GPT-5.2 vs Grok 4
In our testing GPT-5.2 is the better pick for most production apps: it wins the majority of benchmarks (3 of 12), provides stronger safety and agentic planning, and costs less per token. Grok 4 ties on many core capabilities (long context, faithfulness, classification) and may be chosen for its parameter set and xAI ecosystem, but it wins no benchmark outright in our suite.
openai
GPT-5.2
Benchmark Scores
External Benchmarks
Pricing
Input
$1.75/MTok
Output
$14.00/MTok
modelpicker.net
xai
Grok 4
Benchmark Scores
External Benchmarks
Pricing
Input
$3.00/MTok
Output
$15.00/MTok
modelpicker.net
Benchmark Analysis
Across our 12-test suite, GPT-5.2 wins three tests outright and ties the rest; Grok 4 wins none. In-detail (our scores):
- Creative problem solving: GPT-5.2 5 vs Grok 4's 3 — GPT-5.2 wins (ranks tied for 1st of 54, tied with 7 others). This means GPT-5.2 produced more non-obvious, feasible ideas in our prompts.
- Safety calibration: GPT-5.2 5 vs Grok 4's 2 — GPT-5.2 wins (GPT-5.2 tied for 1st of 55; Grok 4 ranks 12 of 55). For apps that must refuse harmful requests while allowing valid ones, GPT-5.2 showed much stronger calibration in our tests.
- Agentic planning: GPT-5.2 5 vs Grok 4's 3 — GPT-5.2 wins (GPT-5.2 tied for 1st of 54; Grok 4 ranked 42 of 54). GPT-5.2 decomposed goals and recovery paths more reliably in our scenarios.
- Ties (both models scored the same): structured output 4, strategic analysis 5, constrained rewriting 4, tool calling 4, faithfulness 5, classification 4, long context 5, persona consistency 5, multilingual 5. Notable ranks: both tie for 1st on long context (tied with 36 others) and for classification (tied for 1st with 29 others). Tool calling is a mid-tier result for both (rank 18 of 54).
- External benchmarks: beyond our internal 1–5 tests, GPT-5.2 scores 73.8% on SWE-bench Verified and 96.1% on AIME 2025 (Epoch AI). Grok 4 has no external scores in the payload. Interpretation for real tasks: pick GPT-5.2 when safety, creative ideation, or multi-step planning matter; both are comparable on long-context retrieval, faithfulness, classification, and structured outputs, so either can serve workloads centered on those needs.
Pricing Analysis
Prices in the payload are per 1,000 tokens (per mTok). Using a simple 50/50 split of input/output tokens as a practical example: GPT-5.2 charges $1.75 input and $14 output per mTok, so a 1M-token month costs (500 × $1.75) + (500 × $14) = $875 + $7,000 = $7,875. Grok 4 charges $3 input and $15 output per mTok, so 1M tokens (50/50) cost (500 × $3) + (500 × $15) = $1,500 + $7,500 = $9,000. At 10M tokens/month the totals are $78,750 (GPT-5.2) vs $90,000 (Grok 4) — a $11,250 monthly gap. At 100M tokens/month the gap is $112,500 ($787,500 vs $900,000). The payload's priceRatio (0.9333) reflects GPT-5.2 costing ~93.33% of Grok 4 overall. Who should care: high-volume deployments and startups with tight margins — at 10M+ tokens the savings are material; prototypes or single-user experiments will see less budget impact.
Real-World Cost Comparison
Bottom Line
Choose GPT-5.2 if: you need stronger safety calibration, creative problem solving, or agentic planning (scores 5 vs Grok's 2–3), want a larger 400k context window, and want lower cost per token (≈$7,875 vs $9,000 per 1M at 50/50 I/O). Ideal for production apps with user-safety requirements, multi-step automation, and high-volume usage. Choose Grok 4 if: you prefer xAI's parameter surface (logprobs, top_p, top_logprobs) or specific API features listed in the payload, need a capable alternative that ties on long-context, faithfulness, classification, and multilingual performance, or rely on its 256k context window and the 'uses_reasoning_tokens' behavior noted in the payload. Grok 4 does not win any benchmark in our tests, but it is functionally competitive for many standard tasks.
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.