LLM Comparison

Grok 4.6 vs DeepSeek V4 Flash 0731: benchmark scores, pricing & comparison.

Side-by-side Grok 4.6 vs DeepSeek V4 Flash 0731 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 #5 vs #20AskClash overall scores 76.6 vs 54.2.
Pricing $2.00/$6.00 vs $0.14/$0.28Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightxAI vs DeepSeek.

Grok 4.6 vs DeepSeek V4 Flash 0731 benchmark comparison

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

MetricGrok 4.6DeepSeek V4 Flash 0731
Overall Score76.654.2
Leaderboard Rank#5#20
RWT9.0
Coding Agent Index76.4
HLE40.337.0
GPQA94.991.0
MATH-50057.4
SWE-bench79.0
SWE-Pro64.7
SWE-Atlas83.9
Terminal-Bench88.482.7
DeepSWE65.954.4
MCP Atlas69.0
Finance Agent48.349.5
MMMU-Pro80.4
ARC-AGI 252.6
MRCR78.7
Input Price (per 1M tokens)$2.00$0.14
Output Price (per 1M tokens)$6.00$0.28
Context Window500K1M
Benchmarks Published1310

Grok 4.6 vs DeepSeek V4 Flash 0731 head-to-head charts

Grok 4.6 leads 5 and DeepSeek V4 Flash 0731 leads 1 of 6 shared benchmarks. DeepSeek V4 Flash 0731 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.6DeepSeek V4 Flash 0731
Overall
76.6Grok 4.6
54.2DeepSeek V4 Flash 0731
HLE
40.3Grok 4.6
37.0DeepSeek V4 Flash 0731
GPQA
94.9Grok 4.6
91.0DeepSeek V4 Flash 0731
Terminal-Bench
88.4Grok 4.6
82.7DeepSeek V4 Flash 0731
DeepSWE
65.9Grok 4.6
54.4DeepSeek V4 Flash 0731
Finance Agent
48.3Grok 4.6
49.5DeepSeek V4 Flash 0731
Grok 4.6
Input$2.00
Output$6.00
Workload$3.20
Context500K
DeepSeek V4 Flash 0731
Input$0.14
Output$0.28
Workload$0.20
Context1M

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

More Grok 4.6 and DeepSeek V4 Flash 0731 comparisons

Explore how Grok 4.6 and DeepSeek V4 Flash 0731 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.