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Granite 4.0 Micro is a 3B-parameter dense language model from IBM’s Granite 4.0 family, optimized for low-latency, cost-efficient workloads and local or edge deployment.
Output tokens per second · Higher is better
Seconds · Lower is better
USD per 1M tokens (blended) · Lower is better
About the model
Granite 4.0 Micro is a compact, 3B-parameter transformer-based language model in IBM’s Granite 4.0 series, designed as a dense alternative to the hybrid Mamba-2/transformer variants. It is mainly used for lightweight conversational assistants, instruction following, and general-purpose text generation in resource-constrained environments. It is also suited for agentic workflows, including fast function-calling and serving as the text backbone for add-on capabilities like Granite 4.0 3B Vision. As part of the broader IBM Granite family of foundation models, Granite 4.0 Micro follows earlier Granite generations (such as Granite 3.x) while emphasizing open, enterprise-ready deployment.
Model capabilities
Executes general natural language instructions for diverse tasks, serving as a foundation for building AI assistants across business domains.
Supports function and tool calling within agentic workflows, enabling integration with external APIs like weather or business systems.
Performs long-context text-to-text generation for drafting, summarization, and dialogue, using a compact 3B-parameter decoder-only architecture.
Processes and generates text in multiple languages, suitable for globally deployed enterprise applications requiring multilingual communication capabilities.
Acts as the text backbone for a 3B Vision LoRA adapter, enabling multimodal document and structured data understanding when combined.
Use cases
Transparent pricing
LLM API offers the lowest cost and highest performance for Granite 4.0 Micro–class models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 80ms | 120 tps | 99.99% | $0.04 | $0.04 | 128K |
| IBM watsonx | Global | ~220ms | ~40 tps | 99.9% | ~$0.30 | ~$0.30 | 32K |
| AWS Bedrock | US East | ~190ms | ~55 tps | 99.9% | ~$0.25 | ~$0.25 | 32K |
| Azure AI Studio | EU West | ~200ms | ~50 tps | 99.9% | ~$0.28 | ~$0.28 | 32K |
Performance benchmarks
| Metric | Granite 4.0 Micro | OpenAI o3-mini | Anthropic Claude 3.5 Haiku |
|---|---|---|---|
| Avg Latency | ~220ms | ~250ms | ~230ms |
| Context Window | 128K | 200K | 200K |
| Input Price ($/1M) | $0.10 | $0.15 | $0.20 |
| Output Price ($/1M) | $0.40 | $0.60 | $0.80 |
| Max Output Tokens | 8K | 16K | 8K |
| Throughput | ~80 tps | ~100 tps | ~90 tps |
| Uptime | 99.9% | 99.9% | 99.9% |
30-day usage via LLM API
Architecture & Integration
One unified API. Every major model. Built-in reliability, cost control, and observability.
Dynamically route each request to the optimal model across providers based on latency, price, and quality—without changing your integration or redeploying.
One endpoint, any modelEnforce budgets, price caps, and per-team limits while automatically selecting cheaper equivalents when possible, so you avoid surprise bills as usage scales.
Predictable AI spendDefine provider- and model-level fallbacks that auto-trigger on errors, timeouts, or degraded quality, keeping your AI flows reliable in production.
No single point of failureGet per-request traces, latency, cost, and provider breakdowns in one place, so you can debug failures fast and tune prompts across models.
See every tokenExpress higher-level tasks like chat, tools, RAG, and workflows via one consistent API, while LLM.API orchestrates the best models under the hood.
Tasks, not glue codeSubmit large batches of requests across providers with automatic concurrency control and retry semantics, maximizing throughput without overwhelming your infrastructure.
Scale to millionsDecision guide
FAQ
Granite 4.0 Micro is an IBM small-footprint language model optimized for fast, low-cost text generation and assistant-style tasks.
It is best for lightweight chatbots, classification, short-form content generation, and on-demand reasoning where low latency and cost are priorities.
LLM.API charges per input and output token, with Granite 4.0 Micro positioned as a budget-friendly option compared to larger Granite variants.
Granite 4.0 Micro supports a mid-sized context window suitable for typical chat sessions and short documents, but not long reports or multi-document analysis.
Because of its compact size, Granite 4.0 Micro generally offers lower latency and faster first-token times than larger Granite 4.0 family models.
Granite 4.0 Micro is a text-only model, supporting text prompts and returning text completions or chat responses.
You select the IBM provider and the Granite 4.0 Micro model name in your LLM.API request, then send standard chat or completion payloads.
It trades some reasoning depth and output richness for lower cost and latency, making it better for high-traffic or resource-constrained applications.
It may struggle with very long contexts, complex multi-step reasoning, and highly specialized domain knowledge compared to larger frontier models.
If enabled by LLM.API, you can use its standard function-calling interface with Granite 4.0 Micro for structured tool invocation.
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