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
GPT-6 Sol vs Qwen3.8 Flash Next: benchmark scores, pricing & comparison.
Side-by-side GPT-6 Sol 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: GPT-6 Sol ranks higher (#20 vs #23) and wins 4 of 6 shared benchmarks; Qwen3.8 Flash Next costs less ($0.16/$0.47 vs $2.00/$10.0 per 1M tokens).
Rank #20 vs #23AskClash overall scores 59.3 vs 57.0.
Pricing $2.00/$10.0 vs $0.16/$0.47Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightOpenAI vs Alibaba.
GPT-6 Sol 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 | GPT-6 Sol | Qwen3.8 Flash Next |
|---|---|---|
| Overall Score | 59.3 | 57.0 |
| Leaderboard Rank | #20 | #23 |
| ACB | 55.8 | 66.5 |
| Coding Agent Index | 56.7 | — |
| HLE | 47.9 | 35.9 |
| GPQA | — | 91.7 |
| IFEval | — | 81.3 |
| SWE-Pro | — | 62.5 |
| SWE-Atlas | 57.5 | — |
| Terminal-Bench | 43.9 | 25.2 |
| DeepSWE | 68.8 | 58.7 |
| GDPval-AA | 1509.9 | 1743.0 |
| Finance Agent | 49.0 | — |
| CharXiv | — | 90.6 |
| MMMU-Pro | 82.9 | 79.8 |
| ARC-AGI 2 | 89.6 | — |
| Input Price (per 1M tokens) | $2.00 | $0.16 |
| Output Price (per 1M tokens) | $10.0 | $0.47 |
| Context Window | 1.05M | 1M |
| Benchmarks Published | 13 | 12 |
GPT-6 Sol vs Qwen3.8 Flash Next head-to-head charts
GPT-6 Sol leads 5 and Qwen3.8 Flash Next leads 2 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.
GPT-6 SolQwen3.8 Flash Next
Overall
ACB
HLE
Terminal-Bench
DeepSWE
GDPval-AA
MMMU-Pro
GPT-6 Sol
Input$2.00
Output$10.0
Workload$4.00
Context1.05M
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 GPT-6 Sol and Qwen3.8 Flash Next comparisons
Explore how GPT-6 Sol and Qwen3.8 Flash Next stack up against other top-ranked LLMs.
Claude Opus 5.5 vs GPT-6 SolClaude Opus 5.5 vs Qwen3.8 Flash NextClaude Fable 5.1 vs GPT-6 SolClaude Fable 5.1 vs Qwen3.8 Flash NextClaude Opus 5 vs GPT-6 SolClaude Opus 5 vs Qwen3.8 Flash NextClaude Sonnet 5.5 vs GPT-6 SolClaude Sonnet 5.5 vs Qwen3.8 Flash NextClaude Fable 5 vs GPT-6 SolClaude Fable 5 vs Qwen3.8 Flash Next
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.