LLM Comparison

Gemini 4 Argon vs Kimi K3.1 Pro: benchmark scores, pricing & comparison.

Side-by-side Gemini 4 Argon vs Kimi K3.1 Pro 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.

Verdict: Gemini 4 Argon ranks higher (#6 vs #9); Kimi K3.1 Pro wins 3 of 5 shared benchmarks.

Rank #6 vs #9AskClash overall scores 72.0 vs 68.4.
Pricing $2.00/$10.0 vs $2.00/$10.0Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightGoogle vs Moonshot AI.

Gemini 4 Argon vs Kimi K3.1 Pro benchmark comparison

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

MetricGemini 4 ArgonKimi K3.1 Pro
Overall Score72.068.4
Leaderboard Rank#6#9
ACB74.8—
HLE57.170.0
GPQA—94.2
Terminal-Bench57.167.2
DeepSWE77.975.5
GDPval-AA1624.11845.7
Finance Agent65.458.6
CharXiv—89.0
MMMU-Pro—84.1
Input Price (per 1M tokens)$2.00$2.00
Output Price (per 1M tokens)$10.0$10.0
Context Window1M1M
Benchmarks Published911

Gemini 4 Argon vs Kimi K3.1 Pro head-to-head charts

Gemini 4 Argon leads 3 and Kimi K3.1 Pro leads 3 of 6 shared benchmarks. Charts show only benchmarks both models publish.

Gemini 4 ArgonKimi K3.1 Pro
Overall
72.0Gemini 4 Argon
68.4Kimi K3.1 Pro
HLE
57.1Gemini 4 Argon
70.0Kimi K3.1 Pro
Terminal-Bench
57.1Gemini 4 Argon
67.2Kimi K3.1 Pro
DeepSWE
77.9Gemini 4 Argon
75.5Kimi K3.1 Pro
GDPval-AA
1624.1Gemini 4 Argon
1845.7Kimi K3.1 Pro
Finance Agent
65.4Gemini 4 Argon
58.6Kimi K3.1 Pro
Gemini 4 Argon
Input$2.00
Output$10.0
Workload$4.00
Context1M
Kimi K3.1 Pro
Input$2.00
Output$10.0
Workload$4.00
Context1M

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

More Gemini 4 Argon and Kimi K3.1 Pro comparisons

Explore how Gemini 4 Argon and Kimi K3.1 Pro 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.