GPT-4o vs Grok 3 Mini

Overview: In our 12-test head-to-head, Grok 3 Mini wins 6 tests, GPT-4o wins 1, and 5 tests tie. Details by test:

• safety calibration: Grok 3 Mini 2 vs GPT-4o 1 — Grok ranks “rank 12 of 55 (20 models share this score)” vs GPT-4o “rank 32 of 55 (24 models share this score)”. That means Grok is materially more likely in our testing to refuse harmful requests and accept legitimate ones.

• agentic planning: GPT-4o 4 vs Grok 3 — GPT-4o wins and ranks “rank 16 of 54 (26 models share this score)” vs Grok’s “rank 42 of 54.” For goal decomposition and failure recovery, GPT-4o is stronger in our tests.

• creative problem solving: tie at 3 each — both models are comparable for idea generation in our suite (both display “rank 30 of 54”).

• structured output: tie at 4 each — both handle JSON/schema compliance similarly (both “rank 26 of 54”).

• tool calling: Grok 3 Mini 5 vs GPT-4o 4 — Grok is top-tier here (tied for 1st of 54) while GPT-4o is mid-tier (“rank 18 of 54”). In practice Grok is more accurate selecting functions, arguments, and sequencing.

• long context: Grok 3 Mini 5 vs GPT-4o 4 — Grok is tied for 1st of 55 models and GPT-4o sits much lower (“rank 38 of 55”), so Grok better preserves retrieval accuracy at 30K+ tokens in our tests.

• multilingual: tie at 4 each — both perform similarly across non-English outputs (both “rank 36 of 55”).

• classification: tie at 4 each — both tied for 1st among 53 models, so routing and categorization are excellent on both.

• strategic analysis: Grok 3 Mini 3 vs GPT-4o 2 — Grok wins here (rank 36 vs GPT-4o rank 44), indicating better nuanced tradeoff reasoning with numbers.

• faithfulness: Grok 3 Mini 5 vs GPT-4o 4 — Grok ties for 1st of 55 models while GPT-4o is lower (“rank 34 of 55”), so Grok is less prone to hallucination on source tasks in our testing.

• constrained rewriting: Grok 3 Mini 4 vs GPT-4o 3 — Grok’s higher score and “rank 6 of 53” indicate stronger compression within hard character limits.

• persona consistency: tie at 5 each — both maintain character well (both tied for 1st among tested models).

External benchmarks: GPT-4o has external results on third‑party tests — on SWE-bench Verified (Epoch AI) GPT-4o scores 31% (Epoch AI), MATH Level 5 53.3%, and AIME 2025 6.4% per the payload. Grok 3 Mini has no external SWE/math scores in this payload. We treat Epoch AI results as supplementary to our internal tests.

Prices in the payload are listed as per mtok (per 1,000 tokens). GPT-4o: input $2.50/mtok, output $10.00/mtok. Grok 3 Mini: input $0.30/mtok, output $0.50/mtok. Raw costs per 1M tokens (1,000 mtok): GPT-4o = $2,500 input / $10,000 output; Grok 3 Mini = $300 input / $500 output. Under a 50/50 input/output usage assumption per 1M tokens: GPT-4o ≈ $6,250 vs Grok 3 Mini ≈ $400 (a $5,850 gap). Scale multiply: for 10M tokens the 50/50 totals are ~$62,500 vs ~$4,000 (gap ~$58,500); for 100M tokens ~$625,000 vs ~$40,000 (gap ~$585,000). Who should care: any product or team doing sustained API usage (millions of tokens/month) — Grok 3 Mini offers orders-of-magnitude cost savings; GPT-4o’s costs make sense mainly when you need its multimodal inputs or its stronger agentic planning despite the 20x output-price ratio.

Choose Grok 3 Mini if: you need the cheapest production-grade API for high-volume use, best-in-class tool-calling, long-context handling, faithfulness, safety calibration, and constrained rewriting — it wins 6/12 tests and costs ~$400 per 1M tokens under a 50/50 input/output mix. Choose GPT-4o if: you require multimodal inputs (text + image + file → text) and stronger agentic planning despite much higher run costs — it’s the better fit when images/files and advanced goal decomposition are essential and the budget can absorb ~$6,250 per 1M tokens (50/50 split).