MODEL PROFILE

Falcon-H1-34B-Instruct-GGUF

tiiuae · Falcon-H1-34B-Instruct-GGUF

Falcon-H1 is a new series of large language models (LLMs) featuring a novel hybrid architecture that combines Transformer-based attention with State Space Models (SSMs) for superior long-context memory and computational efficiency. Released in multiple configurations (0.5B to 34B parameters), Falcon-H1 models demonstrate state-of-the-art performance and exceptional parameter and training efficiency. The flagship Falcon-H1-34B matches or outperforms models up to 70B scale, while smaller models also show strong performance relative to their size. These models excel across reasoning, mathematics, multilingual tasks, instruction following, and scientific knowledge, supporting up to 256K context tokens and 18 languages. All models are released under a permissive open-source license. For more details about the training protocol of this model, please refer to the Falcon-H1 technical blogpost and Technical Report. Currently to use this model you can either rely on Hugging Face `transformers`, `vLLM` or our custom fork of `llama.cpp` library.

Text generationlicense:other
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/31 12:20:58
OVERVIEW

Model overview

Falcon-H1 is a new series of large language models (LLMs) featuring a novel hybrid architecture that combines Transformer-based attention with State Space Models (SSMs) for superior long-context memory and computational efficiency. Released in multiple configurations (0.5B to 34B parameters), Falcon-H1 models demonstrate state-of-the-art performance and exceptional parameter and training efficiency. The flagship Falcon-H1-34B matches or outperforms models up to 70B scale, while smaller models also show strong performance relative to their size. These models excel across reasoning, mathematics, multilingual tasks, instruction following, and scientific knowledge, supporting up to 256K context tokens and 18 languages. All models are released under a permissive open-source license. For more details about the training protocol of this model, please refer to the Falcon-H1 technical blogpost and Technical Report. Currently to use this model you can either rely on Hugging Face `transformers`, `vLLM` or our custom fork of `llama.cpp` library.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

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Sources & traceability

许可证:other。模型介绍与第三方评测均以原来源的具体版本和方法为准。