LLM Comparison

Grok 4.6 vs Inkling-Small: benchmark scores, pricing & comparison.

Side-by-side Grok 4.6 vs Inkling-Small 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 #4 vs #30AskClash overall scores 77.3 vs 36.6.
Pricing $2.00/$6.00 vs $0.58/$1.44Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightxAI vs Thinking Machines Lab.

Grok 4.6 vs Inkling-Small benchmark comparison

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

MetricGrok 4.6Inkling-Small
Overall Score77.336.6
Leaderboard Rank#4#30
ACB69.0
RWT9.0
Coding Agent Index76.4
HLE40.347.8
GPQA94.989.5
IFEval82.2
SWE-bench80.2
SWE-Pro64.7
SWE-Atlas83.9
Terminal-Bench88.464.7
DeepSWE65.9
GDPval-AA1753.0
MCP Atlas79.6
Finance Agent53.741.3
CharXiv81.3
MMMU-Pro80.474.0
ARC-AGI 252.640.1
Input Price (per 1M tokens)$2.00$0.58
Output Price (per 1M tokens)$6.00$1.44
Context Window500K1M
Benchmarks Published1310

Grok 4.6 vs Inkling-Small head-to-head charts

Grok 4.6 leads 6 and Inkling-Small leads 1 of 7 shared benchmarks. Inkling-Small is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.6Inkling-Small
Overall
77.3Grok 4.6
36.6Inkling-Small
HLE
40.3Grok 4.6
47.8Inkling-Small
GPQA
94.9Grok 4.6
89.5Inkling-Small
Terminal-Bench
88.4Grok 4.6
64.7Inkling-Small
Finance Agent
53.7Grok 4.6
41.3Inkling-Small
MMMU-Pro
80.4Grok 4.6
74.0Inkling-Small
ARC-AGI 2
52.6Grok 4.6
40.1Inkling-Small
Grok 4.6
Input$2.00
Output$6.00
Workload$3.20
Context500K
Inkling-Small
Input$0.58
Output$1.44
Workload$0.87
Context1M

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

More Grok 4.6 and Inkling-Small comparisons

Explore how Grok 4.6 and Inkling-Small 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.