💰 Unit Cost Winner OpenAI o4-mini $1.10/1M in · $4.40/1M out
⚡ Latency & Speed Winner Grok 4 480ms TTFT · 95 tok/s
💻 Coding (SWE) Winner Grok 4 73.2% SWE-bench · 95% HumanEval
🧠 STEM Reasoning Winner Grok 4 86.2% GPQA · 97.6% MATH-500

Which model is better: Grok 4 or OpenAI o4-mini?

OpenAI o4-mini is 56.0% cheaper for input tokens ($1.10 vs. $2.50 per 1M tokens) and $4.40 vs. $12.50 for output tokens (2.3x cost advantage). In terms of operational performance, Grok 4 delivers lower response latency at 480ms TTFT (200ms faster than OpenAI o4-mini) with 95 vs. 125 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 68.1% for OpenAI o4-mini and 86.2% vs. 81.4% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.

Verified Performance & Unit Economics Delta (12 Dimensions)

Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.

Metric / Dimension Grok 4 OpenAI o4-mini Net Delta / Advantage
Input Cost / 1M Tokens $2.50 $1.10 OpenAI o4-mini is 2.3x cheaper
Output Cost / 1M Tokens $12.50 $4.40 OpenAI o4-mini (64.8% lower)
Prompt Cache Read / 1M $0.500 $0.275 OpenAI o4-mini is 1.8x cheaper
Prompt Cache Write / 1M $2.50 $1.10 OpenAI o4-mini is 2.3x cheaper
Context Window (Max Output) 262k (66k out) 205k (100k out) Grok 4 (1.3x larger context)
Avg TTFT Response Latency 480ms 680ms Grok 4 (200ms faster)
Generation Speed (Throughput) 95 tok/s 125 tok/s OpenAI o4-mini (+30 tok/s faster)
SWE-bench Verified (Coding) 73.2% 68.1% Grok 4 (+5.1% lead)
GPQA Diamond (PhD STEM) 86.2% 81.4% Grok 4 (+4.8% lead)
MMLU-Pro (Multi-Discipline) 89.9% 85.6% Grok 4 (+4.3% lead)
MATH-500 (Quantitative Logic) 97.6% 97.8% OpenAI o4-mini (+0.2% lead)
Inference Value Score (IVR) 57.6 / 100 63.7 / 100 OpenAI o4-mini (+6.1 pts)

Interactive Monthly Token Economics & ROI Forecaster

Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.

25.0M Tokens
500K 50M 250M 500M+
5.0M Tokens
100K 25M 75M 150M+
50% Cached
0% (Uncached) 25% 50% (Typical Agent) 95% Max

Estimated Monthly Spend

Grok 4 $100.00

$2.50/1M in · $12.50/1M out

Prompt Cache: $0.500/1M read · $2.50/1M write

OpenAI o4-mini $39.19

$1.10/1M in · $4.40/1M out

Prompt Cache: $0.275/1M read · $1.10/1M write

Projected Monthly Cost Reduction
$60.81 / mo
(60.8% lower cost with OpenAI o4-mini)
Open Full Matchup Analysis →
A

When to Choose Grok 4

Choose Grok 4 (xAI) for real-time financial/market intelligence, PhD-level STEM problem solving, and autonomous code generation — offering a 262k context window, 480ms TTFT, and $2.50/1M input pricing ($0.500/1M cached reads).

B

When to Choose OpenAI o4-mini

Choose OpenAI o4-mini (OpenAI) for automated PR review, high-volume agentic coding loops, SQL/data analysis, and visual document reasoning — offering a 204k context window, 680ms TTFT, and $1.10/1M input pricing ($0.275/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Grok 4 or OpenAI o4-mini?

OpenAI o4-mini is cheaper at $1.10/1M input tokens ($4.40/1M output) compared to $2.50/1M input ($12.50/1M output) for Grok 4.

Which model has lower TTFT latency and higher tok/s throughput: Grok 4 or OpenAI o4-mini?

Grok 4 delivers faster first-token latency at 480ms TTFT (95 tok/s throughput) compared to 680ms TTFT (125 tok/s) for OpenAI o4-mini.

How do Grok 4 and OpenAI o4-mini compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Grok 4 scores 73.2% versus 68.1% for OpenAI o4-mini. On GPQA Diamond graduate-level STEM reasoning, Grok 4 scores 86.2% versus 81.4% for OpenAI o4-mini (and 97.6% vs 97.8% on MATH-500).

When should you choose Grok 4?

Choose Grok 4 (xAI) for real-time financial/market intelligence, PhD-level STEM problem solving, and autonomous code generation — offering a 262k context window, 480ms TTFT, and $2.50/1M input pricing ($0.500/1M cached reads).

When should you choose OpenAI o4-mini?

Choose OpenAI o4-mini (OpenAI) for automated PR review, high-volume agentic coding loops, SQL/data analysis, and visual document reasoning — offering a 204k context window, 680ms TTFT, and $1.10/1M input pricing ($0.275/1M cached reads).

Explore High-Priority Related Model Matchups