The latest flagship multimodal model supports million-token context, with encoding capability (SWE-bench 54.6%) and instruction-following (Scale AI 38.3%) performance significantly surpassing GPT-4o, while reducing costs by 26%, making it suitable for complex tasks. Its automatic caching mechanism offers a 75% cost reduction on cache hits.
Pricing
Input Modalities
- Text
- Vision
Output Modalities
- Text
Capabilities
- Tools
- Tool calling
- Structured outputs
- Long context
Providers
Azure gpt-4.1
Pricing$2$8
Cache Read$0.5/M tokens
Web Search$0.025/request
Context1M
Max output32K
Latency1.8S
Throughput78.6TPS
Uptime
100.00% uptime 2 days ago
99.99% uptime yesterday
99.97% uptime today
OpenAI gpt-4.1
Pricing$2$8
Cache Read$0.5/M tokens
Web Search$0.025/request
Context1M
Max output32K
Latency1.1S
Throughput43.3TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Performance for gpt-4.1
Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).
Uptime
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Latency
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Throughput
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Try this model
Python
