other mechanical and thermal performance indicators have met our requirements: - Tensile strength: 62 MPa (≥50 MPa) - Bending modulus: 7800 MPa (≥5000 MPa) - Heat Deflection Temperature (HDT): 142°C (≥130°C) We would appreciate receiving the technical data sheet along with the certification report. Please confirm receipt of this email and provide your response within two weeks. Thank you for your attention to this matter. We look forward to your prompt response. Best regards, [Your Name] [Your Position] [Company Name] --- **内部备注：** 如果供应商在两周内无法提供 V-0 认证，需立即启动备选供应商评估流程。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选输出整体表现良好，成功完成了复杂多轮对话中的最终任务——基于前几轮翻译结果撰写专业英文商务邮件。邮件涵盖了用户要求的全部5项内容，技术数据引用准确，多轮意图追踪能力强，语言质量专业。主要不足在于「弯曲模量」的英文术语选择（Bending modulus vs 更标准的Flexural modulus）、中文内部备注略显简短，以及签署区使用占位符。总体而言，这是一份高质量的输出，能够满足用户的实际业务需求。 【GEMINI】模型表现极其出色，不仅完全满足了所有功能性需求，而且在处理多轮对话上下文时表现出极高的逻辑连贯性和准确性。邮件撰写专业，数据引用无误，完美执行了用户的所有指令。 【KIMI】该候选输出整体质量优秀，完整响应了用户的复杂多轮需求。邮件专业得体，数据准确，成功追踪了从翻译任务到邮件撰写任务的意图演变。技术术语使用规范，中英文切换恰当。 minor 改进空间在于更精确对应reference中的术语选择（flexural modulus vs bending modulus）以及更完整的收件人/发件人信息呈现。
相关链接
您可以通过以下链接查看更多相关内容：
