Contenido
- 1 Los mejores modelos de IA locales 7B
- 1.0.1 Llama-3-8B-Instruct-32k-v0.1-GGUF
- 1.0.2 Mistral-7B-Instruct-v0.3-GGUF
- 1.0.3 Meta-Llama-3-8B-Instruct-GGUF
- 1.0.4 Parable-Granite-4.1-8B-Claude-Fable-5-GGUF
- 1.0.5 Bonsái ternario-8B-gguf
- 1.0.6 Qwen3.5-9B-DeepSeek-V4-Flash-GGUF
- 1.0.7 Parábola-Qwen3-8B-Claude-Fábula-5-GGUF
- 1.0.8 Qwen2.5-7B-Instruct-GGUF
- 1.0.9 Qwen2.5-VL-7B-Instrucciones-GGUF
- 1.0.10 Qwen2.5-Codificador-7B-Instrucciones-GGUF
- 1.0.11 Qwen3.5-9B-La-Fábula-Desafiante-Hereje-Sin-Censura-NEO-IMATRIX-MAX-MTP-GGUF
- 1.0.12 Meta-Llama-3.1-8B-Instruct-GGUF
- 1.0.13 Qwen3-8B-GGUF
- 1.0.14 Qwythos-9B-v2-GGUF
- 1.0.15 Qwen3.5-9B-Sin censura-HauhauCS-Agresivo
- 1.0.16 Qwen3-VL-8B-Instruct-abliterated-GGUF
- 1.0.17 Flux2-Klein-9B-Verdadero-V2
- 1.0.18 UI-TARS-1.5-7B-GGUF
- 1.0.19 vntl-llama3-8b-v2-gguf
- 1.0.20 Qwen3.5-9B-GGUF
- 1.0.21 Qwythos-9B-Claude-Mythos-5-1M-GGUF
- 1.0.22 Ornith-1.0-9B-GGUF
- 1.1 ¡Hola mucho gusto!
Los mejores modelos de IA locales 7B
Los modelos compactos de la gama 7B-9B son la opción ideal para ejecutarlos en un portátil o en una única GPU de consumo.
Llama-3-8B-Instruct-32k-v0.1-GGUF
Modelo de peso abierto 8B de MaziyarPanahi para inferencia de IA local.
Mistral-7B-Instruct-v0.3-GGUF
Modelo de peso abierto 7B de MaziyarPanahi para inferencia de IA local.
Meta-Llama-3-8B-Instruct-GGUF
Modelo de peso abierto 8B de MaziyarPanahi para inferencia de IA local.
Parable-Granite-4.1-8B-Claude-Fable-5-GGUF
Modelo de peso abierto 8B de AnkitAI para inferencia de IA local.
Bonsái ternario-8B-gguf
Modelo de ponderación abierta 8B de prism-ml para inferencia de IA local.
Qwen3.5-9B-DeepSeek-V4-Flash-GGUF
Modelo de ponderación abierta 9B de Jackrong para inferencia de IA local.
Parábola-Qwen3-8B-Claude-Fábula-5-GGUF
Modelo de peso abierto 8B de AnkitAI para inferencia de IA local.
Qwen2.5-7B-Instruct-GGUF
Modelo de ponderación abierta 7B de Alibaba para inferencia de IA local.
Qwen2.5-VL-7B-Instrucciones-GGUF
Modelo de ponderación abierta 7B de Alibaba para inferencia de IA local.
Qwen2.5-Codificador-7B-Instrucciones-GGUF
Modelo de ponderación abierta 7B de Qwen para inferencia de IA local.
Qwen3.5-9B-La-Fábula-Desafiante-Hereje-Sin-Censura-NEO-IMATRIX-MAX-MTP-GGUF
Modelo de ponderación abierta 9B de DavidAU para inferencia de IA local.
Meta-Llama-3.1-8B-Instruct-GGUF
Modelo de ponderación abierta 8B de Meta para inferencia de IA local.
Qwen3-8B-GGUF
Modelo de ponderación abierta 8B de Alibaba para inferencia de IA local.
Qwythos-9B-v2-GGUF
Modelo de ponderación abierta 9B de empero-ai para inferencia de IA local.
Qwen3.5-9B-Sin censura-HauhauCS-Agresivo
Modelo de peso abierto 9B de HauhauCS para inferencia de IA local.
Qwen3-VL-8B-Instruct-abliterated-GGUF
Qwen3-VL-8B-Instruct-abliterated-GGUF is an 8-billion parameter vision-language model developed by Alibaba that has been fully abliterated to remove proprietary constraints while retaining core capabilities. This model excels at handling complex visual reasoning and multi-step tasks within a conversational framework, making it ideal for open-ended analysis and creative generation in the US region. Running this GGUF quantized version locally is highly practical for users with mid-range GPUs, offering fast inference speeds without requiring specialized enterprise hardware.
Flux2-Klein-9B-Verdadero-V2
Modelo de ponderación abierta 9B de wikeeyang para inferencia de IA local.
UI-TARS-1.5-7B-GGUF
Modelo de ponderación abierta 7B de mradermacher para inferencia de IA local.
vntl-llama3-8b-v2-gguf
The vntl-llama3-8b-v2-gguf is an 8B parameter language model developed by lmg-anon that specializes in high-quality translation and conversational tasks. It excels at processing the VNTL-v5-1k dataset to deliver fluent responses, making it ideal for multilingual chat applications and localized content generation. Running this model locally requires a GPU with sufficient VRAM to handle its 8B parameter weight efficiently, ensuring responsive performance for real-time dialogue.
Qwen3.5-9B-GGUF
Qwen3.5-9B-GGUF is a compact large language model developed by Alibaba containing 9 billion parameters. It excels at conversational tasks and image-to-text conversion, making it ideal for lightweight applications that require efficient region US deployment. Running this model locally is practical on consumer-grade hardware thanks to its small footprint, offering fast inference speeds even on modest GPUs when paired with optimization libraries like Unsloth.
Qwythos-9B-Claude-Mythos-5-1M-GGUF
Modelo de ponderación abierta 9B de empero-ai para inferencia de IA local.
Ornith-1.0-9B-GGUF
Ornith-1.0-9B-GGUF is a 9-billion parameter language model developed by ornith-ai designed for conversational interactions within the US region. It excels at generating natural dialogue and handling casual chat tasks, making it ideal for lightweight virtual assistants or simple customer support bots. Running this model locally requires modest hardware resources, allowing it to operate quickly on consumer-grade GPUs without needing massive data centers.
