amazon.nova-micro-v1:0 is a budget-tier language model from Amazon Bedrock. amazon.nova-micro-v1:0 is a proprietary model available exclusively through Amazon Bedrock's API. Amazon Nova is AWS's proprietary model family, tightly integrated with the Bedrock platform — optimized for enterprise AWS workloads with strong multimodal support and competitive pricing.
amazon.nova-micro-v1:0 is priced at $0.035/1M input tokens and $0.14/1M output tokens. Output tokens are 4× more expensive than input tokens — this ratio reflects the sequential nature of autoregressive generation, which requires a separate forward pass per output token versus parallel processing of all input tokens simultaneously. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, amazon.nova-micro-v1:0 costs approximately $0.11 per 1,000 API calls. Amazon Bedrock does not publish a prompt caching rate for this model, so repeated long contexts are billed at the standard $0.035/1M input rate.
Its 128K-token context window handles most long-document tasks — roughly 75,000 words or a full novel — without requiring chunking or retrieval augmentation. Median latency (P50 time-to-first-token) is approximately 150ms — fast enough for real-time interactive applications. Throughput is approximately 500 tokens/second — fast enough to stream responses at reading speed with headroom for concurrent requests. Maximum output length is 5K tokens — adequate for most generation tasks including essays, code functions, and detailed responses.
amazon.nova-micro-v1:0 is best suited to cost, speed. Supported capabilities include function calling / tool use for agentic workflows, streaming token output for real-time UIs. Function calling support makes it suitable for building AI agents, structured data extraction pipelines, and any workflow requiring the model to invoke external APIs or return typed JSON. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how amazon.nova-micro-v1:0 compares to similar models across these dimensions.
amazon.nova-micro-v1:0 sits in the budget tier — the most cost-efficient models, best for high-volume simple tasks, classification, extraction, and applications where cost per call is the primary constraint. Unlike open-weights alternatives, amazon.nova-micro-v1:0 is only available via Amazon Bedrock's API — there is no self-hosted option, which simplifies deployment but creates vendor dependency. When comparing amazon.nova-micro-v1:0 to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (35/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.
Composite quality score based on reasoning, coding, and instruction-following benchmarks.
Input price vs 119 budget models tracked. Avg: $0.110/1M.
| Model ID | amazon.nova-micro-v1:0 |
| Provider | Amazon Bedrock |
| Model Family | Amazon Nova |
| Tier | Budget |
| Context Window | 128,000 tokens (128K) |
| Max Output Tokens | 5,120 tokens |
| Input Price | $0.035 / 1M tokens |
| Output Price | $0.14 / 1M tokens |
| Cached Input Price | Not available |
| Throughput | 500 tokens/sec |
| Latency (P50) | 150ms |
| Intelligence Score | 35/100 |
| LiveBench Score | — |
| Cost per Task (LiveBench) | — |
| Data Confidence | — |
| HLE Score | — |
| GPQA Diamond | — |
| SWE-bench Score | — |
| OSWorld Score | — |
| BrowseComp Score | — |
| Terminal-Bench Score | — |
| AutoBench Score | — |
| Parameters | — |
| Vision Support | No |
| Function Calling | Yes |
| Streaming | Yes |
| Reasoning Model | No |
| Open Weights | No |
| Data Source | Static (verified) |
| Last Updated | 2026-07-01 |
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Self-hosting amazon.nova-micro-v1:0? These GPUs are well-matched for this model's compute and memory requirements.