Compare · ModelsLive · 3 picked · head to head
Claude Fable 5 vs Gemini 3.1 Pro Preview vs Gemini 3.5 Flash
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Fable 5 wins on 10/19 benchmarks
Claude Fable 5 wins 10 of 19 shared benchmarks. Leads in speed · arena · math.
Category leads
speed·Claude Fable 5agentic·Gemini 3.5 Flasharena·Claude Fable 5knowledge·Gemini 3.1 Pro Previewmath·Claude Fable 5reasoning·Gemini 3.1 Pro Previewcoding·Claude Fable 5
Hype vs Reality
Attention vs performance
Claude Fable 5
#12 by perf·no signal
Gemini 3.1 Pro Preview
#74 by perf·no signal
Gemini 3.5 Flash
#44 by perf·no signal
Best value
Gemini 3.5 Flash
1.5x better value than Gemini 3.1 Pro Preview
Claude Fable 5
2.5 pts/$
$30.00/M
Gemini 3.1 Pro Preview
8.1 pts/$
$7.00/M
Gemini 3.5 Flash
11.9 pts/$
$5.25/M
Vendor risk
Who is behind the model
Anthropic
$380.0B·Tier 1
Google DeepMind
$4.00T·Tier 1
Google DeepMind
$4.00T·Tier 1
Head to head
19 benchmarks · 3 models
Claude Fable 5Gemini 3.1 Pro PreviewGemini 3.5 Flash
Artificial Analysis · Agentic Index
Claude Fable 5 leads by +15.4
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?"
Claude Fable 5
52.8
Gemini 3.1 Pro Preview
21.4
Gemini 3.5 Flash
37.5
Artificial Analysis · Coding Index
Claude Fable 5 leads by +6.3
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.
Claude Fable 5
76.5
Gemini 3.1 Pro Preview
68.8
Gemini 3.5 Flash
70.1
Artificial Analysis · Quality Index
Claude Fable 5 leads by +9.7
Claude Fable 5
59.9
Gemini 3.1 Pro Preview
46.5
Gemini 3.5 Flash
50.2
APEX-Agents
Gemini 3.5 Flash leads by +4.6
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Claude Fable 5
45.0
Gemini 3.1 Pro Preview
33.5
Gemini 3.5 Flash
49.6
Chatbot Arena Elo · Coding
Claude Fable 5 leads by +148.4
Claude Fable 5
1653.9
Gemini 3.1 Pro Preview
1447.0
Gemini 3.5 Flash
1505.5
Chatbot Arena Elo · Overall
Claude Fable 5 leads by +21.2
Claude Fable 5
1507.6
Gemini 3.1 Pro Preview
1486.4
Gemini 3.5 Flash
1476.3
Chess Puzzles
Gemini 3.1 Pro Preview leads by +5.0
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Claude Fable 5
41.0
Gemini 3.1 Pro Preview
55.0
Gemini 3.5 Flash
50.0
FrontierMath-Tier-4-v2-Private
Claude Fable 5 leads by +61.0
Claude Fable 5
87.8
Gemini 3.1 Pro Preview
26.8
Gemini 3.5 Flash
26.8
FrontierMath-Tiers-1-3-v2-Private
Claude Fable 5 leads by +24.2
Claude Fable 5
87.0
Gemini 3.1 Pro Preview
59.6
Gemini 3.5 Flash
62.8
OTIS Mock AIME 2024-2025
Claude Fable 5 leads by +4.1
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Fable 5
99.7
Gemini 3.1 Pro Preview
95.6
Gemini 3.5 Flash
95.5
SimpleBench
Claude Fable 5 leads by +2.8
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Fable 5
78.3
Gemini 3.1 Pro Preview
75.5
Gemini 3.5 Flash
72.0
SimpleQA Verified
Gemini 3.1 Pro Preview leads by +8.9
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Claude Fable 5
68.3
Gemini 3.1 Pro Preview
77.3
Gemini 3.5 Flash
68.4
WeirdML
Claude Fable 5 leads by +15.8
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Claude Fable 5
87.8
Gemini 3.1 Pro Preview
72.1
Gemini 3.5 Flash
62.6
ARC-AGI
Gemini 3.1 Pro Preview leads by +5.5
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Gemini 3.1 Pro Preview
98.0
Gemini 3.5 Flash
92.5
ARC-AGI-2
Gemini 3.1 Pro Preview leads by +5.0
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
Gemini 3.1 Pro Preview
77.1
Gemini 3.5 Flash
72.1
FrontierMath-2025-02-28-Private
Gemini 3.5 Flash leads by +2.1
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Gemini 3.1 Pro Preview
36.9
Gemini 3.5 Flash
39.0
FrontierMath-Tier-4-2025-07-01-Private
Gemini 3.1 Pro Preview leads by +2.1
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Gemini 3.1 Pro Preview
16.7
Gemini 3.5 Flash
14.6
GPQA diamond
Gemini 3.1 Pro Preview leads by +1.7
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
Gemini 3.5 Flash
90.4
SWE-Bench verified
Gemini 3.5 Flash leads by +3.7
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 3.1 Pro Preview
75.6
Gemini 3.5 Flash
79.3
Full benchmark table
| Benchmark | Claude Fable 5 | Gemini 3.1 Pro Preview | Gemini 3.5 Flash |
|---|---|---|---|
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?" | 52.8 | 21.4 | 37.5 |
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. | 76.5 | 68.8 | 70.1 |
Artificial Analysis · Quality Index | 59.9 | 46.5 | 50.2 |
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 45.0 | 33.5 | 49.6 |
Chatbot Arena Elo · Coding | 1653.9 | 1447.0 | 1505.5 |
Chatbot Arena Elo · Overall | 1507.6 | 1486.4 | 1476.3 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 41.0 | 55.0 | 50.0 |
FrontierMath-Tier-4-v2-Private | 87.8 | 26.8 | 26.8 |
FrontierMath-Tiers-1-3-v2-Private | 87.0 | 59.6 | 62.8 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 99.7 | 95.6 | 95.5 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 78.3 | 75.5 | 72.0 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 68.3 | 77.3 | 68.4 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 87.8 | 72.1 | 62.6 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | — | 98.0 | 92.5 |
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. | — | 77.1 | 72.1 |
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. | — | 36.9 | 39.0 |
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. | — | 16.7 | 14.6 |
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 | 90.4 |
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. | — | 75.6 | 79.3 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $10.00 | $50.00 | 1.0M tokens (~500 books) | $200.00 | |
| $2.00 | $12.00 | 1.0M tokens (~524 books) | $45.00 | |
| $1.50 | $9.00 | 1.0M tokens (~524 books) | $33.75 |