LLM Comparison

Kimi K3 vs Qwen3.8 Flash Next: benchmark scores, pricing & comparison.

Side-by-side Kimi K3 vs Qwen3.8 Flash Next 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 #7 vs #19AskClash overall scores 74.6 vs 57.6.
Pricing $3.00/$15.0 vs $0.16/$0.47Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightMoonshot AI vs Alibaba.

Kimi K3 vs Qwen3.8 Flash Next benchmark comparison

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

MetricKimi K3Qwen3.8 Flash Next
Overall Score74.657.6
Leaderboard Rank#7#19
ACB57.766.5
RWT8.0
HLE43.535.9
GPQA93.591.7
IFEval81.3
SWE-Pro62.5
Terminal-Bench88.3
DeepSWE68.558.7
GDPval-AA1668.01743.0
MCP Atlas84.2
Finance Agent54.4
CharXiv84.890.6
MMMU-Pro81.6
Input Price (per 1M tokens)$3.00$0.16
Output Price (per 1M tokens)$15.0$0.47
Context Window1M1M
Benchmarks Published119

Kimi K3 vs Qwen3.8 Flash Next head-to-head charts

Kimi K3 leads 4 and Qwen3.8 Flash Next leads 3 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.

Kimi K3Qwen3.8 Flash Next
Overall
74.6Kimi K3
57.6Qwen3.8 Flash Next
ACB
57.7Kimi K3
66.5Qwen3.8 Flash Next
HLE
43.5Kimi K3
35.9Qwen3.8 Flash Next
GPQA
93.5Kimi K3
91.7Qwen3.8 Flash Next
DeepSWE
68.5Kimi K3
58.7Qwen3.8 Flash Next
GDPval-AA
1668.0Kimi K3
1743.0Qwen3.8 Flash Next
CharXiv
84.8Kimi K3
90.6Qwen3.8 Flash Next
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M
Qwen3.8 Flash Next
Input$0.16
Output$0.47
Workload$0.25
Context1M

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

More Kimi K3 and Qwen3.8 Flash Next comparisons

Explore how Kimi K3 and Qwen3.8 Flash Next 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.