LLM Comparison

Claude Opus 5 vs DeepSeek V4 Pro: benchmark scores, pricing & comparison.

Side-by-side Claude Opus 5 vs DeepSeek V4 Pro comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Rank #1 vs #53AskClash overall scores 94.2 vs 20.7.
Pricing $5.00/$25.0 vs $1.74/$3.48Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightAnthropic vs DeepSeek.

Claude Opus 5 vs DeepSeek V4 Pro benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricClaude Opus 5DeepSeek V4 Pro
Overall Score94.220.7
Leaderboard Rank#1#53
RWT9.07.0
HLE64.77.7
GPQA72.9
MATH-50064.5
SWE-bench96.073.6
SWE-Pro79.252.1
Terminal-Bench59.1
DeepSWE68.8
MCP Atlas85.869.4
Finance Agent44.1
ARC-AGI 290.4
MRCR44.7
Input Price (per 1M tokens)$5.00$1.74
Output Price (per 1M tokens)$25.0$3.48
Context Window1M1M
Benchmarks Published88

Claude Opus 5 vs DeepSeek V4 Pro head-to-head charts

Claude Opus 5 leads 6 and DeepSeek V4 Pro leads 0 of 6 shared benchmarks. DeepSeek V4 Pro is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Opus 5DeepSeek V4 Pro
Overall
94.2Claude Opus 5
20.7DeepSeek V4 Pro
RWT
9.0Claude Opus 5
7.0DeepSeek V4 Pro
HLE
64.7Claude Opus 5
7.7DeepSeek V4 Pro
SWE-bench
96.0Claude Opus 5
73.6DeepSeek V4 Pro
SWE-Pro
79.2Claude Opus 5
52.1DeepSeek V4 Pro
MCP Atlas
85.8Claude Opus 5
69.4DeepSeek V4 Pro
Claude Opus 5
Input$5.00
Output$25.0
Workload$10
Context1M
DeepSeek V4 Pro
Input$1.74
Output$3.48
Workload$2.44
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More Claude Opus 5 and DeepSeek V4 Pro comparisons

Explore how Claude Opus 5 and DeepSeek V4 Pro stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.