💰 Unit Cost Winner GPT-4o Mini $0.15/1M in · $0.60/1M out
⚡ Latency & Speed Winner GPT-4o Mini 220ms TTFT · 140 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: GPT-4o Mini or Grok 4?

GPT-4o Mini is 94.0% cheaper for input tokens ($0.15 vs. $2.50 per 1M tokens) and $0.60 vs. $12.50 for output tokens (16.7x cost advantage). In terms of operational performance, GPT-4o Mini delivers lower response latency at 220ms TTFT (260ms faster than Grok 4) with 140 vs. 95 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 86.2% vs. 40.2% 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 GPT-4o Mini Grok 4 Net Delta / Advantage
Input Cost / 1M Tokens $0.15 $2.50 GPT-4o Mini is 16.7x cheaper
Output Cost / 1M Tokens $0.60 $12.50 GPT-4o Mini (95.2% lower)
Prompt Cache Read / 1M $0.075 $0.500 GPT-4o Mini is 6.7x cheaper
Prompt Cache Write / 1M $0.15 $2.50 GPT-4o Mini is 16.7x cheaper
Context Window (Max Output) 131k (16k out) 262k (66k out) Grok 4 (2.0x larger context)
Avg TTFT Response Latency 220ms 480ms GPT-4o Mini (260ms faster)
Generation Speed (Throughput) 140 tok/s 95 tok/s GPT-4o Mini (+45 tok/s faster)
SWE-bench Verified (Coding) 41% 73.2% Grok 4 (+32.2% lead)
GPQA Diamond (PhD STEM) 40.2% 86.2% Grok 4 (+46.0% lead)
MMLU-Pro (Multi-Discipline) 68% 89.9% Grok 4 (+21.9% lead)
MATH-500 (Quantitative Logic) 70.2% 97.6% Grok 4 (+27.4% lead)
Inference Value Score (IVR) 67.2 / 100 57.6 / 100 GPT-4o Mini (+9.6 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

GPT-4o Mini $5.81

$0.15/1M in · $0.60/1M out

Prompt Cache: $0.075/1M read · $0.15/1M write

Grok 4 $100.00

$2.50/1M in · $12.50/1M out

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

Projected Monthly Cost Reduction
$94.19 / mo
(94.2% lower cost with GPT-4o Mini)
Open Full Matchup Analysis →
A

When to Choose GPT-4o Mini

Choose GPT-4o Mini (OpenAI) for high-volume classification, lightweight RAG chatbots, and structured JSON extraction — offering a 131k context window, 220ms TTFT, and $0.15/1M input pricing ($0.075/1M cached reads).

B

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).

Related Questions & Decision Factors

Which is cheaper: GPT-4o Mini or Grok 4?

GPT-4o Mini is cheaper at $0.15/1M input tokens ($0.60/1M 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: GPT-4o Mini or Grok 4?

GPT-4o Mini delivers faster first-token latency at 220ms TTFT (140 tok/s throughput) compared to 480ms TTFT (95 tok/s) for Grok 4.

How do GPT-4o Mini and Grok 4 compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, GPT-4o Mini scores 41% versus 73.2% for Grok 4. On GPQA Diamond graduate-level STEM reasoning, GPT-4o Mini scores 40.2% versus 86.2% for Grok 4 (and 70.2% vs 97.6% on MATH-500).

When should you choose GPT-4o Mini?

Choose GPT-4o Mini (OpenAI) for high-volume classification, lightweight RAG chatbots, and structured JSON extraction — offering a 131k context window, 220ms TTFT, and $0.15/1M input pricing ($0.075/1M cached reads).

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).

Explore High-Priority Related Model Matchups