Meta vs Tencent: Token Pricing, Speed & Intelligence
Full comparison of Meta and Tencent — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Meta
Llama 4 & Muse Spark — the world's most widely deployed open-weight models
Meta AI is the creator of the Llama model family, the most widely used open-weight LLMs in the world. Llama models are available via Meta's own API and through dozens of third-party inference providers. The Llama 4 series includes Behemoth (2T params), Scout, and Maverick, with 1M-token context windows. Meta also offers Muse Spark, a proprietary multimodal model. Because Llama weights are open, teams can self-host on GPU cloud for dramatically lower per-token costs at scale.
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
Meta
Tencent
Key differentiators
Frequently asked questions
Meta FAQs
What is the Llama 4 context window?
Llama 4 Scout and Maverick support 1,000,000-token (1M) context windows. Llama 4 Behemoth also targets 1M context. This makes Llama 4 competitive with Gemini 1.5 Pro for long-document and multi-document tasks.
How much does the Meta Llama API cost?
Llama 3.2 1B is $0.02/1M tokens in/out. Llama 3.2 3B is $0.03/$0.05. Llama 3.1 8B is $0.02/$0.05. Llama 3.2 90B Vision is $1.20/$1.20. Muse Spark 1.1 is $1.25/$4.25. Llama 4 Behemoth pricing is not yet publicly listed.
Can I self-host Llama models?
Yes — all Llama 3.x and Llama 4 Scout/Maverick weights are publicly available under the Llama Community License. You can run them on any GPU cloud provider. A single H100 at ~$2.50/hr can serve Llama 3.1 8B at very high throughput, making self-hosting cost-effective above ~10M tokens/day.
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
Meta — Llama 4 & Muse Spark — the world's most widely deployed open-weight models
Meta AI is the creator of the Llama model family, the most widely used open-weight LLMs in the world. Llama models are available via Meta's own API and through dozens of third-party inference providers. The Llama 4 series includes Behemoth (2T params), Scout, and Maverick, with 1M-token context windows. Meta also offers Muse Spark, a proprietary multimodal model. Because Llama weights are open, teams can self-host on GPU cloud for dramatically lower per-token costs at scale.
The only frontier-class model family available as open weights — enabling self-hosted inference on GPU cloud at a fraction of API pricing for high-volume workloads.
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
Meta
- ▸Open-weight models — self-host on any GPU cloud for lowest per-token cost at scale
- ▸Llama 4 Behemoth: 2T parameter frontier model with 1M context window
- ▸Widest third-party hosting ecosystem — available on AWS, Azure, GCP, Together AI, Groq, and 20+ others
Tencent
- ▸Competitive pricing
- ▸Strong Chinese-language performance
- ▸Large context window
Provider category context
Meta is a open source host, founded in 2023. Tencent is a frontier lab, founded in 2023. The category difference means these providers serve partially overlapping use cases — compare the model lists and pricing tables above to find the best fit for your specific workload.
How to choose between them
Choose Meta if you need open-weight models — self-host on any gpu cloud for lowest per-token cost at scale. Choose Tencent if you need competitive pricing. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.