LLM Comparison

Qwen3.8 Flash Next vs Qwen3.8 27B: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Flash Next vs Qwen3.8 27B 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 #19 vs #26AskClash overall scores 57.6 vs 47.5.
Pricing $0.16/$0.47 vs $0.45/$3.20Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightAlibaba vs Alibaba.

Qwen3.8 Flash Next vs Qwen3.8 27B benchmark comparison

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

MetricQwen3.8 Flash NextQwen3.8 27B
Overall Score57.647.5
Leaderboard Rank#19#26
ACB66.556.4
HLE35.930.8
GPQA91.789.2
IFEval81.379.5
SWE-Pro62.561.7
Terminal-Bench73.0
DeepSWE58.742.2
GDPval-AA1743.0
OSWorld84.3
Finance Agent48.6
CharXiv90.690.2
Input Price (per 1M tokens)$0.16$0.45
Output Price (per 1M tokens)$0.47$3.20
Context Window1M262K
Benchmarks Published910

Qwen3.8 Flash Next vs Qwen3.8 27B head-to-head charts

Qwen3.8 Flash Next leads 8 and Qwen3.8 27B leads 0 of 8 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 NextQwen3.8 27B
Overall
57.6Qwen3.8 Flash Next
47.5Qwen3.8 27B
ACB
66.5Qwen3.8 Flash Next
56.4Qwen3.8 27B
HLE
35.9Qwen3.8 Flash Next
30.8Qwen3.8 27B
GPQA
91.7Qwen3.8 Flash Next
89.2Qwen3.8 27B
IFEval
81.3Qwen3.8 Flash Next
79.5Qwen3.8 27B
SWE-Pro
62.5Qwen3.8 Flash Next
61.7Qwen3.8 27B
DeepSWE
58.7Qwen3.8 Flash Next
42.2Qwen3.8 27B
CharXiv
90.6Qwen3.8 Flash Next
90.2Qwen3.8 27B
Qwen3.8 Flash Next
Input$0.16
Output$0.47
Workload$0.25
Context1M
Qwen3.8 27B
Input$0.45
Output$3.20
Workload$1.09
Context262K

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

More Qwen3.8 Flash Next and Qwen3.8 27B comparisons

Explore how Qwen3.8 Flash Next and Qwen3.8 27B 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.