Compare · ModelsLive · 2 picked · head to head
Gemini 3.5 Flash vs GPT-5.2
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Gemini 3.5 Flash wins on 10/16 benchmarks
Gemini 3.5 Flash wins 10 of 16 shared benchmarks. Leads in agentic · reasoning · arena.
Category leads
agentic·Gemini 3.5 Flashreasoning·Gemini 3.5 Flasharena·Gemini 3.5 Flashknowledge·Gemini 3.5 Flashmath·GPT-5.2coding·Gemini 3.5 Flash
Hype vs Reality
Attention vs performance
Gemini 3.5 Flash
#44 by perf·no signal
GPT-5.2
#93 by perf·no signal
Best value
Gemini 3.5 Flash
1.8x better value than GPT-5.2
Gemini 3.5 Flash
11.9 pts/$
$5.25/M
GPT-5.2
6.8 pts/$
$7.88/M
Vendor risk
Who is behind the model
Google DeepMind
$4.00T·Tier 1
OpenAI
$840.0B·Tier 1
Head to head
16 benchmarks · 2 models
Gemini 3.5 FlashGPT-5.2
APEX-Agents
Gemini 3.5 Flash leads by +15.3
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Gemini 3.5 Flash
49.6
GPT-5.2
34.3
ARC-AGI
Gemini 3.5 Flash leads by +6.3
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Gemini 3.5 Flash
92.5
GPT-5.2
86.2
ARC-AGI-2
Gemini 3.5 Flash leads by +19.2
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
Gemini 3.5 Flash
72.1
GPT-5.2
52.9
Chatbot Arena Elo · Coding
Gemini 3.5 Flash leads by +100.6
Gemini 3.5 Flash
1505.5
GPT-5.2
1405.0
Chatbot Arena Elo · Overall
Gemini 3.5 Flash leads by +41.6
Gemini 3.5 Flash
1476.3
GPT-5.2
1434.6
Chess Puzzles
Gemini 3.5 Flash leads by +1.0
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Gemini 3.5 Flash
50.0
GPT-5.2
49.0
FrontierMath-2025-02-28-Private
GPT-5.2 leads by +1.7
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Gemini 3.5 Flash
39.0
GPT-5.2
40.7
FrontierMath-Tier-4-2025-07-01-Private
GPT-5.2 leads by +4.2
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Gemini 3.5 Flash
14.6
GPT-5.2
18.8
FrontierMath-Tier-4-v2-Private
GPT-5.2 leads by +4.9
Gemini 3.5 Flash
26.8
GPT-5.2
31.7
FrontierMath-Tiers-1-3-v2-Private
GPT-5.2 leads by +4.6
Gemini 3.5 Flash
62.8
GPT-5.2
67.4
GPQA diamond
Gemini 3.5 Flash leads by +1.9
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Gemini 3.5 Flash
90.4
GPT-5.2
88.5
OTIS Mock AIME 2024-2025
GPT-5.2 leads by +0.6
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3.5 Flash
95.5
GPT-5.2
96.1
SimpleBench
Gemini 3.5 Flash leads by +37.1
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Gemini 3.5 Flash
72.0
GPT-5.2
35.0
SimpleQA Verified
Gemini 3.5 Flash leads by +29.5
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Gemini 3.5 Flash
68.4
GPT-5.2
38.9
SWE-Bench verified
Gemini 3.5 Flash leads by +5.6
SWE-bench Verified · 500 human-validated tasks from 12 real Python repositories (Django, Flask, scikit-learn, sympy, and others). Each task requires the model to produce a git patch that resolves a real GitHub issue and passes the test suite. The verified subset eliminates ambiguous tasks from the original SWE-bench. Claude Mythos Preview leads at 93.9%, crossing 90% for the first time in 2026. Opus 4.6 scores 80.8%. The benchmark remains the most-cited evaluation for code-generation capability.
Gemini 3.5 Flash
79.3
GPT-5.2
73.8
WeirdML
GPT-5.2 leads by +9.6
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Gemini 3.5 Flash
62.6
GPT-5.2
72.2
Full benchmark table
| Benchmark | Gemini 3.5 Flash | GPT-5.2 |
|---|---|---|
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 49.6 | 34.3 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | 92.5 | 86.2 |
ARC-AGI-2 ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data. | 72.1 | 52.9 |
Chatbot Arena Elo · Coding | 1505.5 | 1405.0 |
Chatbot Arena Elo · Overall | 1476.3 | 1434.6 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 50.0 | 49.0 |
FrontierMath-2025-02-28-Private FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning. | 39.0 | 40.7 |
FrontierMath-Tier-4-2025-07-01-Private FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning. | 14.6 | 18.8 |
FrontierMath-Tier-4-v2-Private | 26.8 | 31.7 |
FrontierMath-Tiers-1-3-v2-Private | 62.8 | 67.4 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 90.4 | 88.5 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 95.5 | 96.1 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 72.0 | 35.0 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 68.4 | 38.9 |
SWE-Bench verified SWE-bench Verified · 500 human-validated tasks from 12 real Python repositories (Django, Flask, scikit-learn, sympy, and others). Each task requires the model to produce a git patch that resolves a real GitHub issue and passes the test suite. The verified subset eliminates ambiguous tasks from the original SWE-bench. Claude Mythos Preview leads at 93.9%, crossing 90% for the first time in 2026. Opus 4.6 scores 80.8%. The benchmark remains the most-cited evaluation for code-generation capability. | 79.3 | 73.8 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 62.6 | 72.2 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $1.50 | $9.00 | 1.0M tokens (~524 books) | $33.75 | |
| $1.75 | $14.00 | 400K tokens (~200 books) | $48.13 |