This matchup turns on instruction discipline versus presentation polish. Cohere-command-a steals one business-writing round, but grok-4.3 is the more reliable model where exactness actually matters.
The aggregate score says it plainly: grok-4.3 wins 36.6 to 30.1, and the task breakdown backs that up. This was not a vibes contest. It was a test of whether a model can follow constraints, preserve structure, and avoid introducing subtle errors when the prompt leaves little room for improvisation.
The clearest separation showed up in the technical tasks. On `python-log-redactor`, grok-4.3 was simply tighter: it redacted only query parameters preceded by `?` or `&`, preserved the original key casing through captured groups, and avoided the sloppiness in Cohere-command-a’s approach, which could redact `mytoken=...` anywhere in a line and used a weaker IPv4 regex that also matched invalid addresses. That is the difference between a tool you can trust in production and one that creates fresh cleanup work.
Grok-4.3 also handled structured-output compliance better. In `meeting-notes-summary`, it delivered the requested two-sentence summary and a JSON object with the specified keys, while still capturing both key decisions. Cohere-command-a dropped the Android rollout decision from `decisions` and rewired `action_items` into objects instead of the requested simple list. In `messy-orders-to-json`, both models understood the data, but only grok-4.3 respected the instruction to return valid JSON only; Cohere-command-a wrapped its answer in Markdown fences and failed on a basic formatting requirement.
Cohere-command-a’s one win, `vendor-delay-update`, is real but limited. Its response was better organized for the internal audience, with clearer separation of scope, ETA-page status, and next steps for Sales and Support. Grok-4.3 was accurate, but less polished in the customer-facing message and less direct in team guidance. That matters for internal comms. It just does not outweigh repeated misses on precision and schema fidelity elsewhere.
**Final call: grok-4.3 is the stronger text model here because it is more exact, more compliant, and less likely to break the brief in high-consequence tasks. Cohere-command-a writes a neater status update, but grok-4.3 wins the head-to-head on substance.**
python-log-redactor
Language: Python 3.11
Return code only.
Write a function `redact_log(line: str) -> str` for an API gateway that removes sensitive data from a single log line.
Requirements:
- Replace any IPv4 address with `[IP]`.
- Replace any email address with `[EMAIL]`.
- Replace any value of query params named `token`, `api_key`, or `sessionid` with `[REDACTED]`, preserving the key and separators. Example: `token=abc123` -> `token=[REDACTED]`.
- Matching for param names is case-insensitive.
- Do not alter other text.
- Use only the standard library.
Also include a few `assert` tests at the bottom covering mixed cases like:
`2026-04-18T09:14:03Z GET /v1/export?token=q9Z!&page=2 from 198.51.100.24 user=maya@larkspur.tools`
`POST /login?SessionId=xy-77&redirect=/dash by aaron+ops@northjet.io via 203.0.113.9`
`no secrets here`
grok-4.3: ```python
import re
def redact_log(line: str) -> str:
def redact_param(m):
return f"{m.group(1)}{m.group(2)}=[REDACTED]"
line = re.sub(r'([?&])(token|api_key|sessionid)=[^&#\s]*', redact_param, line, flags=re.IGNORECASE)
line = re.sub(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}\b', '[EMAIL]', line)
line = re.sub(r'\b(?:(?:25[0-5]|2[0-4][0-9]|1[0-9][0-9]|[1-9]?[0-9])\.){3}(?:25[0-5]|2[0-4][0-9]|1[0-9][0-9]|[1-9]?[0-9])\b', '[IP]', line)
return line
assert redact_log('2026-04-18T09:14:03Z GET /v1/export?token=q9Z!&page=2 from 198.51.100.24 user=maya@larkspur.tools') == '2026-04-18T09:14:03Z GET /v1/export?token=[REDACTED]&page=2 from [IP] user=[EMAIL]'
assert redact_log('POST /login?SessionId=xy-77&redirect=/dash by aaron+ops@northjet.io via 203.0.113.9') == 'POST /login?SessionId=[REDACTED]&redirect=/dash by [EMAIL] via [IP]'
assert redact_log('no secrets here') == 'no secrets here'
```
cohere-command-a: ```python
import re
def redact_log(line: str) -> str:
"""
Redacts sensitive data from a log line.
Replaces IPv4 addresses, email addresses, and specific query parameters with placeholders.
Args:
line (str): The log line to redact
Returns:
str: The redacted log line
"""
# Replace IPv4 addresses
line = re.sub(
r"\b(?:\d{1,3}\.){3}\d{1,3}\b", "[IP]", line
) # Standard IPv4 regex
# Replace email addresses
line = re.sub(
r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b", "[EMAIL]", line
)
# Replace sensitive query parameters (case-insensitive)
line = re.sub(
r"(?i)(token|api_key|sessionid)=[^&]*",
lambda m: f"{m.group(1)}=[REDACTED]",
line,
)
return line
# Tests
assert (
redact_log(
"2026-04-18T09:14:03Z GET /v1/export?token=q9Z!&page=2 from 198.51.100.24 user=maya@larkspur.tools"
)
== "2026-04-18T09:14:03Z GET /v1/export?token=[REDACTED]&page=2 from [IP] user=[EMAIL]"
)
assert (
redact_log(
"POST /login?SessionId=xy-77&redirect=/dash by aaron+ops@northjet.io via 203.0.113.9"
)
== "POST /login?SessionId=[REDACTED]&redirect=/dash by [EMAIL] via [IP]"
)
assert redact_log("no secrets here") == "no secrets here"
```
A better preserves the required query-param separators by matching only params preceded by ? or & and keeps the original key casing via captured groups. B is less precise: it can redact non-query text like 'mytoken=...' anywhere in the line, does not preserve the exact matched key casing in the replacement, and uses a looser IPv4 regex that matches invalid addresses.
vendor-delay-update
Draft a status update email to our internal sales and support teams.
Context: Our warehouse vendor, BlueHarbor Fulfillment, had a scanner outage this morning from 07:20 to 10:05 local time. Orders were received but not picked during that window. We estimate 143 orders will ship one business day late. No data loss, no payment issues, and expedited orders placed after 10:05 are flowing normally. Customer-facing ETA pages have not yet been updated. We expect the backlog cleared by tomorrow 14:00. Support needs a short approved message to use with affected customers. Sales needs to know this only affects US East inventory, not custom-engraved items.
Write one email:
- audience: internal sales + support
- tone: calm, accountable, practical
- length: 170-220 words
- include a 3-bullet "What to tell customers" section
- include a clear subject line
grok-4.3: Subject: BlueHarbor Fulfillment Scanner Outage – Order Processing Update
Team,
Our warehouse vendor, BlueHarbor Fulfillment, experienced a scanner outage from 07:20 to 10:05 local time this morning. Orders were received but not picked during that window. We estimate this will cause 143 orders to ship one business day late.
There is no data loss or payment issues to report. Expedited orders placed after 10:05 are processing normally. This outage only affects US East inventory and does not impact custom-engraved items. We expect to clear the backlog by tomorrow at 14:00, though customer-facing ETA pages have not been updated yet.
To keep our messaging consistent, here is the approved guidance for affected customers:
- We had a temporary scanner outage at our fulfillment center this morning, which prevented orders from being picked for a few hours.
- Your order will now ship one business day later than the original estimate.
- We apologize for the delay and are prioritizing these orders to get them out as soon as possible.
If you need help with a specific customer or have questions, please reach out directly.
Best regards,
cohere-command-a: **Subject: BlueHarbor Scanner Outage Update – Impact on US East Orders**
Team,
This morning, our warehouse vendor, BlueHarbor Fulfillment, experienced a scanner outage from 07:20 to 10:05 local time. During this window, orders were received but not picked, resulting in an estimated 143 orders shipping one business day late. The issue has been resolved, and there was no data loss or payment disruption. Expedited orders placed after 10:05 are processing normally.
Here’s what you need to know:
- **Scope**: This affects only US East inventory. Custom-engraved items are not impacted.
- **Customer ETAs**: Affected orders’ estimated delivery dates have not yet been updated on customer-facing pages. We expect the backlog to be cleared by tomorrow at 14:00.
- **Next Steps**: Support, please use the approved messaging below when engaging with affected customers. Sales, ensure your teams are aware of the delay for US East orders only.
**What to Tell Customers**
- *“We experienced a temporary delay in our fulfillment process earlier today, which may affect your order’s delivery date by one business day.”*
- *“We’re working quickly to resolve this, and your order should be back on track by tomorrow.”*
- *“Thank you for your patience—we apologize for any inconvenience.”*
Let’s stay proactive and keep communication clear. Reach out if you have questions.
Best,
[Your Name]
B is slightly better organized for the internal audience, explicitly separates scope, ETA-page status, and next steps for Sales and Support, while staying within the requested tone and length. A is solid and accurate, but its customer message is a bit less polished and it gives less direct guidance to the two teams.
meeting-notes-summary
Read the meeting notes below, then provide:
1) a 2-sentence summary
2) a JSON object with keys: `launch_date`, `owner`, `blocked_by`, `decisions`, `action_items`
Meeting notes:
- Team: Nimbus Note mobile sync
- Priya said Android crash rate improved after 5.4.2, but offline edits still duplicate attachments in rare cases.
- Marco wants to keep the staged rollout at 25% until support confirms fewer than 15 duplicate-attachment tickets/day for 3 straight days.
- Decision: iOS release can go out Tuesday 12 Aug if legal approves the revised backup-copy text.
- Legal review owner is Dana; she said feedback by Monday 15:00.
- Blocker: the French translation for the backup-copy screen still uses the old retention wording.
- Action: Jules to patch the French string today.
- Action: Priya to post a support-ticket trend snapshot in #mobile-quality every morning through Tuesday.
- Action: Marco to prepare rollback steps before the release meeting.
- Reminder: enterprise customers on legacy sync are not affected.
grok-4.3: 1) The Nimbus Note mobile sync team noted improved Android crash rates after 5.4.2 but decided to hold the staged rollout at 25% until duplicate-attachment support tickets stay below 15 per day for three straight days, while also addressing rare offline duplication bugs. For iOS, release is set for Tuesday 12 Aug pending legal approval of revised backup-copy text, with a French translation blocker, daily monitoring actions, and rollback prep all in progress.
2)
```json
{
"launch_date": "Tuesday 12 Aug",
"owner": "Dana",
"blocked_by": "French translation for the backup-copy screen still uses the old retention wording",
"decisions": [
"iOS release can go out Tuesday 12 Aug if legal approves the revised backup-copy text",
"Keep Android staged rollout at 25% until support confirms fewer than 15 duplicate-attachment tickets/day for 3 straight days"
],
"action_items": [
"Jules to patch the French string today",
"Priya to post a support-ticket trend snapshot in #mobile-quality every morning through Tuesday",
"Marco to prepare rollback steps before the release meeting"
]
}
```
cohere-command-a: ### Summary:
The Nimbus Note mobile sync team discussed ongoing issues with the Android app, particularly rare cases of duplicate attachments in offline edits, and decided to maintain a staged rollout at 25% until support tickets decrease. The iOS release is scheduled for Tuesday, August 12, pending legal approval of revised backup-copy text and resolution of a French translation issue.
### JSON Object:
```json
{
"launch_date": "Tuesday 12 Aug",
"owner": "Dana (Legal review)",
"blocked_by": "French translation for backup-copy screen using old retention wording",
"decisions": [
"iOS release can go out Tuesday 12 Aug if legal approves revised backup-copy text"
],
"action_items": [
{
"assignee": "Jules",
"task": "Patch the French string today"
},
{
"assignee": "Priya",
"task": "Post a support-ticket trend snapshot in #mobile-quality every morning through Tuesday"
},
{
"assignee": "Marco",
"task": "Prepare rollback steps before the release meeting"
}
]
}
```
A better follows the requested format with a clear 2-sentence summary and a JSON object matching the specified keys while capturing both key decisions. B is mostly correct but omits the Android rollout decision from `decisions` and changes the `action_items` structure from a simple list to objects, which is less faithful to the prompt.
messy-orders-to-json
Convert the messy order notes below into valid JSON only.
Output schema:
{
"orders": [
{
"order_id": string,
"customer": string,
"ship_country": string,
"items": [{"sku": string, "qty": integer}],
"priority": "low" | "normal" | "high",
"gift": boolean
}
]
}
Rules:
- Preserve input order.
- Normalize country names to full English names.
- Trim spaces.
- Quantities are integers.
- If priority missing, use "normal".
- Interpret gift markers yes/y/true as true; no/n/false as false.
- Do not invent missing items.
Messy notes:
1. order=QF-1908 | customer: Nila Voss | country=DE | items: AX-4 x2, BOLT-9 x 1 | gift=y | priority=high
2. customer=Orin Hale; id QF-1909; ship to: United States ; lines= MUG-RED*4 ; gift=no
3. QF-1910 / Mei Tan / UK / SKUs [PEN-2 qty 3 ; NOTE-88 qty 12] / priority low / gift true
4. id:QF-1911, customer: "R. Ibarra", country: jp, items: CABLE-USB-C x1, ADAPT-2 x2, , gift: n
grok-4.3: {
"orders": [
{
"order_id": "QF-1908",
"customer": "Nila Voss",
"ship_country": "Germany",
"items": [
{"sku": "AX-4", "qty": 2},
{"sku": "BOLT-9", "qty": 1}
],
"priority": "high",
"gift": true
},
{
"order_id": "QF-1909",
"customer": "Orin Hale",
"ship_country": "United States",
"items": [
{"sku": "MUG-RED", "qty": 4}
],
"priority": "normal",
"gift": false
},
{
"order_id": "QF-1910",
"customer": "Mei Tan",
"ship_country": "United Kingdom",
"items": [
{"sku": "PEN-2", "qty": 3},
{"sku": "NOTE-88", "qty": 12}
],
"priority": "low",
"gift": true
},
{
"order_id": "QF-1911",
"customer": "R. Ibarra",
"ship_country": "Japan",
"items": [
{"sku": "CABLE-USB-C", "qty": 1},
{"sku": "ADAPT-2", "qty": 2}
],
"priority": "normal",
"gift": false
}
]
}
cohere-command-a: ```json
{
"orders": [
{
"order_id": "QF-1908",
"customer": "Nila Voss",
"ship_country": "Germany",
"items": [
{"sku": "AX-4", "qty": 2},
{"sku": "BOLT-9", "qty": 1}
],
"priority": "high",
"gift": true
},
{
"order_id": "QF-1909",
"customer": "Orin Hale",
"ship_country": "United States",
"items": [
{"sku": "MUG-RED", "qty": 4}
],
"priority": "normal",
"gift": false
},
{
"order_id": "QF-1910",
"customer": "Mei Tan",
"ship_country": "United Kingdom",
"items": [
{"sku": "PEN-2", "qty": 3},
{"sku": "NOTE-88", "qty": 12}
],
"priority": "low",
"gift": true
},
{
"order_id": "QF-1911",
"customer": "R. Ibarra",
"ship_country": "Japan",
"items": [
{"sku": "CABLE-USB-C", "qty": 1},
{"sku": "ADAPT-2", "qty": 2}
],
"priority": "normal",
"gift": false
}
]
}
```
Both outputs parse the orders correctly and match the schema content, but A follows the instruction to output valid JSON only. B wraps the JSON in Markdown code fences, so it is not JSON-only and is less compliant.
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