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Side-by-side comparison of API pricing, context window, latency, and benchmark performance. Data refreshed daily from provider APIs and ModelStop's own latency probes.
💰granite-4.0-h-micro is 91% cheaper than Meituan: LongCat Flash Chat
⚡Meituan: LongCat Flash Chat is 541ms faster than granite-4.0-h-micro
Price (lower is better), Speed/Latency (lower is better), Performance (higher is better)
granite-4.0-h-micro is 1076% cheaper
| Spec | granite-4.0-h-micro | Meituan: LongCat Flash Chat |
|---|---|---|
| Provider | ibm-granite | meituan |
| Input price / 1M tokens | $0.02 | $0.20 |
| Output price / 1M tokens | $0.11 | $0.80 |
| Context window | 131k tokens | 131k tokens |
| Latency (p50) | 541ms | — |
| Best benchmark score | — | — |
| Open source | No | No |
Granite 4.0 instruct models deliver strong performance across benchmarks, achieving industry-leading results in key agentic tasks like instruction following and function calling. These efficiencies make the models well-suited for a wide range of use cases like retrieval-augmented generation (RAG), multi-agent workflows, and edge deployments.
LongCat-Flash-Chat is a large-scale Mixture-of-Experts (MoE) model with 560B total parameters, of which 18.6B–31.3B (≈27B on average) are dynamically activated per input. It introduces a shortcut-connected MoE design to reduce...
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