Compare · ModelsLive · 2 picked · head to head
Gemini 3.1 Pro Preview vs Qwen3.7 Max
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Gemini 3.1 Pro Preview wins on 7/10 benchmarks
Gemini 3.1 Pro Preview wins 7 of 10 shared benchmarks. Leads in speed · knowledge · reasoning.
Category leads
speed·Gemini 3.1 Pro Previewknowledge·Gemini 3.1 Pro Previewmath·Qwen3.7 Maxreasoning·Gemini 3.1 Pro Preview
Hype vs Reality
Attention vs performance
Gemini 3.1 Pro Preview
#74 by perf·no signal
Qwen3.7 Max
#28 by perf·no signal
Best value
Qwen3.7 Max
3.4x better value than Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview
8.1 pts/$
$7.00/M
Qwen3.7 Max
27.2 pts/$
$2.50/M
Vendor risk
Who is behind the model
Google DeepMind
$4.00T·Tier 1
Alibaba (Qwen)
$293.0B·Tier 1
Head to head
10 benchmarks · 2 models
Gemini 3.1 Pro PreviewQwen3.7 Max
Artificial Analysis · Agentic Index
Qwen3.7 Max leads by +9.2
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
Qwen3.7 Max
30.6
Artificial Analysis · Coding Index
Gemini 3.1 Pro Preview leads by +2.9
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
Qwen3.7 Max
66.0
Artificial Analysis · Quality Index
Gemini 3.1 Pro Preview leads by +0.5
Gemini 3.1 Pro Preview
46.5
Qwen3.7 Max
46.0
Chess Puzzles
Gemini 3.1 Pro Preview leads by +33.0
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
55.0
Qwen3.7 Max
22.0
FrontierMath-Tier-4-v2-Private
Qwen3.7 Max leads by +7.3
Gemini 3.1 Pro Preview
26.8
Qwen3.7 Max
34.1
FrontierMath-Tiers-1-3-v2-Private
Qwen3.7 Max leads by +4.9
Gemini 3.1 Pro Preview
59.6
Qwen3.7 Max
64.6
GPQA diamond
Gemini 3.1 Pro Preview leads by +3.3
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
92.1
Qwen3.7 Max
88.8
OTIS Mock AIME 2024-2025
Gemini 3.1 Pro Preview leads by +0.6
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3.1 Pro Preview
95.6
Qwen3.7 Max
95.0
SimpleBench
Gemini 3.1 Pro Preview leads by +11.0
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Gemini 3.1 Pro Preview
75.5
Qwen3.7 Max
64.5
SimpleQA Verified
Gemini 3.1 Pro Preview leads by +18.8
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Gemini 3.1 Pro Preview
77.3
Qwen3.7 Max
58.5
Full benchmark table
| Benchmark | Gemini 3.1 Pro Preview | Qwen3.7 Max |
|---|---|---|
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 | 30.6 |
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 | 66.0 |
Artificial Analysis · Quality Index | 46.5 | 46.0 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 55.0 | 22.0 |
FrontierMath-Tier-4-v2-Private | 26.8 | 34.1 |
FrontierMath-Tiers-1-3-v2-Private | 59.6 | 64.6 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 92.1 | 88.8 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 95.6 | 95.0 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 75.5 | 64.5 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 77.3 | 58.5 |
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 | |
| $1.25 | $3.75 | 1.0M tokens (~500 books) | $18.75 |