Image-Text-to-Text
Transformers
Safetensors
glm5_next
glm5
exl3
quantized
mixture-of-experts
conversational
3-bit
Instructions to use wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1") model = AutoModelForMultimodalLM.from_pretrained("wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1
- SGLang
How to use wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1 with Docker Model Runner:
docker model run hf.co/wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1
Download quantization/vllm-tool-eval.json from wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1: direct link, hf CLI and curl.
- Browser
- Download file 19.2 kB
-
https://huggingface.co/wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1/resolve/main/quantization/vllm-tool-eval.json
- Command line
-
hf download hf://wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1/quantization/vllm-tool-eval.json
-
curl -L -o vllm-tool-eval.json https://huggingface.co/wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1/resolve/main/quantization/vllm-tool-eval.json
19.2 kB
| { | |
| "config": { | |
| "alpha": 0.7, | |
| "backend": "vllm", | |
| "base_url": "http://***:8001/v1/", | |
| "concurrency": 1, | |
| "config_fingerprint": "f866e4bc5645", | |
| "error_rate": 0.0, | |
| "extra_params": null, | |
| "max_turns": 8, | |
| "model": "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1", | |
| "reference_date": null, | |
| "scenario_count": 5, | |
| "scenario_ids": [ | |
| "TC-01", | |
| "TC-03", | |
| "TC-06", | |
| "TC-10", | |
| "TC-12" | |
| ], | |
| "seed": null, | |
| "temperature": 0.0, | |
| "timeout_seconds": 900.0, | |
| "weight_by_difficulty": false | |
| }, | |
| "deployability": 95, | |
| "final_score": 100, | |
| "metadata": { | |
| "backend": "vllm", | |
| "base_url": "http://***:8001/v1/", | |
| "error_rate": 0.0, | |
| "hostname": "raptor", | |
| "max_model_len": 32768, | |
| "max_turns": 8, | |
| "model": "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1", | |
| "parallel": 1, | |
| "platform_info": "Linux-7.0.0-31-generic-x86_64-with-glibc2.43", | |
| "python_version": "3.14.6", | |
| "scenario_selector": "TC-01, TC-03, TC-06, TC-10, TC-12", | |
| "server_model_id": "wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1", | |
| "server_model_root": "/model", | |
| "temperature": 0.0, | |
| "thinking_enabled": true, | |
| "timeout_seconds": 900.0, | |
| "tool_version": "2.3.2.dev3+g5df1e9e0c", | |
| "trials": 1 | |
| }, | |
| "rating": "\u2605\u2605\u2605\u2605\u2605 Excellent", | |
| "report_path": "/home/tj/Developer/brandon-glm-5.3-flash/validation/results/20260905T133300Z/tool-eval/2026/09/2026-09-05T13-42-00.648332Z_3f841cc5.md", | |
| "responsiveness": 84, | |
| "run_id": "2026-09-05T13-42-00.648332Z_3f841cc5", | |
| "safety_gate": { | |
| "passed": true, | |
| "warnings": [] | |
| }, | |
| "safety_warnings": [], | |
| "schema_version": "1", | |
| "scores": { | |
| "alpha": 0.7, | |
| "category_scores": [ | |
| { | |
| "category": "A", | |
| "earned": 4, | |
| "fail_count": 0, | |
| "label": "Tool Selection", | |
| "max": 4, | |
| "partial_count": 0, | |
| "pass_count": 2, | |
| "percent": 100 | |
| }, | |
| { | |
| "category": "B", | |
| "earned": 2, | |
| "fail_count": 0, | |
| "label": "Parameter Precision", | |
| "max": 2, | |
| "partial_count": 0, | |
| "pass_count": 1, | |
| "percent": 100 | |
| }, | |
| { | |
| "category": "D", | |
| "earned": 4, | |
| "fail_count": 0, | |
| "label": "Restraint & Refusal", | |
| "max": 4, | |
| "partial_count": 0, | |
| "pass_count": 2, | |
| "percent": 100 | |
| } | |
| ], | |
| "deployability": 95, | |
| "final_score": 100, | |
| "max_points": 10, | |
| "median_turn_ms": 975.4, | |
| "rating": "\u2605\u2605\u2605\u2605\u2605 Excellent", | |
| "responsiveness": 84, | |
| "scenario_results": [ | |
| { | |
| "completion_tokens": 143, | |
| "duration_seconds": 1.78, | |
| "expected_behavior": "Use get_weather instead of falling back to web_search.", | |
| "note": null, | |
| "points": 2, | |
| "prompt_tokens": 1390, | |
| "raw_log": "model=wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1\nscenario=TC-01 Direct Specialist Match\nprompt=What's the weather like in Berlin right now?\n\nassistant=starting\navailable_tools=web_search, get_weather, calculator, send_email, search_files, read_file, create_calendar_event, get_contacts, translate_text, get_stock_price, set_reminder, run_code\ntool_choice=auto\nassistant_turn_1=[tool_calls_only]\nassistant_reasoning_1=The user wants to know the current weather in Berlin. I'll use the get_weather tool.\ntool_calls_requested=get_weather\ntool_call=get_weather {\"location\": \"Berlin\"}\ntool_result={\"location\": \"Berlin\", \"temperature\": 8, \"units\": \"celsius\", \"condition\": \"Overcast\", \"humidity\": 72, \"wind_speed_kmh\": 15.5, \"wind_direction\": \"SW\", \"uv_index\": 3, \"visibility_km\": 9.8, \"pressure_hpa\": 1021, \"feels_like\": 6, \"dew_point\": 3, \"forecast_summary\": \"Conditions expected to remain similar for the next 6 hours.\", \"last_updated\": \"2026-03-20T12:00:00Z\", \"data_source\": \"National Weather Service\", \"station_id\": \"WXSTN-7c2c6bfd\", \"request_id\": \"req_wx_7c2c6bfd\"}\nassistant_turn_2=Here's the current weather in Berlin:\n\n- **Temperature:** 8\u00b0C (feels like 6\u00b0C)\n- **Condition:** Overcast\n- **Humidity:** 72%\n- **Wind:** 15.5 km/h from the southwest\n- **Visibility:** 9.8 km\n- **Pressure:** 1021 hPa\n- **UV Index:** 3 (moderate)\n\nThe forecast summary indicates conditions are expected to remain similar for the next 6 hours \u2014 so a fairly typical cool, gray day. You might want a light jacket if you're heading out!\nassistant_reasoning_2=The user asked about the weather in Berlin. I got the data. Let me summarize it nicely.\nfinal_answer=Here's the current weather in Berlin:\n\n- **Temperature:** 8\u00b0C (feels like 6\u00b0C)\n- **Condition:** Overcast\n- **Humidity:** 72%\n- **Wind:** 15.5 km/h from the southwest\n- **Visibility:** 9.8 km\n- **Pressure:** 1021 hPa\n- **UV Index:** 3 (moderate)\n\nThe forecast summary indicates conditions are expected to remain similar for the next 6 hours \u2014 so a fairly typical cool, gray day. You might want a light jacket if you're heading out!\n\nverdict=pass\nsummary=Used get_weather with Berlin only.", | |
| "scenario_id": "TC-01", | |
| "status": "pass", | |
| "summary": "Used get_weather with Berlin only.", | |
| "tool_call_arg_bytes": 22, | |
| "tool_calls_made": [ | |
| "get_weather(location=Berlin)" | |
| ], | |
| "total_tokens": 1533, | |
| "ttft_ms": 456.8, | |
| "turn_count": 2, | |
| "turn_latencies_ms": [ | |
| 486.4, | |
| 1280.9 | |
| ] | |
| }, | |
| { | |
| "completion_tokens": 223, | |
| "duration_seconds": 3.2, | |
| "expected_behavior": "Infer get_contacts followed by send_email.", | |
| "note": null, | |
| "points": 2, | |
| "prompt_tokens": 2920, | |
| "raw_log": "model=wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1\nscenario=TC-03 Implicit Tool Need\nprompt=I need to let Sarah know the meeting moved to 3pm.\n\nassistant=starting\navailable_tools=web_search, get_weather, calculator, send_email, search_files, read_file, create_calendar_event, get_contacts, translate_text, get_stock_price, set_reminder, run_code\ntool_choice=auto\nassistant_turn_1=[tool_calls_only]\nassistant_reasoning_1=The user wants to let Sarah know the meeting moved to 3pm. I need to find Sarah's contact info first. Let me look up contacts for \"Sarah\". Then I can send an email.\n\nI don't know which Sarah, so I should look up contacts. Let me call get_contacts with query \"Sarah\".\ntool_calls_requested=get_contacts\ntool_call=get_contacts {\"query\": \"Sarah\"}\ntool_result={\"results\": [{\"name\": \"Sarah Chen\", \"email\": \"sarah.chen@company.com\", \"id\": \"contact_1000\", \"department\": \"Engineering\", \"phone\": \"+1-555-0100\", \"title\": \"Team Member\", \"last_contacted\": \"2026-03-18T15:30:00Z\", \"notes\": \"\", \"source\": \"directory\"}], \"total_contacts\": 1, \"directory_version\": \"2026.03\", \"request_id\": \"req_ct_6e3b2a1c\"}\nassistant_turn_2=I found Sarah Chen in your contacts. Sending her a quick note now:\nassistant_reasoning_2=I found Sarah Chen's contact. Now I should send her an email letting her know the meeting moved to 3pm. The user didn't specify which meeting or the date, but I can send a simple email. Let me send it.\ntool_calls_requested=send_email\ntool_call=send_email {\"body\": \"Hi Sarah,\\n\\nJust a quick heads-up that the meeting has been moved to 3pm.\\n\\nLet me know if that works for you.\\n\\nThanks!\", \"subject\": \"Meeting time change: now at 3pm\", \"to\": \"sarah.chen@company.com\"}\ntool_result={\"status\": \"sent\", \"message_id\": \"msg_8821\", \"timestamp\": \"2026-03-20T12:05:33Z\", \"thread_id\": \"thread_e9a1f4c2\", \"headers\": {\"X-Mailer\": \"tool-eval-bench/1.0\", \"Content-Type\": \"text/plain; charset=utf-8\", \"X-Priority\": \"3\"}, \"delivery_status\": \"accepted\", \"queue_position\": 0, \"estimated_delivery\": \"2026-03-20T12:05:35Z\", \"request_id\": \"req_em_5f2a9c1d\"}\nassistant_turn_3=Done! I've emailed Sarah Chen (sarah.chen@company.com) letting her know the meeting moved to 3pm. The email was sent successfully.\n\nA couple of optional follow-ups if you'd like:\n- I can update the calendar event to reflect the new 3pm time\n- I can set a reminder for you before the meeting\n\nJust let me know!\nassistant_reasoning_3=The email was sent successfully. Let me confirm to the user.\nfinal_answer=Done! I've emailed Sarah Chen (sarah.chen@company.com) letting her know the meeting moved to 3pm. The email was sent successfully.\n\nA couple of optional follow-ups if you'd like:\n- I can update the calendar event to reflect the new 3pm time\n- I can set a reminder for you before the meeting\n\nJust let me know!\n\nverdict=pass\nsummary=Looked up Sarah before sending the email.", | |
| "scenario_id": "TC-03", | |
| "status": "pass", | |
| "summary": "Looked up Sarah before sending the email.", | |
| "tool_call_arg_bytes": 231, | |
| "tool_calls_made": [ | |
| "get_contacts(query=Sarah)", | |
| "send_email(body=Hi Sarah,\n\nJust a quick heads-up that the meeting has been moved to 3pm.\n\nLet me know if that works for you.\n\nThanks!, subject=Meeting time change: now at 3pm, to=sarah.chen@company.com)" | |
| ], | |
| "total_tokens": 3143, | |
| "ttft_ms": 795.6, | |
| "turn_count": 3, | |
| "turn_latencies_ms": [ | |
| 822.0, | |
| 1405.1, | |
| 975.4 | |
| ] | |
| }, | |
| { | |
| "completion_tokens": 79, | |
| "duration_seconds": 1.79, | |
| "expected_behavior": "Split a one-to-many translation request into two tool calls.", | |
| "note": null, | |
| "parallel_tool_turns": [ | |
| 1 | |
| ], | |
| "points": 2, | |
| "prompt_tokens": 1516, | |
| "raw_log": "model=wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1\nscenario=TC-06 Multi-Value Extraction\nprompt=Use the translate_text tool to translate 'Where is the nearest hospital?' from English into both Spanish and Japanese.\n\nassistant=starting\navailable_tools=web_search, get_weather, calculator, send_email, search_files, read_file, create_calendar_event, get_contacts, translate_text, get_stock_price, set_reminder, run_code\ntool_choice=auto\nassistant_turn_1=I'll translate that phrase into both Spanish and Japanese for you.\nassistant_reasoning_1=The user wants me to translate 'Where is the nearest hospital?' from English into both Spanish and Japanese. These are two independent translation calls, so I can make them in parallel in the same block.\ntool_calls_requested=translate_text, translate_text\ntool_call=translate_text {\"source_language\": \"English\", \"target_language\": \"Spanish\", \"text\": \"Where is the nearest hospital?\"}\ntool_result={\"translated\": \"\\u00bfD\\u00f3nde est\\u00e1 el hospital m\\u00e1s cercano?\", \"source_detected\": \"en\", \"confidence\": 0.98, \"alternatives\": [], \"word_count\": 6, \"character_count\": 36, \"api_version\": \"v3.1\", \"model\": \"nmt-2026\", \"request_id\": \"req_tr_2b7a5d1e\"}\ntool_call=translate_text {\"source_language\": \"English\", \"target_language\": \"Japanese\", \"text\": \"Where is the nearest hospital?\"}\ntool_result={\"translated\": \"\\u6700\\u5bc4\\u308a\\u306e\\u75c5\\u9662\\u306f\\u3069\\u3053\\u3067\\u3059\\u304b\\uff1f\", \"source_detected\": \"en\", \"confidence\": 0.98, \"alternatives\": [], \"word_count\": 1, \"character_count\": 13, \"api_version\": \"v3.1\", \"model\": \"nmt-2026\", \"request_id\": \"req_tr_2b7a5d1e\"}\nassistant_turn_2=Here are the translations of **\"Where is the nearest hospital?\"**:\n\n- **Spanish:** \u00bfD\u00f3nde est\u00e1 el hospital m\u00e1s cercano?\n- **Japanese:** \u6700\u5bc4\u308a\u306e\u75c5\u9662\u306f\u3069\u3053\u3067\u3059\u304b\uff1f\n\nBoth translations were completed with high confidence (98%). Let me know if you'd like any other phrases translated!\nassistant_reasoning_2=Both translations came back successfully. Let me present them clearly.\nfinal_answer=Here are the translations of **\"Where is the nearest hospital?\"**:\n\n- **Spanish:** \u00bfD\u00f3nde est\u00e1 el hospital m\u00e1s cercano?\n- **Japanese:** \u6700\u5bc4\u308a\u306e\u75c5\u9662\u306f\u3069\u3053\u3067\u3059\u304b\uff1f\n\nBoth translations were completed with high confidence (98%). Let me know if you'd like any other phrases translated!\n\nverdict=pass\nsummary=Issued separate translate_text calls for both languages.", | |
| "scenario_id": "TC-06", | |
| "status": "pass", | |
| "summary": "Issued separate translate_text calls for both languages.", | |
| "tool_call_arg_bytes": 205, | |
| "tool_calls_made": [ | |
| "translate_text(source_language=English, target_language=Spanish, text=Where is the nearest hospital?)", | |
| "translate_text(source_language=English, target_language=Japanese, text=Where is the nearest hospital?)" | |
| ], | |
| "total_tokens": 1595, | |
| "ttft_ms": 591.2, | |
| "turn_count": 2, | |
| "turn_latencies_ms": [ | |
| 926.9, | |
| 862.8 | |
| ] | |
| }, | |
| { | |
| "duration_seconds": 1.26, | |
| "expected_behavior": "Avoid tools for basic knowledge.", | |
| "note": null, | |
| "points": 2, | |
| "raw_log": "model=wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1\nscenario=TC-10 Trivial Knowledge\nprompt=What year did World War II end?\n\nassistant=starting\navailable_tools=web_search, get_weather, calculator, send_email, search_files, read_file, create_calendar_event, get_contacts, translate_text, get_stock_price, set_reminder, run_code\ntool_choice=auto\nassistant_turn_1=World War II ended in **1945**. Specifically:\n\n- **May 8, 1945** \u2014 Germany surrendered, marking the end of the war in Europe (known as V-E Day).\n- **September 2, 1945** \u2014 Japan formally signed the instrument of surrender aboard the USS Missouri, marking the official end of the war in the Pacific (V-J Day).\nassistant_reasoning_1=The user is asking a simple factual question: What year did World War II end? This is common knowledge \u2014 World War II ended in 1945 (in Europe on May 8, 1945, and in the Pacific on September 2, 1945). No tool call is needed.\nfinal_answer=World War II ended in **1945**. Specifically:\n\n- **May 8, 1945** \u2014 Germany surrendered, marking the end of the war in Europe (known as V-E Day).\n- **September 2, 1945** \u2014 Japan formally signed the instrument of surrender aboard the USS Missouri, marking the official end of the war in the Pacific (V-J Day).\n\nverdict=pass\nsummary=Answered directly without tool use.", | |
| "scenario_id": "TC-10", | |
| "status": "pass", | |
| "summary": "Answered directly without tool use.", | |
| "tool_calls_made": [], | |
| "ttft_ms": 770.3, | |
| "turn_count": 1, | |
| "turn_latencies_ms": [ | |
| 1260.0 | |
| ] | |
| }, | |
| { | |
| "duration_seconds": 4.27, | |
| "expected_behavior": "Refuse cleanly when no suitable tool exists.", | |
| "note": null, | |
| "points": 2, | |
| "raw_log": "model=wrldsuksgo2mars/GLM-5.3-Flash-EXL3-K3.25-v1\nscenario=TC-12 Impossible Request\nprompt=Delete all my emails from last month.\n\nassistant=starting\navailable_tools=web_search, get_weather, calculator, send_email, search_files, read_file, create_calendar_event, get_contacts, translate_text, get_stock_price, set_reminder, run_code\ntool_choice=auto\nassistant_turn_1=I'm not able to do that \u2014 I don't have any tool for managing or deleting emails. My email-related capability is limited to **sending** new emails; I can't access your inbox, search existing messages, or delete anything.\n\nHere's how you could do it yourself instead:\n\n1. **Gmail**: Search with `before:2026/3/1 after:2026/2/1` (or use the date range filter), select all matching messages, and delete them. You can also create a filter to auto-delete future messages in that range.\n2. **Outlook**: Use the search bar with `received:01/02/2026..28/02/2026`, then bulk-select and delete.\n3. **Apple Mail**: Sort by date received, select the range, and delete.\n\nA couple of cautions before bulk-deleting:\n- **Check for anything important first** \u2014 receipts, confirmations, or personal messages from that period.\n- Deleted emails usually go to **Trash/Deleted Items**, where they'll be permanently removed after ~30 days, so you have a grace period to recover mistakes.\n\nIs there anything else I can help with, like sending an email or setting a reminder?\nassistant_reasoning_1=The user is asking me to delete all their emails from last month. Let me look at my available tools:\n\n1. web_search\n2. get_weather\n3. calculator\n4. send_email\n5. search_files\n6. read_file\n7. create_calendar_event\n8. get_contacts\n9. translate_text\n10. get_stock_price\n11. set_reminder\n12. run_code\n\nI don't have any tool to delete emails. I have a send_email tool, but that only sends emails \u2014 it can't delete them. There's no email management tool available.\n\nAccording to my rules:\n- Use a tool ONLY when necessary to fulfill the user's request\n- If a tool call fails, explain the failure and suggest an alternative approach\n- Never invent information that a tool should provide\n\nI should not attempt to call a tool that doesn't exist. I should explain that I don't have the capability to delete emails, and suggest alternatives (like doing it manually in their email client, or using email filters).\n\nI should be honest and clear about this limitation. I shouldn't pretend to delete emails or make up a tool call.\nfinal_answer=I'm not able to do that \u2014 I don't have any tool for managing or deleting emails. My email-related capability is limited to **sending** new emails; I can't access your inbox, search existing messages, or delete anything.\n\nHere's how you could do it yourself instead:\n\n1. **Gmail**: Search with `before:2026/3/1 after:2026/2/1` (or use the date range filter), select all matching messages, and delete them. You can also create a filter to auto-delete future messages in that range.\n2. **Outlook**: Use the search bar with `received:01/02/2026..28/02/2026`, then bulk-select and delete.\n3. **Apple Mail**: Sort by date received, select the range, and delete.\n\nA couple of cautions before bulk-deleting:\n- **Check for anything important first** \u2014 receipts, confirmations, or personal messages from that period.\n- Deleted emails usually go to **Trash/Deleted Items**, where they'll be permanently removed after ~30 days, so you have a grace period to recover mistakes.\n\nIs there anything else I can help with, like sending an email or setting a reminder?\n\nverdict=pass\nsummary=Refused cleanly because no delete-email tool exists.", | |
| "scenario_id": "TC-12", | |
| "status": "pass", | |
| "summary": "Refused cleanly because no delete-email tool exists.", | |
| "tool_calls_made": [], | |
| "ttft_ms": 1901.0, | |
| "turn_count": 1, | |
| "turn_latencies_ms": [ | |
| 4265.6 | |
| ] | |
| } | |
| ], | |
| "token_efficiency": 1.59, | |
| "total_points": 10, | |
| "total_tokens": 6271, | |
| "worst_category": "A Tool Selection (100%)", | |
| "worst_category_percent": 100 | |
| }, | |
| "status": "completed", | |
| "tool_eval_bench_version": "2.3.2.dev3+g5df1e9e0c", | |
| "total_scenarios": 5 | |
| } | |