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diplodocus-preview-q4
Diplodocus preview 4 is OsaurusAI's K2 Horizon 7B fine-tune for documents,
spreadsheets, and tool-assisted tasks. This Q4_K_M GGUF build uses the
embedded chat template and enables reasoning by default. Applications
must provide the tools; the model download does not include workspace tools.
Repository: localaiLicense: apache-2.0
diplodocus-preview-q6
Diplodocus preview 4 is OsaurusAI's K2 Horizon 7B fine-tune for documents,
spreadsheets, and tool-assisted tasks. This Q6_K GGUF build uses the
embedded chat template and enables reasoning by default. Applications
must provide the tools; the model download does not include workspace tools.
Repository: localaiLicense: apache-2.0
diplodocus-preview-q8
Diplodocus preview 4 is OsaurusAI's K2 Horizon 7B fine-tune for documents,
spreadsheets, and tool-assisted tasks. This Q8_0 GGUF build uses the
embedded chat template and enables reasoning by default. Applications
must provide the tools; the model download does not include workspace tools.
Repository: localaiLicense: apache-2.0
underdog-saluki-27b-1.0-abliterated
Kujira's abliterated adaptation of Underdog Saluki 27B 1.0 uses mixed
IQ2 weights with an embedded MTP head. This text-only llama.cpp build
uses ordinary decoding; the MTP variant enables speculative decoding.
Repository: localaiLicense: apache-2.0
underdog-saluki-27b-1.0-abliterated-mtp
Kujira's abliterated adaptation of Underdog Saluki 27B 1.0 uses mixed
IQ2 weights with an embedded MTP head. This text-only llama.cpp build
enables multi-token prediction with up to two draft tokens.
Repository: localaiLicense: apache-2.0
underdog-saluki-27b-1.0-mtp
Underdog Saluki 27B 1.0 with its mixed IQ2 main weights preserved and
a Qwen3.8-27B MTP head added. This llama.cpp build enables multi-token
prediction with up to two draft tokens and includes the F16 vision
projector. The weights and projector total approximately 9.28 GB.
Repository: localaiLicense: apache-2.0
underdog-saluki-27b-1.0
Underdog Saluki 27B 1.0 is a mixed IQ2 quantization of Qwen3.8-27B
for chat, reasoning, and tool use. This llama.cpp build includes the
F16 vision projector and uses the embedded chat template.
The weights and projector total approximately 8.83 GB before runtime memory.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-uncensored-genesis-hermes-v6
Qwen3.6-35B-A3B Uncensored Genesis Hermes V6 is LuffyTheFox's multimodal,
agentic derivative of HauhauCS's uncensored Qwen3.6-35B-A3B model. It
combines Genesis tensor calibration with Hermes function-calling data while
retaining the 35B mixture-of-experts architecture, roughly 3B active
parameters per token, and the native 262K-token context window.
This entry installs the Q8_0 GGUF together with its F16 multimodal projector
for llama.cpp. The model card recommends Jinja chat templates and at least a
128K context for its thinking behavior. License: Apache-2.0.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-genesis-hermes-v7
Qwen3.6-35B-A3B Genesis Hermes V7 is LuffyTheFox's Apache-2.0 multimodal,
agentic derivative of HauhauCS's uncensored Qwen3.6-35B-A3B model. It
combines Genesis tensor calibration with Hermes function-calling data while
retaining the 35B mixture-of-experts architecture, roughly 3B active
parameters per token, and the native 262K-token context window.
This entry's own payload uses the model card's recommended APEX GGUF and the
shared F16 multimodal projector. Automatic variant selection may instead
choose Compact APEX, an MTP-enabled APEX build, or Q8_K_P based on serving
features and available memory. The model card recommends Jinja chat
templates and at least a 128K context for its thinking behavior.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-genesis-hermes-final
Qwen3.6-35B-A3B Genesis Hermes Final is a multimodal mixture-of-experts
model with 35B total parameters and about 3B active per token. This
uncensored derivative combines the HauhauCS base with Hermes
function-calling data and the author's Genesis weight processing.
This build uses APEX and includes the F16 vision projector.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-genesis-hermes-final-apex-compact
Qwen3.6-35B-A3B Genesis Hermes Final is a multimodal mixture-of-experts
model with 35B total parameters and about 3B active per token. This
uncensored derivative combines the HauhauCS base with Hermes
function-calling data and the author's Genesis weight processing.
This build uses APEX Compact and includes the F16 vision projector.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-genesis-hermes-final-mtp-apex
Qwen3.6-35B-A3B Genesis Hermes Final is a multimodal mixture-of-experts
model with 35B total parameters and about 3B active per token. This
uncensored derivative combines the HauhauCS base with Hermes
function-calling data and the author's Genesis weight processing.
This build uses APEX and includes the F16 vision projector.
Native multi-token prediction is enabled for speculative decoding.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-genesis-hermes-final-mtp-apex-compact
Qwen3.6-35B-A3B Genesis Hermes Final is a multimodal mixture-of-experts
model with 35B total parameters and about 3B active per token. This
uncensored derivative combines the HauhauCS base with Hermes
function-calling data and the author's Genesis weight processing.
This build uses APEX Compact and includes the F16 vision projector.
Native multi-token prediction is enabled for speculative decoding.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-genesis-hermes-final-q8-k-p
Qwen3.6-35B-A3B Genesis Hermes Final is a multimodal mixture-of-experts
model with 35B total parameters and about 3B active per token. This
uncensored derivative combines the HauhauCS base with Hermes
function-calling data and the author's Genesis weight processing.
This build uses Q8_K_P and includes the F16 vision projector.
Repository: localaiLicense: apache-2.0
minicpm5-1b-claude-opus-fable5-v2-thinking
# MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking
GGUF quantizations for local deployment: **MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking-GGUF**
中文说明
**MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking** is a compact 1B **Thinking** language model built on openbmb/MiniCPM5-1B. Compared with V1, this V2 release is further fine-tuned on **Fable 5** data with a stronger focus on **tool calling / function calling**, while also improving **coding** and **instruction-following**. It keeps MiniCPM5's native Thinking chat template and XML tool-call format.
Previous version: **MiniCPM5-1B-Claude-Opus-Fable5-Thinking** (V1)
For llama.cpp / Ollama / LM Studio deployment, see the **GGUF repository**.
## Overview
## Capabilities
- **Tool calling (enhanced in V2)** — more reliable XML / function-calling style tool use on top of MiniCPM5's native format
- **Coding** — code generation, debugging, and software-engineering-style tasks
- **Instruction following** — more reliable adherence to user prompts and structured constraints
- **Thinking mode** — chain-of-thought reasoning via the MiniCPM5 chat template
- **Long context** — up to **128K tokens** (131,072 tokens per `config.json`)
...
Repository: localaiLicense: apache-2.0
lfm2.5-1.2b-nova-function-calling
The **LFM2.5-1.2B-Nova-Function-Calling-GGUF** is a quantized version of the original model, optimized for efficiency with **Unsloth**. It supports text and multimodal tasks, using different quantization levels (e.g., Q2_K, Q3_K, Q4_K, etc.) to balance performance and memory usage. The model is designed for function calling and is faster than the original version, making it suitable for tasks like code generation, reasoning, and multi-modal input processing.
Repository: localaiLicense: apache-2.0
granite-4.2-3b:vllm
Granite 4.2 3B is IBM's compact dense reasoning model for code generation,
tool calling, agentic workflows, multilingual chat, and long-context tasks.
This entry serves the bfloat16 safetensors with vLLM and supports a
128K-token context. It is the smallest fallback in a family that also offers
the higher-capacity 8B and 30B checkpoints as variants.
Repository: localaiLicense: apache-2.0
granite-4.2-8b:vllm
Granite 4.2 8B is IBM's mid-sized dense reasoning model for code generation,
tool calling, agentic workflows, multilingual chat, and long-context tasks.
This entry serves the higher-capacity bfloat16 safetensors with vLLM and
supports a 128K-token context.
Repository: localaiLicense: apache-2.0
granite-4.2-30b:vllm
Granite 4.2 30B is IBM's largest dense Granite 4.2 reasoning model for code
generation, tool calling, agentic workflows, multilingual chat, and
long-context tasks. This entry serves the bfloat16 safetensors with vLLM and
supports a 128K-token context.
Repository: localaiLicense: apache-2.0
ibm-granite_granite-4.0-h-small
Granite-4.0-H-Small is a 32B parameter long-context instruct model finetuned from Granite-4.0-H-Small-Base using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets. This model is developed using a diverse set of techniques with a structured chat format, including supervised finetuning, model alignment using reinforcement learning, and model merging. Granite 4.0 instruct models feature improved instruction following (IF) and tool-calling capabilities, making them more effective in enterprise applications.
Repository: localaiLicense: apache-2.0
ibm-granite_granite-4.0-h-tiny
Granite-4.0-H-Tiny is a 7B parameter long-context instruct model finetuned from Granite-4.0-H-Tiny-Base using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets. This model is developed using a diverse set of techniques with a structured chat format, including supervised finetuning, model alignment using reinforcement learning, and model merging. Granite 4.0 instruct models feature improved instruction following (IF) and tool-calling capabilities, making them more effective in enterprise applications.
Repository: localaiLicense: apache-2.0
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