LLM Comparison

Qwen3.8 Flash Next vs GPT-6.1 Sol: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Flash Next vs GPT-6.1 Sol 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: Qwen3.8 Flash Next ranks higher (#20 vs #30); Qwen3.8 Flash Next costs less ($0.16/$0.47 vs $2.00/$10.0 per 1M tokens).

Rank #20 vs #30AskClash overall scores 63.3 vs 58.1.
Pricing $0.16/$0.47 vs $2.00/$10.0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryAlibaba vs OpenAI.

Qwen3.8 Flash Next vs GPT-6.1 Sol benchmark comparison

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

MetricQwen3.8 Flash NextGPT-6.1 Sol
Overall Score63.358.1
Leaderboard Rank#20#30
ACB66.561.9
HLE35.9—
GPQA91.7—
IFEval81.3—
SWE-Pro62.5—
Terminal-Bench86.1—
DeepSWE58.775.2
GDPval-AA1743.0—
CharXiv90.6—
MMMU-Pro79.8—
Input Price (per 1M tokens)$0.16$2.00
Output Price (per 1M tokens)$0.47$10.0
Context Window1M1.05M
Benchmarks Published123

Qwen3.8 Flash Next vs GPT-6.1 Sol head-to-head charts

Qwen3.8 Flash Next leads 2 and GPT-6.1 Sol leads 1 of 3 shared benchmarks. Qwen3.8 Flash Next is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 Flash NextGPT-6.1 Sol
Overall
63.3Qwen3.8 Flash Next
58.1GPT-6.1 Sol
ACB
66.5Qwen3.8 Flash Next
61.9GPT-6.1 Sol
DeepSWE
58.7Qwen3.8 Flash Next
75.2GPT-6.1 Sol
Qwen3.8 Flash Next
Input$0.16
Output$0.47
Workload$0.25
Context1M
GPT-6.1 Sol
Input$2.00
Output$10.0
Workload$4.00
Context1.05M

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

More Qwen3.8 Flash Next and GPT-6.1 Sol comparisons

Explore how Qwen3.8 Flash Next and GPT-6.1 Sol 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.