LLM Comparison

Grok 4.5 vs DeepSeek V4 Pro 0813: benchmark scores, pricing & comparison.

Side-by-side Grok 4.5 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 #11 vs #17AskClash overall scores 69.7 vs 60.5.
Pricing $2.00/$6.00 vs $0.43/$0.87Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightxAI vs DeepSeek.

Grok 4.5 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.

MetricGrok 4.5DeepSeek V4 Pro 0813
Overall Score69.760.5
Leaderboard Rank#11#17
RWT9.07.0
Coding Agent Index76.4
HLE40.342.7
GPQA93.190.1
SWE-bench80.6
SWE-Pro64.755.4
SWE-Atlas83.9
Terminal-Bench83.387.9
DeepSWE62.7
MCP Atlas73.6
Finance Agent48.3
MMMU-Pro80.4
ARC-AGI 252.6
Input Price (per 1M tokens)$2.00$0.43
Output Price (per 1M tokens)$6.00$0.87
Context Window500K1M
Benchmarks Published129

Grok 4.5 vs DeepSeek V4 Pro 0813 head-to-head charts

Grok 4.5 leads 4 and DeepSeek V4 Pro 0813 leads 2 of 6 shared benchmarks. DeepSeek V4 Pro 0813 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.5DeepSeek V4 Pro 0813
Overall
69.7Grok 4.5
60.5DeepSeek V4 Pro 0813
RWT
9.0Grok 4.5
7.0DeepSeek V4 Pro 0813
HLE
40.3Grok 4.5
42.7DeepSeek V4 Pro 0813
GPQA
93.1Grok 4.5
90.1DeepSeek V4 Pro 0813
SWE-Pro
64.7Grok 4.5
55.4DeepSeek V4 Pro 0813
Terminal-Bench
83.3Grok 4.5
87.9DeepSeek V4 Pro 0813
Grok 4.5
Input$2.00
Output$6.00
Workload$3.20
Context500K
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 Grok 4.5 and DeepSeek V4 Pro 0813 comparisons

Explore how Grok 4.5 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.