💰 Unit Cost Winner Claude 4 Opus $15.00/1M in · $75.00/1M out
⚡ Latency & Speed Winner Claude 4 Opus 920ms TTFT · 46 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 o1?

Claude 4 Opus and o1 share identical input pricing at $15.00 per 1M tokens ($75.00 vs. $60.00 output). In terms of operational performance, Claude 4 Opus delivers lower response latency at 920ms TTFT (1680ms faster than o1) with 46 vs. 48 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 48.9% for o1 and 87.1% vs. 78.0% 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 o1 Net Delta / Advantage
Input Cost / 1M Tokens $15.00 $15.00 Identical Pricing
Output Cost / 1M Tokens $75.00 $60.00 o1 (20.0% lower)
Prompt Cache Read / 1M $1.500 $7.500 Claude 4 Opus is 5.0x cheaper
Prompt Cache Write / 1M $18.75 $15.00 o1 is 1.3x cheaper
Context Window (Max Output) 205k (64k out) 205k (100k out) Equal Context Window
Avg TTFT Response Latency 920ms 2600ms Claude 4 Opus (1680ms faster)
Generation Speed (Throughput) 46 tok/s 48 tok/s o1 (+2 tok/s faster)
SWE-bench Verified (Coding) 77.2% 48.9% Claude 4 Opus (+28.3% lead)
GPQA Diamond (PhD STEM) 87.1% 78% Claude 4 Opus (+9.1% lead)
MMLU-Pro (Multi-Discipline) 91.8% 83.3% Claude 4 Opus (+8.5% lead)
MATH-500 (Quantitative Logic) 98.1% 96.4% Claude 4 Opus (+1.7% lead)
Inference Value Score (IVR) 43.6 / 100 37.2 / 100 Claude 4 Opus (+6.4 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

o1 $581.25

$15.00/1M in · $60.00/1M out

Prompt Cache: $7.500/1M read · $15.00/1M write

Projected Monthly Cost Reduction
$0.00 / mo
(Identical monthly cost)
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 o1

Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Claude 4 Opus or o1?

Both Claude 4 Opus and o1 share identical input pricing at $15.00/1M tokens.

Which model has lower TTFT latency and higher tok/s throughput: Claude 4 Opus or o1?

Claude 4 Opus delivers faster first-token latency at 920ms TTFT (46 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.

How do Claude 4 Opus and o1 compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Claude 4 Opus scores 77.2% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, Claude 4 Opus scores 87.1% versus 78% for o1 (and 98.1% vs 96.4% 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 o1?

Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).

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