Compare · ModelsLive · 2 picked · head to head
Gemini 3.1 Pro Preview vs Kimi K2.7 Code
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Gemini 3.1 Pro Preview wins on 18/22 benchmarks
Gemini 3.1 Pro Preview wins 18 of 22 shared benchmarks. Leads in speed · knowledge · math.
Category leads
speed·Gemini 3.1 Pro Previewagentic·Kimi K2.7 Codeknowledge·Gemini 3.1 Pro Previewcoding·Kimi K2.7 Codemath·Gemini 3.1 Pro Previewreasoning·Gemini 3.1 Pro Preview
Hype vs Reality
Attention vs performance
Gemini 3.1 Pro Preview
#143 by perf·#10 by attention
Kimi K2.7 Code
#79 by perf·#15 by attention
Best value
Kimi K2.7 Code
3.9x better value than Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview
7.0 pts/$
$7.00/M
Kimi K2.7 Code
27.4 pts/$
$2.05/M
Vendor risk
Who is behind the model
Google DeepMind
$3.61T·Tier 1
Moonshot AI
$50.0B·Tier 1
Head to head
22 benchmarks · 2 models
Gemini 3.1 Pro PreviewKimi K2.7 Code
Artificial Analysis · Agentic Index
Kimi K2.7 Code leads by +8.2
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
Kimi K2.7 Code
29.6
Artificial Analysis · Coding Index
Gemini 3.1 Pro Preview leads by +8.1
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
Kimi K2.7 Code
60.8
Artificial Analysis · CritPt
Gemini 3.1 Pro Preview leads by +7.7
Gemini 3.1 Pro Preview
17.7
Kimi K2.7 Code
10.0
Artificial Analysis · GDPval
Kimi K2.7 Code leads by +12.3
Gemini 3.1 Pro Preview
14.6
Kimi K2.7 Code
26.9
Artificial Analysis · GPQA Diamond
Gemini 3.1 Pro Preview leads by +4.5
Gemini 3.1 Pro Preview
94.1
Kimi K2.7 Code
89.6
Artificial Analysis · Humanity's Last Exam
Gemini 3.1 Pro Preview leads by +12.0
Gemini 3.1 Pro Preview
47.0
Kimi K2.7 Code
35.0
Artificial Analysis · IFBench
Gemini 3.1 Pro Preview leads by +14.0
Gemini 3.1 Pro Preview
77.1
Kimi K2.7 Code
63.1
Artificial Analysis · Long Context Reasoning
Gemini 3.1 Pro Preview leads by +2.7
Gemini 3.1 Pro Preview
82.0
Kimi K2.7 Code
79.3
Artificial Analysis · Quality Index
Gemini 3.1 Pro Preview leads by +3.9
Gemini 3.1 Pro Preview
29.7
Kimi K2.7 Code
25.8
Artificial Analysis · SciCode
Gemini 3.1 Pro Preview leads by +10.9
Gemini 3.1 Pro Preview
58.7
Kimi K2.7 Code
47.8
Artificial Analysis · tau2-Bench Telecom
Gemini 3.1 Pro Preview leads by +5.5
Gemini 3.1 Pro Preview
95.6
Kimi K2.7 Code
90.1
Artificial Analysis · Terminal-Bench Hard
Gemini 3.1 Pro Preview leads by +9.1
Gemini 3.1 Pro Preview
53.8
Kimi K2.7 Code
44.7
APEX-Agents
Kimi K2.7 Code leads by +2.5
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Gemini 3.1 Pro Preview
35.1
Kimi K2.7 Code
37.6
Chess Puzzles
Gemini 3.1 Pro Preview leads by +38.9
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
Kimi K2.7 Code
9.5
Deepswe
Kimi K2.7 Code leads by +18.8
Gemini 3.1 Pro Preview
11.7
Kimi K2.7 Code
30.5
FrontierMath-Tier-4-v2-Private
Gemini 3.1 Pro Preview leads by +14.6
Gemini 3.1 Pro Preview
26.8
Kimi K2.7 Code
12.2
FrontierMath-Tiers-1-3-v2-Private
Gemini 3.1 Pro Preview leads by +5.9
Gemini 3.1 Pro Preview
62.8
Kimi K2.7 Code
56.9
GPQA diamond
Gemini 3.1 Pro Preview leads by +9.1
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
Kimi K2.7 Code
87.3
OTIS Mock AIME 2024-2025
Gemini 3.1 Pro Preview leads by +0.0
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3.1 Pro Preview
95.6
Kimi K2.7 Code
95.5
SimpleBench
Gemini 3.1 Pro Preview leads by +26.0
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
Kimi K2.7 Code
49.5
SimpleQA Verified
Gemini 3.1 Pro Preview leads by +37.0
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
73.5
Kimi K2.7 Code
36.5
WeirdML
Gemini 3.1 Pro Preview leads by +17.9
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Gemini 3.1 Pro Preview
72.1
Kimi K2.7 Code
54.1
Full benchmark table
| Benchmark | Gemini 3.1 Pro Preview | Kimi K2.7 Code |
|---|---|---|
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 | 29.6 |
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 | 60.8 |
Artificial Analysis · CritPt | 17.7 | 10.0 |
Artificial Analysis · GDPval | 14.6 | 26.9 |
Artificial Analysis · GPQA Diamond | 94.1 | 89.6 |
Artificial Analysis · Humanity's Last Exam | 47.0 | 35.0 |
Artificial Analysis · IFBench | 77.1 | 63.1 |
Artificial Analysis · Long Context Reasoning | 82.0 | 79.3 |
Artificial Analysis · Quality Index | 29.7 | 25.8 |
Artificial Analysis · SciCode | 58.7 | 47.8 |
Artificial Analysis · tau2-Bench Telecom | 95.6 | 90.1 |
Artificial Analysis · Terminal-Bench Hard | 53.8 | 44.7 |
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 35.1 | 37.6 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 48.4 | 9.5 |
Deepswe | 11.7 | 30.5 |
FrontierMath-Tier-4-v2-Private | 26.8 | 12.2 |
FrontierMath-Tiers-1-3-v2-Private | 62.8 | 56.9 |
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 | 87.3 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 95.6 | 95.5 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 75.5 | 49.5 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 73.5 | 36.5 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 72.1 | 54.1 |
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 | |
| $0.60 | $3.50 | 262K tokens (~131 books) | $13.25 |