Compare · ModelsLive · 2 picked · head to head
Gemini 3.5 Flash vs Claude Fable 5
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Fable 5 wins on 10/13 benchmarks
Claude Fable 5 wins 10 of 13 shared benchmarks. Leads in speed · arena · math.
Category leads
speed·Claude Fable 5agentic·Gemini 3.5 Flasharena·Claude Fable 5knowledge·Gemini 3.5 Flashmath·Claude Fable 5reasoning·Claude Fable 5coding·Claude Fable 5
Hype vs Reality
Attention vs performance
Gemini 3.5 Flash
#44 by perf·no signal
Claude Fable 5
#12 by perf·no signal
Best value
Gemini 3.5 Flash
4.8x better value than Claude Fable 5
Gemini 3.5 Flash
11.9 pts/$
$5.25/M
Claude Fable 5
2.5 pts/$
$30.00/M
Vendor risk
Who is behind the model
Google DeepMind
$4.00T·Tier 1
Anthropic
$380.0B·Tier 1
Head to head
13 benchmarks · 2 models
Gemini 3.5 FlashClaude Fable 5
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?"
Gemini 3.5 Flash
37.5
Claude Fable 5
52.8
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.
Gemini 3.5 Flash
70.1
Claude Fable 5
76.5
Artificial Analysis · Quality Index
Claude Fable 5 leads by +9.7
Gemini 3.5 Flash
50.2
Claude Fable 5
59.9
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.
Gemini 3.5 Flash
49.6
Claude Fable 5
45.0
Chatbot Arena Elo · Coding
Claude Fable 5 leads by +148.4
Gemini 3.5 Flash
1505.5
Claude Fable 5
1653.9
Chatbot Arena Elo · Overall
Claude Fable 5 leads by +31.3
Gemini 3.5 Flash
1476.3
Claude Fable 5
1507.6
Chess Puzzles
Gemini 3.5 Flash leads by +9.0
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
Claude Fable 5
41.0
FrontierMath-Tier-4-v2-Private
Claude Fable 5 leads by +61.0
Gemini 3.5 Flash
26.8
Claude Fable 5
87.8
FrontierMath-Tiers-1-3-v2-Private
Claude Fable 5 leads by +24.2
Gemini 3.5 Flash
62.8
Claude Fable 5
87.0
OTIS Mock AIME 2024-2025
Claude Fable 5 leads by +4.2
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3.5 Flash
95.5
Claude Fable 5
99.7
SimpleBench
Claude Fable 5 leads by +6.2
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Gemini 3.5 Flash
72.0
Claude Fable 5
78.3
SimpleQA Verified
Gemini 3.5 Flash leads by +0.1
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
Claude Fable 5
68.3
WeirdML
Claude Fable 5 leads by +25.2
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Gemini 3.5 Flash
62.6
Claude Fable 5
87.8
Full benchmark table
| Benchmark | Gemini 3.5 Flash | Claude Fable 5 |
|---|---|---|
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?" | 37.5 | 52.8 |
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. | 70.1 | 76.5 |
Artificial Analysis · Quality Index | 50.2 | 59.9 |
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 | 45.0 |
Chatbot Arena Elo · Coding | 1505.5 | 1653.9 |
Chatbot Arena Elo · Overall | 1476.3 | 1507.6 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 50.0 | 41.0 |
FrontierMath-Tier-4-v2-Private | 26.8 | 87.8 |
FrontierMath-Tiers-1-3-v2-Private | 62.8 | 87.0 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 95.5 | 99.7 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 72.0 | 78.3 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 68.4 | 68.3 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 62.6 | 87.8 |
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 | |
| $10.00 | $50.00 | 1.0M tokens (~500 books) | $200.00 |