LLM Comparison

Claude Opus 5 vs DeepSeek V4 Pro 0813: benchmark scores, pricing & comparison.

Side-by-side Claude Opus 5 vs DeepSeek V4 Pro 0813 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 #17AskClash overall scores 90.3 vs 60.5.
Pricing $5.00/$25.0 vs $0.43/$0.87Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightAnthropic vs DeepSeek.

Claude Opus 5 vs DeepSeek V4 Pro 0813 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 0813
Overall Score90.360.5
Leaderboard Rank#1#17
RWT9.07.0
HLE64.742.7
GPQA90.1
SWE-bench96.080.6
SWE-Pro79.255.4
Terminal-Bench87.9
DeepSWE73.662.7
MCP Atlas85.873.6
ARC-AGI 290.4
Input Price (per 1M tokens)$5.00$0.43
Output Price (per 1M tokens)$25.0$0.87
Context Window1M1M
Benchmarks Published89

Claude Opus 5 vs DeepSeek V4 Pro 0813 head-to-head charts

Claude Opus 5 leads 7 and DeepSeek V4 Pro 0813 leads 0 of 7 shared benchmarks. DeepSeek V4 Pro 0813 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Opus 5DeepSeek V4 Pro 0813
Overall
90.3Claude Opus 5
60.5DeepSeek V4 Pro 0813
RWT
9.0Claude Opus 5
7.0DeepSeek V4 Pro 0813
HLE
64.7Claude Opus 5
42.7DeepSeek V4 Pro 0813
SWE-bench
96.0Claude Opus 5
80.6DeepSeek V4 Pro 0813
SWE-Pro
79.2Claude Opus 5
55.4DeepSeek V4 Pro 0813
DeepSWE
73.6Claude Opus 5
62.7DeepSeek V4 Pro 0813
MCP Atlas
85.8Claude Opus 5
73.6DeepSeek V4 Pro 0813
Claude Opus 5
Input$5.00
Output$25.0
Workload$10
Context1M
DeepSeek V4 Pro 0813
Input$0.43
Output$0.87
Workload$0.61
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 0813 comparisons

Explore how Claude Opus 5 and DeepSeek V4 Pro 0813 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.