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Model details
Amazon: Nova Micro 1.0
Amazon Nova Micro 1.0 is a text-only large language model engineered specifically for applications demanding ultra-low latency and exceptional cost efficiency. Positioned as the fastest option within the Amazon Nova family, it prioritizes responsive interactions and throughput over broader multimodal capabilities. Its architecture is streamlined for text processing, with a substantial context window allowing it to handle long conversations, process extensive documents, and manage multi-step reasoning tasks without sacrificing speed. The model is particularly suited for real-time interactive chat, text summarization, translation, and content classification workflows where quick turnaround matters more than reasoning depth.
Designed as an accessible entry point in the Nova lineup, Nova Micro 1.0 delivers frontier-level text intelligence at a fraction of the cost of larger models, making enterprise-grade language processing viable for organizations of all sizes. While its mathematical reasoning and coding abilities are characterized as straightforward rather than advanced, the model holds its own for simpler coding tasks and basic problem-solving. It sits alongside tool calling and temperature control options, giving developers flexibility in how they deploy it. Notably, this model represents the first generation of the Nova family, and those seeking newer workloads may consider Nova 2 variants for more recent advancements—but for cost-sensitive, latency-critical text applications, Micro remains a practical choice.
Quick Info
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- Kilo Gateway
- Model key
- amazon/nova-micro-v1
- Release date
- Dec 5, 2024
- Last updated
- Dec 5, 2024
- Input modalities
- Output modalities
- Capabilities
Cost
- Input token cost
- $0.035
- Output token cost
- $0.14
Limits
- Output tokens
- 5,120 tokens
- Context window
- 128,000 tokens
Transparent token rates
Compare Amazon: Nova Micro 1.0 pricing
Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
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