Benchmark scores
Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.
LLM Comparison
Grok 4.7 vs Qwen3.8 Flash Next: benchmark scores, pricing & comparison.
Side-by-side Grok 4.7 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.
Verdict: Grok 4.7 ranks higher (#22 vs #23) and wins 3 of 5 shared benchmarks; Qwen3.8 Flash Next costs less ($0.16/$0.47 vs $2.00/$6.00 per 1M tokens).
Rank #22 vs #23AskClash overall scores 56.9 vs 56.4.
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 4.7 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.
| Metric | Grok 4.7 | Qwen3.8 Flash Next |
|---|---|---|
| Overall Score | 56.9 | 56.4 |
| Leaderboard Rank | #22 | #23 |
| ACB | 66.4 | 66.5 |
| Coding Agent Index | 56.0 | — |
| HLE | 43.1 | 35.9 |
| GPQA | — | 91.7 |
| IFEval | — | 81.3 |
| SWE-Pro | — | 62.5 |
| SWE-Atlas | 63.0 | — |
| Terminal-Bench | 25.8 | 25.2 |
| DeepSWE | 73.0 | 58.7 |
| GDPval-AA | 1695.2 | 1743.0 |
| Finance Agent | 49.2 | — |
| CharXiv | — | 90.6 |
| MMMU-Pro | — | 79.8 |
| Input Price (per 1M tokens) | $2.00 | $0.16 |
| Output Price (per 1M tokens) | $6.00 | $0.47 |
| Context Window | 500K | 1M |
| Benchmarks Published | 11 | 12 |
Grok 4.7 vs Qwen3.8 Flash Next head-to-head charts
Grok 4.7 leads 4 and Qwen3.8 Flash Next leads 2 of 6 shared benchmarks. Qwen3.8 Flash Next is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.
Grok 4.7Qwen3.8 Flash Next
Overall
ACB
HLE
Terminal-Bench
DeepSWE
GDPval-AA
Grok 4.7
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.
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How to read this comparison
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.