Compare · ModelsLive · 2 picked · head to head
Claude Opus 4.7 (Fast) vs Gemini 3.5 Flash
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Opus 4.7 (Fast) wins on 3/3 benchmarks
Claude Opus 4.7 (Fast) wins 3 of 3 shared benchmarks. Leads in speed.
Category leads
speed·Claude Opus 4.7 (Fast)
Hype vs Reality
Attention vs performance
Claude Opus 4.7 (Fast)
no bench·no signal
Gemini 3.5 Flash
#44 by perf·no signal
Best value
Gemini 3.5 Flash
Claude Opus 4.7 (Fast)
—
$90.00/M
Gemini 3.5 Flash
11.9 pts/$
$5.25/M
Vendor risk
Who is behind the model
Anthropic
$380.0B·Tier 1
Google DeepMind
$4.00T·Tier 1
Head to head
3 benchmarks · 2 models
Claude Opus 4.7 (Fast)Gemini 3.5 Flash
Artificial Analysis · Agentic Index
Claude Opus 4.7 (Fast) leads by +6.9
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 Opus 4.7 (Fast)
44.4
Gemini 3.5 Flash
37.5
Artificial Analysis · Coding Index
Claude Opus 4.7 (Fast) leads by +3.5
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 Opus 4.7 (Fast)
73.6
Gemini 3.5 Flash
70.1
Artificial Analysis · Quality Index
Claude Opus 4.7 (Fast) leads by +3.3
Claude Opus 4.7 (Fast)
53.5
Gemini 3.5 Flash
50.2
Full benchmark table
| Benchmark | Claude Opus 4.7 (Fast) | 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?" | 44.4 | 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. | 73.6 | 70.1 |
Artificial Analysis · Quality Index | 53.5 | 50.2 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $30.00 | $150.00 | 1.0M tokens (~500 books) | $600.00 | |
| $1.50 | $9.00 | 1.0M tokens (~524 books) | $33.75 |
People also compared