💰 Unit Cost Winner OpenAI o3 $2.00/1M in · $8.00/1M out
⚡ Latency & Speed Winner GPT-4o 280ms TTFT · 100 tok/s
💻 Coding (SWE) Winner OpenAI o3 71.7% SWE-bench · 95.2% HumanEval
🧠 STEM Reasoning Winner OpenAI o3 87.7% GPQA · 98.6% MATH-500

Which model is better: GPT-4o or OpenAI o3?

OpenAI o3 is 20.0% cheaper for input tokens ($2.00 vs. $2.50 per 1M tokens) and $8.00 vs. $10.00 for output tokens (1.2x cost advantage). In terms of operational performance, GPT-4o delivers lower response latency at 280ms TTFT (870ms faster than OpenAI o3) with 100 vs. 82 tok/s throughput. OpenAI o3 leads coding evaluations at 71.7% SWE-bench Verified vs. 48.0% for GPT-4o and 87.7% vs. 53.6% 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 OpenAI o3 Net Delta / Advantage
Input Cost / 1M Tokens $2.50 $2.00 OpenAI o3 is 1.3x cheaper
Output Cost / 1M Tokens $10.00 $8.00 OpenAI o3 (20.0% lower)
Prompt Cache Read / 1M $1.250 $0.500 OpenAI o3 is 2.5x cheaper
Prompt Cache Write / 1M $2.50 $2.00 OpenAI o3 is 1.3x cheaper
Context Window (Max Output) 131k (16k out) 205k (100k out) OpenAI o3 (1.6x larger context)
Avg TTFT Response Latency 280ms 1150ms GPT-4o (870ms faster)
Generation Speed (Throughput) 100 tok/s 82 tok/s GPT-4o (+18 tok/s faster)
SWE-bench Verified (Coding) 48% 71.7% OpenAI o3 (+23.7% lead)
GPQA Diamond (PhD STEM) 53.6% 87.7% OpenAI o3 (+34.1% lead)
MMLU-Pro (Multi-Discipline) 75.9% 89.8% OpenAI o3 (+13.9% lead)
MATH-500 (Quantitative Logic) 76.6% 98.6% OpenAI o3 (+22.0% lead)
Inference Value Score (IVR) 47.6 / 100 60.6 / 100 OpenAI o3 (+13 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 $96.88

$2.50/1M in · $10.00/1M out

Prompt Cache: $1.250/1M 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
$25.63 / mo
(26.5% lower cost with OpenAI o3)
Open Full Matchup Analysis →
A

When to Choose GPT-4o

Choose GPT-4o (OpenAI) for general enterprise assistants, multimodal customer support, and structured JSON output pipelines — offering a 131k context window, 280ms TTFT, and $2.50/1M input pricing ($1.250/1M 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: GPT-4o or OpenAI o3?

OpenAI o3 is cheaper at $2.00/1M input tokens ($8.00/1M output) compared to $2.50/1M input ($10.00/1M output) for GPT-4o.

Which model has lower TTFT latency and higher tok/s throughput: GPT-4o or OpenAI o3?

GPT-4o delivers faster first-token latency at 280ms TTFT (100 tok/s throughput) compared to 1150ms TTFT (82 tok/s) for OpenAI o3.

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

On SWE-bench Verified software engineering, GPT-4o scores 48% versus 71.7% for OpenAI o3. On GPQA Diamond graduate-level STEM reasoning, GPT-4o scores 53.6% versus 87.7% for OpenAI o3 (and 76.6% vs 98.6% on MATH-500).

When should you choose GPT-4o?

Choose GPT-4o (OpenAI) for general enterprise assistants, multimodal customer support, and structured JSON output pipelines — offering a 131k context window, 280ms TTFT, and $2.50/1M input pricing ($1.250/1M 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).

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