gemini-3.5-flash-low
Input $0.04 USD · Output $0.20 USD / 1M tokens
chat comparison
gemini-3.5-flash-lowvsgpt-5.5
Compare the things that matter before you build: current price, capabilities, and latest aggregated LLM7 statistics.
Current pricing
See the cost difference clearly
gpt-5.5
Input $0.55 USD · Output $3.30 USD / 1M tokens
Minimum request: $0.0001 USD
What's different
Only capabilities that differ between these models are listed. Green highlights the broader supported option or larger context window.
Context window
gemini-3.5-flash-low
1,040,000 tokens
gpt-5.5Better fit
1,050,000 tokens
Input formats
gemini-3.5-flash-low
text
gpt-5.5
text, image
Vision
gemini-3.5-flash-low
Not supported
gpt-5.5Better fit
Supported
Tool calling
gemini-3.5-flash-low
Not supported
gpt-5.5Better fit
Supported
Latest LLM7 statistics
Recent aggregated percentages and response-time metrics from LLM7, not a global model benchmark or traffic disclosure.
Recent stability
gemini-3.5-flash-low
80%
gpt-5.5
82%
Average response time
gemini-3.5-flash-low
17,079.2 ms
gpt-5.5
15,646.35 ms
P95 API latency
gemini-3.5-flash-low
60,000 ms
gpt-5.5
60,000 ms
Side-by-side trends
Shared charts make the observed differences easier to read. Metrics without enough history stay hidden.
Request success rate
Both models on the same scale
gemini-3.5-flash-low: 100%gpt-5.5: 100%
Average API latency
Both models on the same scale
gemini-3.5-flash-low: 30,227 msgpt-5.5: 4,105 ms
P95 API latency
Both models on the same scale
gemini-3.5-flash-low: 60,000 msgpt-5.5: 5,000 ms
Estimate your workload
Try the same request volume against both public price lists.
Cost calculator
Adjust the volume to see an instant estimate at the current public price.
01M
Input estimate
$0.0004
Output estimate
$0.0005
Estimated total
$0.0009
Cost calculator
Adjust the volume to see an instant estimate at the current public price.
01M
Input estimate
$0.0055
Output estimate
$0.00825
Estimated total
$0.01375
Quick take
- gpt-5.5 has a larger context window.
- gpt-5.5 supports image input while the other model does not.