Benchmark scores
Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.
LLM Comparison
Gemini 3.6 Flash vs Qwen3.7 Plus: benchmark scores, pricing & comparison.
Side-by-side Gemini 3.6 Flash vs Qwen3.7 Plus 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 3.6 Flash wins 6 of 8 shared benchmarks; Qwen3.7 Plus costs less ($0.40/$1.60 vs $1.50/$7.50 per 1M tokens).
Rank #129 vs #129AskClash overall scores 44.7 vs 36.4.
Pricing $1.50/$7.50 vs $0.40/$1.60Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryGoogle vs Alibaba.
Gemini 3.6 Flash vs Qwen3.7 Plus benchmark comparison
Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.
| Metric | Gemini 3.6 Flash | Qwen3.7 Plus |
|---|---|---|
| Overall Score | 44.7 | 36.4 |
| Leaderboard Rank | #129 | #129 |
| ACB | 33.8 | — |
| RWT | — | 7.5 |
| HLE | 38.0 | 34.7 |
| GPQA | 92.8 | 90.3 |
| IFEval | — | 94.6 |
| SWE-bench | — | 77.7 |
| SWE-Pro | 58.7 | 57.6 |
| DeepSWE | 46.7 | — |
| GDPval-AA | 1421.0 | 1522.1 |
| OSWorld | 83.0 | 73.3 |
| MCP Atlas | — | 73.2 |
| Finance Agent | — | 38.2 |
| CharXiv | 85.2 | 85.9 |
| MMMU-Pro | 83.2 | 79.0 |
| Tau2 | — | 93.0 |
| MRCR | 91.8 | 91.7 |
| Input Price (per 1M tokens) | $1.50 | $0.40 |
| Output Price (per 1M tokens) | $7.50 | $1.60 |
| Context Window | 1M | 1M |
| Benchmarks Published | 9 | 11 |
Gemini 3.6 Flash vs Qwen3.7 Plus head-to-head charts
Gemini 3.6 Flash leads 7 and Qwen3.7 Plus leads 2 of 9 shared benchmarks. Qwen3.7 Plus is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.
Gemini 3.6 FlashQwen3.7 Plus
Overall
HLE
GPQA
SWE-Pro
GDPval-AA
OSWorld
CharXiv
MMMU-Pro
MRCR
Gemini 3.6 Flash
Input$1.50
Output$7.50
Workload$3.00
Context1M
Qwen3.7 Plus
Input$0.40
Output$1.60
Workload$0.72
Context1M
Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.
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How to read this comparison
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.