💰 Unit Cost Winner GPT-4o $2.50/1M in · $10.00/1M out
⚡ Latency & Speed Winner GPT-4o 280ms TTFT · 100 tok/s
💻 Coding (SWE) Winner Claude 4 Opus 77.2% SWE-bench · 96.8% HumanEval
🧠 STEM Reasoning Winner Claude 4 Opus 87.1% GPQA · 98.1% MATH-500

Which model is better: Claude 4 Opus or GPT-4o?

GPT-4o is 83.3% cheaper for input tokens ($2.50 vs. $15.00 per 1M tokens) and $10.00 vs. $75.00 for output tokens (6.0x cost advantage). In terms of operational performance, GPT-4o delivers lower response latency at 280ms TTFT (640ms faster than Claude 4 Opus) with 100 vs. 46 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 48.0% for GPT-4o and 87.1% 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 Claude 4 Opus GPT-4o Net Delta / Advantage
Input Cost / 1M Tokens $15.00 $2.50 GPT-4o is 6.0x cheaper
Output Cost / 1M Tokens $75.00 $10.00 GPT-4o (86.7% lower)
Prompt Cache Read / 1M $1.500 $1.250 GPT-4o is 1.2x cheaper
Prompt Cache Write / 1M $18.75 $2.50 GPT-4o is 7.5x cheaper
Context Window (Max Output) 205k (64k out) 131k (16k out) Claude 4 Opus (1.6x larger context)
Avg TTFT Response Latency 920ms 280ms GPT-4o (640ms faster)
Generation Speed (Throughput) 46 tok/s 100 tok/s GPT-4o (+54 tok/s faster)
SWE-bench Verified (Coding) 77.2% 48% Claude 4 Opus (+29.2% lead)
GPQA Diamond (PhD STEM) 87.1% 53.6% Claude 4 Opus (+33.5% lead)
MMLU-Pro (Multi-Discipline) 91.8% 75.9% Claude 4 Opus (+15.9% lead)
MATH-500 (Quantitative Logic) 98.1% 76.6% Claude 4 Opus (+21.5% lead)
Inference Value Score (IVR) 43.6 / 100 47.6 / 100 GPT-4o (+4 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

Claude 4 Opus $581.25

$15.00/1M in · $75.00/1M out

Prompt Cache: $1.500/1M read · $18.75/1M write

GPT-4o $96.88

$2.50/1M in · $10.00/1M out

Prompt Cache: $1.250/1M read · $2.50/1M write

Projected Monthly Cost Reduction
$484.38 / mo
(83.3% lower cost with GPT-4o)
Open Full Matchup Analysis →
A

When to Choose Claude 4 Opus

Choose Claude 4 Opus (Anthropic) for mission-critical R&D, long-horizon autonomous coding tasks, complex theorem proving, and executive strategic synthesis — offering a 204k context window, 920ms TTFT, and $15.00/1M input pricing ($1.500/1M cached reads).

B

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).

Related Questions & Decision Factors

Which is cheaper: Claude 4 Opus or GPT-4o?

GPT-4o is cheaper at $2.50/1M input tokens ($10.00/1M output) compared to $15.00/1M input ($75.00/1M output) for Claude 4 Opus.

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

GPT-4o delivers faster first-token latency at 280ms TTFT (100 tok/s throughput) compared to 920ms TTFT (46 tok/s) for Claude 4 Opus.

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

On SWE-bench Verified software engineering, Claude 4 Opus scores 77.2% versus 48% for GPT-4o. On GPQA Diamond graduate-level STEM reasoning, Claude 4 Opus scores 87.1% versus 53.6% for GPT-4o (and 98.1% vs 76.6% on MATH-500).

When should you choose Claude 4 Opus?

Choose Claude 4 Opus (Anthropic) for mission-critical R&D, long-horizon autonomous coding tasks, complex theorem proving, and executive strategic synthesis — offering a 204k context window, 920ms TTFT, and $15.00/1M input pricing ($1.500/1M cached reads).

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).

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