Compare · ModelsLive · 2 picked · head to head
Gemini 3.1 Pro Preview vs Qwen3.6 27B
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Gemini 3.1 Pro Preview wins on 8/10 benchmarks
Gemini 3.1 Pro Preview wins 8 of 10 shared benchmarks. Leads in knowledge · general · math.
Category leads
speed·Qwen3.6 27Bknowledge·Gemini 3.1 Pro Previewgeneral·Gemini 3.1 Pro Previewmath·Gemini 3.1 Pro Preview
Hype vs Reality
Attention vs performance
Gemini 3.1 Pro Preview
#148 by perf·#10 by attention
Qwen3.6 27B
#69 by perf·#1 by attention
Best value
Qwen3.6 27B
4.7x better value than Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview
6.9 pts/$
$7.00/M
Qwen3.6 27B
32.6 pts/$
$1.76/M
Vendor risk
Who is behind the model
Google DeepMind
$3.53T·Tier 1
Alibaba (Qwen)
$293.0B·Tier 1
Head to head
10 benchmarks · 2 models
Gemini 3.1 Pro PreviewQwen3.6 27B
Artificial Analysis · Agentic Index
Qwen3.6 27B leads by +5.6
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
Gemini 3.1 Pro Preview
21.4
Qwen3.6 27B
27.0
Artificial Analysis · Coding Index
Gemini 3.1 Pro Preview leads by +15.1
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
Gemini 3.1 Pro Preview
68.8
Qwen3.6 27B
53.7
Artificial Analysis · Quality Index
Qwen3.6 27B leads by +7.3
Gemini 3.1 Pro Preview
29.7
Qwen3.6 27B
37.0
Chess Puzzles
Gemini 3.1 Pro Preview leads by +30.5
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Gemini 3.1 Pro Preview
48.4
Qwen3.6 27B
17.9
Dtbench
Gemini 3.1 Pro Preview leads by +31.6
Gemini 3.1 Pro Preview
95.1
Qwen3.6 27B
63.5
FrontierMath-Tiers-1-3-v2-Private
Gemini 3.1 Pro Preview leads by +25.9
Gemini 3.1 Pro Preview
62.8
Qwen3.6 27B
36.9
GPQA diamond
Gemini 3.1 Pro Preview leads by +11.9
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Gemini 3.1 Pro Preview
96.5
Qwen3.6 27B
84.5
Lmca
Gemini 3.1 Pro Preview leads by +22.7
Gemini 3.1 Pro Preview
63.3
Qwen3.6 27B
40.6
Mystery Game Puzzles
Gemini 3.1 Pro Preview leads by +27.3
Gemini 3.1 Pro Preview
27.3
Qwen3.6 27B
0.0
OTIS Mock AIME 2024-2025
Gemini 3.1 Pro Preview leads by +4.5
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3.1 Pro Preview
95.6
Qwen3.6 27B
91.1
Full benchmark table
| Benchmark | Gemini 3.1 Pro Preview | Qwen3.6 27B |
|---|---|---|
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 21.4 | 27.0 |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 68.8 | 53.7 |
Artificial Analysis · Quality Index | 29.7 | 37.0 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 48.4 | 17.9 |
Dtbench | 95.1 | 63.5 |
FrontierMath-Tiers-1-3-v2-Private | 62.8 | 36.9 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 96.5 | 84.5 |
Lmca | 63.3 | 40.6 |
Mystery Game Puzzles | 27.3 | 0.0 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 95.6 | 91.1 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $2.00 | $12.00 | 1.0M tokens (~524 books) | $45.00 | |
| $0.32 | $3.20 | 262K tokens (~131 books) | $10.40 |
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