LLM Comparison

Grok 4.6 vs Qwen3.8 Flash Next: benchmark scores, pricing & comparison.

Side-by-side Grok 4.6 vs Qwen3.8 Flash Next 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 #19AskClash overall scores 75.9 vs 57.6.
Pricing $2.00/$6.00 vs $0.16/$0.47Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightxAI vs Alibaba.

Grok 4.6 vs Qwen3.8 Flash Next benchmark comparison

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

MetricGrok 4.6Qwen3.8 Flash Next
Overall Score75.957.6
Leaderboard Rank#5#19
ACB69.066.5
RWT9.0
Coding Agent Index76.4
HLE40.335.9
GPQA94.991.7
IFEval81.3
SWE-Pro64.762.5
SWE-Atlas83.9
Terminal-Bench88.4
DeepSWE65.958.7
GDPval-AA1753.01743.0
Finance Agent53.7
CharXiv90.6
MMMU-Pro80.4
ARC-AGI 252.6
Input Price (per 1M tokens)$2.00$0.16
Output Price (per 1M tokens)$6.00$0.47
Context Window500K1M
Benchmarks Published139

Grok 4.6 vs Qwen3.8 Flash Next head-to-head charts

Grok 4.6 leads 7 and Qwen3.8 Flash Next leads 0 of 7 shared benchmarks. Qwen3.8 Flash Next is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.6Qwen3.8 Flash Next
Overall
75.9Grok 4.6
57.6Qwen3.8 Flash Next
ACB
69.0Grok 4.6
66.5Qwen3.8 Flash Next
HLE
40.3Grok 4.6
35.9Qwen3.8 Flash Next
GPQA
94.9Grok 4.6
91.7Qwen3.8 Flash Next
SWE-Pro
64.7Grok 4.6
62.5Qwen3.8 Flash Next
DeepSWE
65.9Grok 4.6
58.7Qwen3.8 Flash Next
GDPval-AA
1753.0Grok 4.6
1743.0Qwen3.8 Flash Next
Grok 4.6
Input$2.00
Output$6.00
Workload$3.20
Context500K
Qwen3.8 Flash Next
Input$0.16
Output$0.47
Workload$0.25
Context1M

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

More Grok 4.6 and Qwen3.8 Flash Next comparisons

Explore how Grok 4.6 and Qwen3.8 Flash Next 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.