LLM Comparison

DeepSeek V4.1 Flash vs GLM-5.3: benchmark scores, pricing & comparison.

Side-by-side DeepSeek V4.1 Flash vs GLM-5.3 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 #14 vs #15AskClash overall scores 68.3 vs 68.3.
Pricing $0.15/$0.60 vs $1.40/$4.40Input and output token prices per 1M tokens when published.
API vs Open WeightDeepSeek vs Z.AI.

DeepSeek V4.1 Flash vs GLM-5.3 benchmark comparison

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

MetricDeepSeek V4.1 FlashGLM-5.3
Overall Score68.368.3
Leaderboard Rank#14#15
ACB63.062.2
RWT8.5
HLE36.862.5
GPQA90.991.7
Terminal-Bench90.688.2
DeepSWE74.269.0
GDPval-AA1600.01769.0
Finance Agent53.555.8
MMMU-Pro77.0
Input Price (per 1M tokens)$0.15$1.40
Output Price (per 1M tokens)$0.60$4.40
Context Window1M1M
Benchmarks Published1110

DeepSeek V4.1 Flash vs GLM-5.3 head-to-head charts

DeepSeek V4.1 Flash leads 4 and GLM-5.3 leads 4 of 8 shared benchmarks. DeepSeek V4.1 Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

DeepSeek V4.1 FlashGLM-5.3
Overall
68.3DeepSeek V4.1 Flash
68.3GLM-5.3
ACB
63.0DeepSeek V4.1 Flash
62.2GLM-5.3
HLE
36.8DeepSeek V4.1 Flash
62.5GLM-5.3
GPQA
90.9DeepSeek V4.1 Flash
91.7GLM-5.3
Terminal-Bench
90.6DeepSeek V4.1 Flash
88.2GLM-5.3
DeepSWE
74.2DeepSeek V4.1 Flash
69.0GLM-5.3
GDPval-AA
1600.0DeepSeek V4.1 Flash
1769.0GLM-5.3
Finance Agent
53.5DeepSeek V4.1 Flash
55.8GLM-5.3
DeepSeek V4.1 Flash
Input$0.15
Output$0.60
Workload$0.27
Context1M
GLM-5.3
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 DeepSeek V4.1 Flash and GLM-5.3 comparisons

Explore how DeepSeek V4.1 Flash and GLM-5.3 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.