LLM Comparison

Qwen3.8 27B vs Gemini 3.1 Pro: benchmark scores, pricing & comparison.

Side-by-side Qwen3.8 27B vs Gemini 3.1 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.

Rank #17 vs #33AskClash overall scores 57.0 vs 40.6.
Pricing $0.45/$3.20 vs $2.00/$12.0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryAlibaba vs Google.

Qwen3.8 27B vs Gemini 3.1 Pro benchmark comparison

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

MetricQwen3.8 27BGemini 3.1 Pro
Overall Score57.040.6
Leaderboard Rank#17#33
ACB56.4
Coding Agent Index30.3
HLE30.851.4
GPQA89.294.3
IFEval79.5
SWE-bench80.6
SWE-Pro61.754.2
Terminal-Bench73.068.5
DeepSWE42.211.7
OSWorld84.3
MCP Atlas69.2
Finance Agent43.0
CharXiv90.280.2
MMMU-Pro83.9
ARC-AGI 277.1
Tau299.3
MRCR84.9
Input Price (per 1M tokens)$0.45$2.00
Output Price (per 1M tokens)$3.20$12.0
Context Window262K1M
Benchmarks Published916

Qwen3.8 27B vs Gemini 3.1 Pro head-to-head charts

Qwen3.8 27B leads 5 and Gemini 3.1 Pro leads 2 of 7 shared benchmarks. Qwen3.8 27B is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Qwen3.8 27BGemini 3.1 Pro
Overall
57.0Qwen3.8 27B
40.6Gemini 3.1 Pro
HLE
30.8Qwen3.8 27B
51.4Gemini 3.1 Pro
GPQA
89.2Qwen3.8 27B
94.3Gemini 3.1 Pro
SWE-Pro
61.7Qwen3.8 27B
54.2Gemini 3.1 Pro
Terminal-Bench
73.0Qwen3.8 27B
68.5Gemini 3.1 Pro
DeepSWE
42.2Qwen3.8 27B
11.7Gemini 3.1 Pro
CharXiv
90.2Qwen3.8 27B
80.2Gemini 3.1 Pro
Qwen3.8 27B
Input$0.45
Output$3.20
Workload$1.09
Context262K
Gemini 3.1 Pro
Input$2.00
Output$12.0
Workload$4.40
Context1M

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

More Qwen3.8 27B and Gemini 3.1 Pro comparisons

Explore how Qwen3.8 27B and Gemini 3.1 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.