Moonshot AI vs Tencent: Token Pricing, Speed & Intelligence
Full comparison of Moonshot AI and Tencent — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Moonshot AI
Kimi — long-context frontier models from China's leading AI lab
Moonshot AI is a Chinese AI startup behind the Kimi model family. Kimi K2 is a 1-trillion-parameter MoE model released as open-weight, competitive with frontier models on coding and agentic tasks. The Kimi API offers long-context processing up to 128K tokens with competitive pricing.
Tencent
Hunyuan LLMs from China's largest tech company
Tencent offers the Hunyuan series of large language models via its cloud platform. Hunyuan models are optimised for Chinese and multilingual tasks, with strong performance on coding and reasoning benchmarks.
Key metrics
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Live token pricing
Strengths & weaknesses
Moonshot AI
Tencent
Key differentiators
Kimi K2 is a 1-trillion-parameter open-weight MoE model that scores competitively with Claude Sonnet on coding and agentic benchmarks.
Hunyuan 3 (hy3) offers a 262K context window at $0.14/1M input tokens — among the cheapest frontier-class models available.
Frequently asked questions
Moonshot AI FAQs
What is Kimi K2?
Kimi K2 is a 1-trillion-parameter mixture-of-experts model from Moonshot AI, released as open-weight. It activates approximately 32B parameters per token and is designed for coding, agentic tasks, and long-context reasoning.
Is Kimi K2 open-weight?
Yes. Kimi K2 weights are publicly available on Hugging Face, making it one of the largest open-weight models available. Teams can self-host it on multi-GPU clusters or access it via the Moonshot API.
How does Kimi K2 compare to Claude Sonnet?
Kimi K2 scores competitively with Claude Sonnet 4 on coding benchmarks including SWE-bench. It is particularly strong on agentic tasks that require tool use and multi-step planning.
Tencent FAQs
What is Tencent Hunyuan?
Hunyuan is Tencent's family of large language models, available via the Tencent Cloud API. The latest generation (hy3) supports 262K context and competitive pricing.
Is Tencent Hunyuan available internationally?
Yes. The Hunyuan API is accessible globally via Tencent Cloud, though latency may be higher outside Asia-Pacific regions.
Provider resources
Moonshot AI — Kimi — long-context frontier models from China's leading AI lab
Moonshot AI is a Chinese AI startup behind the Kimi model family. Kimi K2 is a 1-trillion-parameter MoE model released as open-weight, competitive with frontier models on coding and agentic tasks. The Kimi API offers long-context processing up to 128K tokens with competitive pricing.
Kimi K2 is a 1-trillion-parameter open-weight MoE model that scores competitively with Claude Sonnet on coding and agentic benchmarks.
Tencent — Hunyuan LLMs from China's largest tech company
Tencent offers the Hunyuan series of large language models via its cloud platform. Hunyuan models are optimised for Chinese and multilingual tasks, with strong performance on coding and reasoning benchmarks.
Hunyuan 3 (hy3) offers a 262K context window at $0.14/1M input tokens — among the cheapest frontier-class models available.
Key strengths compared
Moonshot AI
- ▸Kimi K2 is a 1T MoE open-weight model with strong coding scores
- ▸Competitive on agentic and tool-use benchmarks
- ▸Long-context support up to 128K tokens
Tencent
- ▸Competitive pricing
- ▸Strong Chinese-language performance
- ▸Large context window
Provider category context
Moonshot AI is a frontier lab, founded in 2023. Tencent is a frontier lab, founded in 2023. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Moonshot AI and Tencent are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: Moonshot AI leads on kimi k2 is a 1t moe open-weight model with strong coding scores, while Tencent leads on competitive pricing. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.