💰 Unit Cost Winner OpenAI o3-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 o3-mini?

OpenAI o3-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 (470ms faster than OpenAI o3-mini) with 95 vs. 98 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 86.2% vs. 79.7% 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 o3-mini Net Delta / Advantage
Input Cost / 1M Tokens $2.50 $1.10 OpenAI o3-mini is 2.3x cheaper
Output Cost / 1M Tokens $12.50 $4.40 OpenAI o3-mini (64.8% lower)
Prompt Cache Read / 1M $0.500 $0.550 Grok 4 is 1.1x cheaper
Prompt Cache Write / 1M $2.50 $1.10 OpenAI o3-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 950ms Grok 4 (470ms faster)
Generation Speed (Throughput) 95 tok/s 98 tok/s OpenAI o3-mini (+3 tok/s faster)
SWE-bench Verified (Coding) 73.2% 49.3% Grok 4 (+23.9% lead)
GPQA Diamond (PhD STEM) 86.2% 79.7% Grok 4 (+6.5% lead)
MMLU-Pro (Multi-Discipline) 89.9% 83.2% Grok 4 (+6.7% lead)
MATH-500 (Quantitative Logic) 97.6% 97.9% OpenAI o3-mini (+0.3% lead)
Inference Value Score (IVR) 57.6 / 100 59.7 / 100 OpenAI o3-mini (+2.1 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 o3-mini $42.63

$1.10/1M in · $4.40/1M out

Prompt Cache: $0.550/1M read · $1.10/1M write

Projected Monthly Cost Reduction
$57.38 / mo
(57.4% lower cost with OpenAI o3-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 o3-mini

Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Grok 4 or OpenAI o3-mini?

OpenAI o3-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 o3-mini?

Grok 4 delivers faster first-token latency at 480ms TTFT (95 tok/s throughput) compared to 950ms TTFT (98 tok/s) for OpenAI o3-mini.

How do Grok 4 and OpenAI o3-mini compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Grok 4 scores 73.2% versus 49.3% for OpenAI o3-mini. On GPQA Diamond graduate-level STEM reasoning, Grok 4 scores 86.2% versus 79.7% for OpenAI o3-mini (and 97.6% vs 97.9% 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 o3-mini?

Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).

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