LLM Comparison

Composer 2.5 vs DeepSeek V4 Pro 0813: benchmark scores, pricing & comparison.

Side-by-side Composer 2.5 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 #13 vs #17AskClash overall scores 67.0 vs 60.5.
Pricing $0.50/$2.50 vs $0.43/$0.87Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightCursor vs DeepSeek.

Composer 2.5 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.

MetricComposer 2.5DeepSeek V4 Pro 0813
Overall Score67.060.5
Leaderboard Rank#13#17
RWT8.57.0
Coding Agent Index38.2
HLE42.7
GPQA90.1
SWE-bench80.6
SWE-Pro47.055.4
SWE-Atlas72.0
Terminal-Bench69.387.9
DeepSWE62.7
MCP Atlas73.6
Input Price (per 1M tokens)$0.50$0.43
Output Price (per 1M tokens)$2.50$0.87
Context Window200K1M
Benchmarks Published59

Composer 2.5 vs DeepSeek V4 Pro 0813 head-to-head charts

Composer 2.5 leads 2 and DeepSeek V4 Pro 0813 leads 2 of 4 shared benchmarks. DeepSeek V4 Pro 0813 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Composer 2.5DeepSeek V4 Pro 0813
Overall
67.0Composer 2.5
60.5DeepSeek V4 Pro 0813
RWT
8.5Composer 2.5
7.0DeepSeek V4 Pro 0813
SWE-Pro
47.0Composer 2.5
55.4DeepSeek V4 Pro 0813
Terminal-Bench
69.3Composer 2.5
87.9DeepSeek V4 Pro 0813
Composer 2.5
Input$0.50
Output$2.50
Workload$1.00
Context200K
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 Composer 2.5 and DeepSeek V4 Pro 0813 comparisons

Explore how Composer 2.5 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.