Ultra-lightweight model with million-token context, optimized for speed and low latency, costing only $0.10 per million input tokens. It is suitable for edge computing and real-time interaction. The automatic caching mechanism offers a 75% cost reduction on cache hits.
Pricing
Input Modalities
- Text
- Vision
Output Modalities
- Text
Context length
- 1.05M tokens
Max output
- 32.8K tokens
Capabilities
- Thinking
- Streaming
- Tool calling
- Web search
- URL context
- Code interpreter
- Computer use
- File search
- Memory tool
- Structured outputs
- Citations
- Prompt caching
- Background mode
- Server-side sessions
Providers
Azure gpt-4.1-nano
Pricing$0.1$0.4
Cache Read$0.025/M tokens
Web Search$0.01/request
Context1M
Max output32K
Latency1.0S
Throughput101.4TPS
Uptime
100.00% uptime 3 days ago
99.99% uptime 2 days ago
100.00% uptime yesterday
OpenAI gpt-4.1-nano
Pricing$0.1$0.4
Cache Read$0.025/M tokens
Web Search$0.01/request
Context1M
Max output32K
Latency0.8S
Throughput72.7TPS
Uptime
0.00% uptime 3 days ago
0.00% uptime 2 days ago
0.00% uptime yesterday
Performance for gpt-4.1-nano
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