LLM Comparison

Gemini 3.6 Flash vs SWE-1.7: benchmark scores, pricing & comparison.

Side-by-side Gemini 3.6 Flash vs SWE-1.7 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.

Open live leaderboardGemini 3.6 Flash model pageSWE-1.7 model page
Rank #17 vs #46AskClash overall scores 62.9 vs 26.7.
Pricing $1.50/$7.50 vs $0/$0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryGoogle vs Cognition.

Gemini 3.6 Flash vs SWE-1.7 benchmark comparison

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

MetricGemini 3.6 FlashSWE-1.7
Overall Score62.926.7
Leaderboard Rank#17#46
RWT—8.5
HLE38.0—
GPQA92.8—
SWE-Pro58.7—
Terminal-Bench78.081.5
DeepSWE49.0—
OSWorld83.0—
CharXiv85.2—
MMMU-Pro83.2—
MRCR91.8—
Input Price (per 1M tokens)$1.50$0
Output Price (per 1M tokens)$7.50$0
Context Window1M256K
Benchmarks Published111

Gemini 3.6 Flash vs SWE-1.7 head-to-head charts

Gemini 3.6 Flash leads 1 and SWE-1.7 leads 1 of 2 shared benchmarks. SWE-1.7 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Gemini 3.6 FlashSWE-1.7
Overall
62.9Gemini 3.6 Flash
26.7SWE-1.7
Terminal-Bench
78.0Gemini 3.6 Flash
81.5SWE-1.7
Gemini 3.6 Flash
Input$1.50
Output$7.50
Workload$3.00
Context1M
SWE-1.7
Input$0
Output$0
Workload$0.00
Context256K

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

More Gemini 3.6 Flash and SWE-1.7 comparisons

Explore how Gemini 3.6 Flash and SWE-1.7 stack up against other top-ranked LLMs.

Claude Fable 5 vs Gemini 3.6 FlashClaude Fable 5 vs SWE-1.7GPT-5.6 Sol vs Gemini 3.6 FlashGPT-5.6 Sol vs SWE-1.7Kimi K3 vs Gemini 3.6 FlashKimi K3 vs SWE-1.7Claude Opus 4.8 vs Gemini 3.6 FlashClaude Opus 4.8 vs SWE-1.7Grok 4.5 vs Gemini 3.6 FlashGrok 4.5 vs SWE-1.7

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.