💰 Unit Cost Winner DeepSeek V3 $0.14/1M in · $0.28/1M out
⚡ Latency & Speed Winner DeepSeek V3 410ms TTFT · 78 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 DeepSeek V3?

DeepSeek V3 is 99.1% cheaper for input tokens ($0.14 vs. $15.00 per 1M tokens) and $0.28 vs. $75.00 for output tokens (107.1x cost advantage). In terms of operational performance, DeepSeek V3 delivers lower response latency at 410ms TTFT (510ms faster than Claude 4 Opus) with 78 vs. 46 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 87.1% vs. 59.1% 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 DeepSeek V3 Net Delta / Advantage
Input Cost / 1M Tokens $15.00 $0.14 DeepSeek V3 is 107.1x cheaper
Output Cost / 1M Tokens $75.00 $0.28 DeepSeek V3 (99.6% lower)
Prompt Cache Read / 1M $1.500 $0.014 DeepSeek V3 is 107.1x cheaper
Prompt Cache Write / 1M $18.75 $0.14 DeepSeek V3 is 133.9x cheaper
Context Window (Max Output) 205k (64k out) 131k (8k out) Claude 4 Opus (1.6x larger context)
Avg TTFT Response Latency 920ms 410ms DeepSeek V3 (510ms faster)
Generation Speed (Throughput) 46 tok/s 78 tok/s DeepSeek V3 (+32 tok/s faster)
SWE-bench Verified (Coding) 77.2% 42% Claude 4 Opus (+35.2% lead)
GPQA Diamond (PhD STEM) 87.1% 59.1% Claude 4 Opus (+28.0% lead)
MMLU-Pro (Multi-Discipline) 91.8% 75.9% Claude 4 Opus (+15.9% lead)
MATH-500 (Quantitative Logic) 98.1% 90.2% Claude 4 Opus (+7.9% lead)
Inference Value Score (IVR) 43.6 / 100 75 / 100 DeepSeek V3 (+31.4 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

DeepSeek V3 $3.33

$0.14/1M in · $0.28/1M out

Prompt Cache: $0.014/1M read · $0.14/1M write

Projected Monthly Cost Reduction
$577.93 / mo
(99.4% lower cost with DeepSeek V3)
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 DeepSeek V3

Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Claude 4 Opus or DeepSeek V3?

DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M 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 DeepSeek V3?

DeepSeek V3 delivers faster first-token latency at 410ms TTFT (78 tok/s throughput) compared to 920ms TTFT (46 tok/s) for Claude 4 Opus.

How do Claude 4 Opus and DeepSeek V3 compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Claude 4 Opus scores 77.2% versus 42% for DeepSeek V3. On GPQA Diamond graduate-level STEM reasoning, Claude 4 Opus scores 87.1% versus 59.1% for DeepSeek V3 (and 98.1% vs 90.2% 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 DeepSeek V3?

Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M cached reads).

Explore High-Priority Related Model Matchups