LLM Comparison

Gemini 3.8 Flash vs Kimi K3: benchmark scores, pricing & comparison.

Side-by-side Gemini 3.8 Flash vs Kimi K3 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 #8 vs #9AskClash overall scores 63.3 vs 62.8.
Pricing $1.50/$7.50 vs $3.00/$15.0Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightGoogle vs Moonshot AI.

Gemini 3.8 Flash vs Kimi K3 benchmark comparison

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

MetricGemini 3.8 FlashKimi K3
Overall Score63.362.8
Leaderboard Rank#8#9
ACB61.157.7
RWT8.0
HLE54.943.5
GPQA93.5
Terminal-Bench89.488.3
DeepSWE73.868.5
GDPval-AA1545.01668.0
MCP Atlas84.2
Finance Agent61.454.4
CharXiv86.284.8
MMMU-Pro81.6
Input Price (per 1M tokens)$1.50$3.00
Output Price (per 1M tokens)$7.50$15.0
Context Window1M1M
Benchmarks Published711

Gemini 3.8 Flash vs Kimi K3 head-to-head charts

Gemini 3.8 Flash leads 7 and Kimi K3 leads 1 of 8 shared benchmarks. Gemini 3.8 Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Gemini 3.8 FlashKimi K3
Overall
63.3Gemini 3.8 Flash
62.8Kimi K3
ACB
61.1Gemini 3.8 Flash
57.7Kimi K3
HLE
54.9Gemini 3.8 Flash
43.5Kimi K3
Terminal-Bench
89.4Gemini 3.8 Flash
88.3Kimi K3
DeepSWE
73.8Gemini 3.8 Flash
68.5Kimi K3
GDPval-AA
1545.0Gemini 3.8 Flash
1668.0Kimi K3
Finance Agent
61.4Gemini 3.8 Flash
54.4Kimi K3
CharXiv
86.2Gemini 3.8 Flash
84.8Kimi K3
Gemini 3.8 Flash
Input$1.50
Output$7.50
Workload$3.00
Context1M
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M

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

More Gemini 3.8 Flash and Kimi K3 comparisons

Explore how Gemini 3.8 Flash and Kimi K3 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.