💰 Unit Cost Winner OpenAI o3 $2.00/1M in · $8.00/1M 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 OpenAI o3 87.7% GPQA · 98.6% MATH-500

Which model is better: Grok 4 or OpenAI o3?

OpenAI o3 is 20.0% cheaper for input tokens ($2.00 vs. $2.50 per 1M tokens) and $8.00 vs. $12.50 for output tokens (1.2x cost advantage). In terms of operational performance, Grok 4 delivers lower response latency at 480ms TTFT (670ms faster than OpenAI o3) with 95 vs. 82 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 71.7% for OpenAI o3 and 86.2% vs. 87.7% 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 Net Delta / Advantage
Input Cost / 1M Tokens $2.50 $2.00 OpenAI o3 is 1.3x cheaper
Output Cost / 1M Tokens $12.50 $8.00 OpenAI o3 (36.0% lower)
Prompt Cache Read / 1M $0.500 $0.500 Identical Cache Read Pricing
Prompt Cache Write / 1M $2.50 $2.00 OpenAI o3 is 1.3x cheaper
Context Window (Max Output) 262k (66k out) 205k (100k out) Grok 4 (1.3x larger context)
Avg TTFT Response Latency 480ms 1150ms Grok 4 (670ms faster)
Generation Speed (Throughput) 95 tok/s 82 tok/s Grok 4 (+13 tok/s faster)
SWE-bench Verified (Coding) 73.2% 71.7% Grok 4 (+1.5% lead)
GPQA Diamond (PhD STEM) 86.2% 87.7% OpenAI o3 (+1.5% lead)
MMLU-Pro (Multi-Discipline) 89.9% 89.8% Grok 4 (+0.1% lead)
MATH-500 (Quantitative Logic) 97.6% 98.6% OpenAI o3 (+1.0% lead)
Inference Value Score (IVR) 57.6 / 100 60.6 / 100 OpenAI o3 (+3 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 $71.25

$2.00/1M in · $8.00/1M out

Prompt Cache: $0.500/1M read · $2.00/1M write

Projected Monthly Cost Reduction
$28.75 / mo
(28.7% lower cost with OpenAI o3)
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

Choose OpenAI o3 (OpenAI) for algorithmic synthesis, mathematical verification, PhD-level scientific research, and multi-step tool planning — offering a 204k context window, 1150ms TTFT, and $2.00/1M input pricing ($0.500/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Grok 4 or OpenAI o3?

OpenAI o3 is cheaper at $2.00/1M input tokens ($8.00/1M 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?

Grok 4 delivers faster first-token latency at 480ms TTFT (95 tok/s throughput) compared to 1150ms TTFT (82 tok/s) for OpenAI o3.

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

On SWE-bench Verified software engineering, Grok 4 scores 73.2% versus 71.7% for OpenAI o3. On GPQA Diamond graduate-level STEM reasoning, Grok 4 scores 86.2% versus 87.7% for OpenAI o3 (and 97.6% vs 98.6% 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?

Choose OpenAI o3 (OpenAI) for algorithmic synthesis, mathematical verification, PhD-level scientific research, and multi-step tool planning — offering a 204k context window, 1150ms TTFT, and $2.00/1M input pricing ($0.500/1M cached reads).

Explore High-Priority Related Model Matchups