Compare Grok 4.5 from Grok and tencent/Hunyuan-MT-7B from Hunyuan on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
Grok 4.5
tencent/Hunyuan-MT-7BGrok 4.5 was trained on datasets spanning knowledge in coding, science, engineering, and math. With both intelligent and efficient reasoning, Grok 4.5 excels at real engineering tasks and exceeds comparable leading models at these tasks.
Hunyuan-MT-7B is a lightweight translation model with 7 billion parameters, designed to translate source text into target languages. The model supports translation among 33 languages as well as 5 Chinese minority languages. In the WMT25 International Machine Translation Competition, Hunyuan-MT-7B achieved first place in 30 out of 31 language categories it participated in, demonstrating its exceptional translation capabilities. For translation scenarios, Tencent Hunyuan proposed a complete training paradigm from pre-training to supervised fine-tuning, followed by translation reinforcement and ensemble reinforcement, enabling it to achieve industry-leading performance among models of similar scale. The model is computationally efficient, easy to deploy, and suitable for various application scenarios.
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
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tencent/Hunyuan-MT-7B: $0.2/M output tokens; Grok 4.5: $6/M. Use the cost calculator above to estimate your own workload.
Grok 4.5: 4.4s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
Grok 4.5 at 34.2 tok/s and tencent/Hunyuan-MT-7B at 8.4 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
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