LLM Comparison

Qwen3.8 Flash Next vs GLM-5.2: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 Flash Next vs GLM-5.2 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 #25AskClash overall scores 57.6 vs 47.5.
Pricing $0.16/$0.47 vs $1.40/$4.40Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightAlibaba vs Z.AI.

Qwen3.8 Flash Next vs GLM-5.2 benchmark comparison

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

MetricQwen3.8 Flash NextGLM-5.2
Overall Score57.647.5
Leaderboard Rank#19#25
ACB66.5
RWT8.5
Coding Agent Index74.4
HLE35.954.7
GPQA91.791.2
IFEval81.373.3
SWE-Pro62.562.1
SWE-Atlas74.4
Terminal-Bench82.7
DeepSWE58.743.8
GDPval-AA1743.0
MCP Atlas76.8
Finance Agent49.7
CharXiv90.6
Tau299.1
Input Price (per 1M tokens)$0.16$1.40
Output Price (per 1M tokens)$0.47$4.40
Context Window1M1M
Benchmarks Published912

Qwen3.8 Flash Next vs GLM-5.2 head-to-head charts

Qwen3.8 Flash Next leads 5 and GLM-5.2 leads 1 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.

Qwen3.8 Flash NextGLM-5.2
Overall
57.6Qwen3.8 Flash Next
47.5GLM-5.2
HLE
35.9Qwen3.8 Flash Next
54.7GLM-5.2
GPQA
91.7Qwen3.8 Flash Next
91.2GLM-5.2
IFEval
81.3Qwen3.8 Flash Next
73.3GLM-5.2
SWE-Pro
62.5Qwen3.8 Flash Next
62.1GLM-5.2
DeepSWE
58.7Qwen3.8 Flash Next
43.8GLM-5.2
Qwen3.8 Flash Next
Input$0.16
Output$0.47
Workload$0.25
Context1M
GLM-5.2
Input$1.40
Output$4.40
Workload$2.28
Context1M

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

More Qwen3.8 Flash Next and GLM-5.2 comparisons

Explore how Qwen3.8 Flash Next and GLM-5.2 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.