LLM Comparison

Qwen3.8 Flash Next vs Claude Opus 5.5: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Flash Next vs Claude Opus 5.5 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 #11 vs #12AskClash overall scores 65.1 vs 64.5.
Pricing $0.16/$0.47 vs $4.00/$20.0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryAlibaba vs Anthropic.

Qwen3.8 Flash Next vs Claude Opus 5.5 benchmark comparison

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

MetricQwen3.8 Flash NextClaude Opus 5.5
Overall Score65.164.5
Leaderboard Rank#11#12
ACB66.561.7
HLE35.967.7
GPQA91.7
IFEval81.3
SWE-Pro62.589.9
Terminal-Bench86.1
DeepSWE58.774.2
GDPval-AA1743.01846.2
CharXiv90.6
MMMU-Pro79.887.7
Input Price (per 1M tokens)$0.16$4.00
Output Price (per 1M tokens)$0.47$20.0
Context Window1M1M
Benchmarks Published117

Qwen3.8 Flash Next vs Claude Opus 5.5 head-to-head charts

Qwen3.8 Flash Next leads 2 and Claude Opus 5.5 leads 5 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.

Qwen3.8 Flash NextClaude Opus 5.5
Overall
65.1Qwen3.8 Flash Next
64.5Claude Opus 5.5
ACB
66.5Qwen3.8 Flash Next
61.7Claude Opus 5.5
HLE
35.9Qwen3.8 Flash Next
67.7Claude Opus 5.5
SWE-Pro
62.5Qwen3.8 Flash Next
89.9Claude Opus 5.5
DeepSWE
58.7Qwen3.8 Flash Next
74.2Claude Opus 5.5
GDPval-AA
1743.0Qwen3.8 Flash Next
1846.2Claude Opus 5.5
MMMU-Pro
79.8Qwen3.8 Flash Next
87.7Claude Opus 5.5
Qwen3.8 Flash Next
Input$0.16
Output$0.47
Workload$0.25
Context1M
Claude Opus 5.5
Input$4.00
Output$20.0
Workload$8.00
Context1M

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

More Qwen3.8 Flash Next and Claude Opus 5.5 comparisons

Explore how Qwen3.8 Flash Next and Claude Opus 5.5 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.