GPT-6 Astra vs Gemini 4 Argon vs Claude Opus 5.5 Comparability

GPT-6 Astra, Gemini 4 Argon, and Claude Opus 5.5 are three highly effective AI fashions, however which one performs higher when given precise work? To search out out, we put them by means of 4 sensible duties involving challenge reporting, knowledge evaluation, product wireframing, and go-to-market technique.

Moderately than counting on benchmark scores, we examined how precisely every mannequin adopted directions, dealt with equipped recordsdata, and delivered usable outcomes. On this article, we evaluate their outputs, study the place every mannequin succeeded or struggled, and reveal which carried out greatest total.

How I examined them

Listed below are the settings I had used for testing the three fashions:

Excessive is Argon’s highest pondering setting. These app settings don’t equalize compute or instruments. I made one try per job, plus one Argon CSV retry; this can be a hands-on comparability, not a repeated-trial benchmark.

For mannequin background, learn:

1. GPT-6 Astra: Options, Benchmarks, Pricing, and What’s New
2. Gemini 4 Argon Overview: Options, Pricing, and Efficiency
3. Claude Opus 5.5 Examined: What’s New and How Good Is It?

1. Product wireframing

ShiftBridge’s transient requested for a food-bank coordinator dashboard with protection, filtering and eligible-volunteer task panels.

Immediate

I’ve connected the ShiftBridge product transient. Construct the coordinator dashboard as a clear, usable wireframe I can open in a browser. Make it one self-contained HTML file with all types and interactions included, and observe the transient’s content material and necessities.

I need to see the total desktop display at 1440 x 900 and nonetheless be capable of apply it to cell. Make the uncovered-shifts filter and the task panel work. Hold the interface centered on the coordinator’s precise job. Ship the HTML file; hold any rationalization below 60 phrases. Use solely the connected transient.

GPT Astra:

Gemini 4 Argon:

Opus 5.5:

Overview:

All three produced working, self-contained HTML. Filters appropriately hid and restored the staffed shift. Project panels confirmed Alex for packing and Sam/Priya for supply; closing and Escape labored, with focus returning appropriately. Cellular checks at 390 × 844 handed (responsive design).

Astra and Opus match the requested 1440 × 900 desktop. Argon prolonged to 987 pixels and required saving its unchanged chat code manually. Argon additionally produced the most simple wanting design of all of them (some buttons weren’t useful both).

2. Mission reporting

The 2-page Harbor Clinic PDF contained conflicting updates. The job was to reconcile them right into a sponsor report.

Immediate

I’ve connected the Harbor Clinic challenge packet. Write the challenge report I ought to ship to the sponsor as of twenty-two October 2026. Hold it below 350 phrases, together with one compact desk of an important dangers and actions.

Give me the general standing, whether or not the two November pilot ought to proceed primarily based on the proof obtainable at this time, the present funds place, and the selections wanted earlier than the 30 October checkpoint. Use the most recent proof when the paperwork disagree. Embody homeowners and dates the place the packet provides them, and be clear about something nonetheless unconfirmed. Use solely the connected packet.

Astra Report:

Argon Report:

Opus Report:

Overview: All three used the most recent 18/24 acceptance end result and two open priority-one defects. Their $53,600 forecast appropriately uncovered a $5,600 funds hole. None handled scheduled opinions as approvals or approved the pilot prematurely. House owners, actions and dates had been usable.

Astra was compact; Argon used a traditional report construction. Opus usefully flagged the unconfirmed privateness assessment falling on choice day. All three gave a passable response.

3. Knowledge insights

BrightPath equipped an precise acquisition CSV and measurement transient. The choice was the place to spend the subsequent $1,000.

Immediate

I’ve connected BrightPath’s acquisition CSV and the brief measurement transient. Evaluate the final 4 weeks with the primary 4 weeks and inform me what modified, why the headline signup conversion price moved, and the place the subsequent $1,000 ought to go.

Give me one compact before-and-after desk, three helpful insights, two concrete actions, and one limitation. Test channel-level outcomes in addition to the overall, and contemplate activated learners fairly than signups alone. Use the precise recordsdata, present numbers I can confirm, and hold the reply below 350 phrases. Use solely the connected materials.

Astra Response:

Opus Response:

Argon Response (incomplete):

Overview:

Astra and Opus caught the entice: search conversion improved from 10% to 11%, and social from 4% to five%. The blended price fell as a result of lower-converting social grew from 16.7% to 75% of classes. Each prioritized a monitored search check: current activation prices had been $19.70 for search versus $33.33 for social. Neither assured marginal returns.

Argon reported an empty CSV and returned an unpopulated framework. A recent retry with an identical recordsdata additionally failed. Each had been confirmed Argon Excessive responses.

4. GTM technique

ShelfCheck wanted twelve new paying shops by day 42, with fourteen-day trials, six weekly onboardings and restricted founder time.

Immediate

I’ve connected the ShelfCheck launch transient. Give me a sensible six-week GTM technique to succeed in 12 new paying shops by day 42. Decide the primary buyer section, write a transparent positioning line, select the primary acquisition route, and lay out the weekly plan.

Embody a small launch funds and funnel with the assumptions labelled, the trial and onboarding timing, the acquisition-cost verify, and two particular thresholds for altering the plan. Work inside the precise product, money and crew limits. Hold it below 450 phrases and use solely the connected transient.

Astra GTM:

Opus GTM:

Argon GTM:

Overview:

All three focused impartial retailers, prevented unsupported integrations and used heat outreach. They revered the efficient $3,000 acquisition ceiling: twelve clients × $250 CAC. At most 24 trials might begin by day 28; twelve payers require a minimum of 50% conversion.

Astra’s $1,200 plan explicitly raised the required conversion forecast after missed begins. Opus’s $1,250 plan was sound, however its “a minimum of 55%” fallback was too free: 9 early begins depart 21 potential trials, requiring 57.1%. Argon’s $1,200 plan couldn’t recuperate misplaced capability merely by filling later weeks; it additionally exceeded 450 phrases.

Argon’s exercise confirmed an online search regardless of the brief-only instruction; remaining materials details stayed inside the transient.

Scorecard

Astra is my slim choose right here. Opus accomplished all 4 duties and tied on three; its launch contingency wanted tightening. Argon’s accomplished work was helpful, however the CSV failure limits comparability throughout the set. NC just isn’t zero, so I’ve not assigned Argon an total whole.

API record costs checked on 22 October had been 50 per million enter/output tokens for Astra and 10 for Opus. Argon listed 10 by means of November, then 20 from December. Browser-task prices weren’t measured; these charges don’t set up the price of these runs.

Ceaselessly Requested Questions

Learning, evaluating, and explaining AI techniques for over 6 years.

“𝘖𝘯𝘤𝘦 𝘮𝘦𝘯 𝘵𝘶𝘳𝘯𝘦𝘥 𝘵𝘩𝘦𝘪𝘳 𝘵𝘩𝘪𝘯𝘬𝘪𝘯𝘨 𝘰𝘷𝘦𝘳 𝘵𝘰 𝘮𝘢𝘤𝘩𝘪𝘯𝘦𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘩𝘰𝘱𝘦 𝘵𝘩𝘢𝘵 𝘵𝘩𝘪𝘴 𝘸𝘰𝘶𝘭𝘥 𝘴𝘦𝘵 𝘵𝘩𝘦𝘮 𝘧𝘳𝘦𝘦. 𝘉𝘶𝘵 𝘵𝘩𝘢𝘵 𝘰𝘯𝘭𝘺 𝘱𝘦𝘳𝘮𝘪𝘵𝘵𝘦𝘥 𝘰𝘵𝘩𝘦𝘳 𝘮𝘦𝘯 𝘸𝘪𝘵𝘩 𝘮𝘢𝘤𝘩𝘪𝘯𝘦𝘴 𝘵𝘰 𝘦𝘯𝘴𝘭𝘢𝘷𝘦 𝘵𝘩𝘦𝘮.” — 𝖥𝗋𝖺𝗇𝗄 𝖧𝖾𝗋𝖻𝖾𝗋𝗍, 𝖣𝗎𝗇𝖾