GPT-5.4 vs Grok 4 for Research
Winner: GPT-5.4. Both models score 5/5 on our Research task, but GPT-5.4 is the better choice for deep research workflows because it outperforms Grok 4 on safety calibration (5 vs 2), agentic planning (5 vs 3), structured output (5 vs 4) and creative problem solving (4 vs 3). GPT-5.4 also provides a much larger context window (1,050,000 tokens vs 256,000 tokens), lower input cost (2.5 vs 3 per mTok), and has published external results — 76.9% on SWE-bench Verified and 95.3% on AIME 2025 (Epoch AI) — that reinforce its strengths for complex synthesis. Grok 4 is preferable only when accurate classification/routing is the primary need (classification 4 vs GPT-5.4's 3) or when you require Grok’s reasoning-token billing/diagnostics behavior.
openai
GPT-5.4
Benchmark Scores
External Benchmarks
Pricing
Input
$2.50/MTok
Output
$15.00/MTok
modelpicker.net
xai
Grok 4
Benchmark Scores
External Benchmarks
Pricing
Input
$3.00/MTok
Output
$15.00/MTok
modelpicker.net
Task Analysis
What Research demands: literature review and deep synthesis need long-context handling, faithfulness to source material, structured outputs for reproducible results (JSON/tables), agentic planning (decomposing tasks, failover), tool calling for retrieval/experiments, strong safety calibration for sensitive queries, and reliable multilingual/analytic ability. On these dimensions our 1–5 proxies show parity on some cores (long context 5 and faithfulness 5 for both; strategic analysis 5 tied) but clear advantages for GPT-5.4 in safety calibration (5 vs 2), agentic planning (5 vs 3), structured output (5 vs 4), and creative problem solving (4 vs 3). GPT-5.4 additionally reports SWE-bench Verified 76.9% and AIME 2025 95.3% (Epoch AI), which are relevant supplemental signals for coding/math-heavy research tasks; Grok 4 has no external benchmark in the payload. Cost and context matter: GPT-5.4’s larger context window and lower input cost make it more practical for single-shot analysis of very long corpora.
Practical Examples
- Long literature synthesis: GPT-5.4 (context_window 1,050,000) can keep more of a 200k–500k‑token corpus in context and produce compliant structured outputs (structured output 5 vs 4), making it better for end-to-end systematic reviews. 2) Safety-sensitive policy analysis: GPT-5.4’s safety calibration 5 vs Grok 4’s 2 reduces the risk of unsafe or disallowed recommendations in our testing. 3) Multi-step experimental planning: agentic planning 5 (GPT-5.4) vs 3 (Grok 4) — GPT-5.4 is stronger at goal decomposition and recovery in our bench. 4) Classification-heavy triage: Grok 4 is superior for routing and categorical labeling (classification 4 vs GPT-5.4’s 3), so use Grok 4 when accurate, scalable labeling is the priority. 5) Math/coding sub‑tasks: GPT-5.4 reports 76.9% on SWE-bench Verified and 95.3% on AIME 2025 (Epoch AI), suggesting strong external performance on code/math benchmarks; Grok 4 lacks those external scores in the payload.
Bottom Line
For Research, choose GPT-5.4 if you need high safety guarantees, superior agentic planning, strict structured outputs, massive single-session context (1,050,000 tokens), or the external benchmark signals (SWE-bench 76.9%, AIME 95.3% — Epoch AI). Choose Grok 4 if your primary need is classification/routing at scale (classification 4 vs 3) or if you prefer Grok’s reasoning-token behavior (quirk present in payload).
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.