GPT-5.3-Codex vs Grok 4.5 for multi-step research
GPT-5.3-Codex wins, 94–85
Same 12 multi-step research tasks, marked blind by three rival labs. GPT-5.3-Codex took 8 tasks, Grok 4.5 took 1, 3 tied. Tested 27 Aug 2026.
Where they differed most
Four sources, all real-shaped, all about empty shops in one seaside town. Source A — borough council economic development report, March 2026: 'town centre vacancy stands at 18.4% (74 of 402 units), down from 21.1% in 2024.' Source B — a national retail body's Q1 2026 briefing: 'the North East average is 16.2%; Redcar is cited at 23%.' Source C — local newspaper, February 2026: 'traders say more than a third of the high street now sits empty.' Source D — a commercial property agent's listings page, April 2026: '31 units currently available to let in Redcar town centre.' Write the synthesis. It must say what the four sources JOINTLY support, attribute every claim to the source that carries it, explain why the figures differ rather than picking a favourite (note what 'town centre' and 'high street' and 'available to let' each measure), and end by stating plainly what none of them establishes. Banned, because a research answer must attribute: 'studies show', 'research suggests', 'it is widely accepted'.
Taken together, the four sources support one cautious conclusion: **empty premises in Redcar are a material town-centre issue in early 2026, but the exact level depends on what is being counted**. - **Source A (borough council, March 2026)** reports a **town-centre vacancy rate of 18.4% (74 of 402 units)**, and says this is down from **21.1% in 2024**. - **Source B (national retail body, Q1 2026)** places the **North East average at 16.2%** and **cites Redcar at 23%**, indicating Redcar is above the regional benchmark in that source’s datase…
**Synthesis** The four sources jointly support that Redcar had a substantial number of empty commercial units in its central shopping area in early 2026, with vacancy clearly above negligible levels and, on one measure, above the regional average, even though the precise scale is reported differently. The borough council economic development report (Source A, March 2026) states that town-centre vacancy stands at 18.4% (74 of 402 units), down from 21.1% in 2024. The national retail body’s Q1 2026 briefing (Source B) gives the North East averag…
Task by task
| Task | GPT-5.3-Codex | Grok 4.5 |
|---|---|---|
| Four numbers, one high street | 10 | 8 |
| The trial that both worked and didn't | 8 | 8 |
| Break the brief into answerable steps | 10 | 9 |
| Corroboration that isn't | 9 | 8 |
| The disagreement is definitional | 9 | 7 |
| A forecast is not an outcome | 9 | 8 |
| The evidence table, as JSON | 10 | 10 |
| Funded, and still the best data | 9.5 | 8 |
| Write only the limits section | 8 | 9 |
| Not answerable from what you have | 10 | 9 |
| The statistic and the doorstep | 10 | 8 |
| Refuse the manufactured briefing | 10 | 10 |
Full receipts: GPT-5.3-Codex, Grok 4.5 · judges claude-sonnet-5, gemini-3.1-pro-preview, grok-4.5
Questions people ask
Which is better for multi-step research: GPT-5.3-Codex or Grok 4.5?
GPT-5.3-Codex — it scored 94/100 against 85/100 on our 12-task multi-step research suite, winning 8 tasks to 1 with 3 tied. Every answer was marked blind by three judges from three rival AI labs.
How was this tested?
Both models answered the identical published multi-step research tasks. Three AI judges from three different labs scored every answer blind against a fixed rubric; mechanically checkable rules (word limits, banned phrases) are enforced by the test harness in code. The raw outputs and judge verdicts are downloadable.
More multi-step research head-to-heads: GPT-5.3-Codex vs GPT-5.6 Terra · GPT-5.6 Terra vs Grok 4.5 · Claude Sonnet 5 vs GPT-5.3-Codex · GPT-5.3-Codex vs GPT-5.5 · GPT-5.3-Codex vs GPT-5.6 Luna · GPT-5.3-Codex vs GPT-5.6 Sol
Full ranking: Best AI for multi-step research · model pages: GPT-5.3-Codex, Grok 4.5