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ling-3.0-flash-iq1
Ling-3.0-flash is InclusionAI's MIT-licensed hybrid reasoning MoE model
with 124B total parameters and 5.5B active parameters per token. It targets
coding, deep research, instruction following, and agentic workflows with a
native 256K-token context window.
This default entry uses the 36.5 GB AD-IQ1_M GGUF. A higher-quality
44.7 GB AD-IQ2_XS model is available as a variant.
Repository: localaiLicense: mit
carbon-3b-q4
Carbon-3B is Hugging Face's 3B-parameter genomic foundation model for DNA
and RNA sequence generation, recovery, variant-effect prediction, and
motif-perturbation analysis. It supports 32,768 tokens natively and uses a
hybrid tokenizer with 6-mer DNA tokens.
This default entry uses the Q4_K_M GGUF. A higher-quality Q8_0 build is
available as a variant. Prefix DNA sequences with `` and use uppercase
A, C, G, and T characters in groups of six.
Repository: localaiLicense: apache-2.0
carbon-8b-q4
Carbon-8B is the largest model in Hugging Face's Carbon family of genomic
foundation models. It targets DNA and RNA sequence generation, recovery,
variant-effect prediction, and motif-perturbation analysis with a native
context length of 32,768 hybrid 6-mer DNA tokens.
This default entry uses the Q4_K_M GGUF. A higher-quality Q8_0 build is
available as a variant. Prefix DNA sequences with `` and use uppercase
A, C, G, and T characters in groups of six.
Repository: localaiLicense: apache-2.0
qwen3.8-27b-q4
Qwen3.8-27B is Qwen's dense 27B vision-language model for reasoning,
coding, tool use, and long-running agent tasks. It accepts text, images,
and video, and it supports a native context window of 262K tokens.
This default entry uses the official Q4_K_M GGUF and Q8_0 vision
projector. The linked variants add MTP speculative decoding or use the
higher-quality Q8_0 model.
Repository: localaiLicense: apache-2.0
qwen3.8-9b-q4
Qwen3.8-9B is Empero AI's full-parameter distillation of Qwen3.8 2.4T
A95B into the dense Qwen3.5-9B architecture. It targets reasoning,
mathematics, coding, instruction following, and tool use, and supports a
native 262K-token context window. This default entry uses Q4_K_M weights;
a higher-quality Q8_0 build is available as a variant.
Repository: localaiLicense: apache-2.0
qwen3.8-4b-q4
Qwen3.8-4B is Empero AI's full-parameter distillation of Qwen3.8 2.4T
A95B into the Qwen3.5-4B architecture. It targets mathematics, reasoning,
instruction following, and tool use with a native 262K-token context
window. This default entry uses Q4_K_M weights; a higher-quality Q8_0
build is available as a variant.
Repository: localaiLicense: apache-2.0
qwen3.8-2b-q4
Qwen3.8-2B is Empero AI's smallest Qwen3.8 reasoning distillation. It uses
the Qwen3.5-2B architecture and targets mathematics, instruction
following, tool use, and edge deployment with a native 262K-token context
window. This default entry uses Q4_K_M weights; a higher-quality Q8_0
build is available as a variant.
Repository: localaiLicense: apache-2.0
kimi-k3
π°Β Β Tech Blog | Β Β Β πΒ Β Full Report
## 1. Model Introduction
Kimi K3 is an open-weight, native multimodal agentic model and our most capable model to date. It is a 2.8T-parameter model built on Kimi Delta Attention (KDA) and Attention Residuals (AttnRes), with native vision capabilities and a 1-million-token context window. It is the world's first open 3T-class model, designed for frontier intelligence across long-horizon coding, knowledge work, and reasoning.
...
Repository: localaiLicense: other
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-v7-mtp-apex
Qwen3.6-35B-A3B Genesis Hermes V7 in the full APEX GGUF format with native
multi-token prediction enabled for speculative decoding, plus the shared
F16 multimodal projector.
Repository: localaiLicense: apache-2.0
qwen3.6-35b-a3b-genesis-hermes-v7-mtp-apex-compact
Qwen3.6-35B-A3B Genesis Hermes V7 in the smaller APEX Compact GGUF format
with native multi-token prediction enabled for speculative decoding, plus
the shared F16 multimodal projector.
Repository: localaiLicense: apache-2.0
qwythos-27b-v1-mtp
Qwythos-27B-v1 MTP is the Q4_K_M build with its native multi-token
prediction head enabled for faster speculative decoding. It also includes
the shared vision projector and supports tool use and long-context
reasoning.
Repository: localaiLicense: apache-2.0
qwythos-9b-v2
Empero AI
# Qwythos-9B-v2 β the new and improved Qwythos
The next iteration of Qwythos: **all the reasoning of Qwythos-9B, with the looping behavior fixed.** v2 keeps the deep chain-of-thought, the uncensored research posture, and the 1M-token context of its predecessor, and cleans up the rough edges that showed up in real use.
- π **Looping behavior eliminated** β repetition/degeneration under greedy or low-temperature decoding dropped from **6.7% β 0%**. You can serve it *without* leaning on `repetition_penalty` as a band-aid.
- π§ **Reasoning fully preserved** β MMLU, GSM8K, GPQA, ARC and HumanEval are all held at (or above) the v1 level. This is a *hygiene* upgrade, not a capability regression.
- 𧩠**MTP head restored** β the native multi-token-prediction module (dropped in the previous export) is back, so config and weights agree and speculative-decoding setups work.
- πͺͺ **Cleaner identity** β the model no longer prefaces unrelated answers with its identity; it introduces itself only when you actually ask.
- π **Still intentionally uncensored** for research, cybersecurity, red-teaming, biology, chemistry, pharmacology and clinical work.
- π **St
...
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**
δΈζθ―΄ζ
**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)** β more reliable XML / function-calling style tool use on top of MiniCPM5's native format
- **Coding** β code generation, debugging, and software-engineering-style tasks
- **Instruction following** β more reliable adherence to user prompts and structured constraints
- **Thinking mode** β chain-of-thought reasoning via the MiniCPM5 chat template
- **Long context** β up to **128K tokens** (131,072 tokens per `config.json`)
...
Repository: localaiLicense: apache-2.0
ternary-bonsai-8b-q2-g64
Ternary Bonsai 8B (PrismML), GGUF Q2_0 with group-64 packing (each FP16 scale shared
across 64 weights instead of 128). Slightly larger (~2.31 GB) but matches llama.cpp's
native 64-value Q2_0 block layout. Runs on LocalAI's `bonsai` backend. License: Apache 2.0.
Repository: localaiLicense: apache-2.0
ternary-bonsai-27b-q2-g64
Ternary Bonsai 27B (PrismML), GGUF Q2_0 with group-64 packing (~7.59 GB), matching
llama.cpp's native 64-value Q2_0 block layout, with the 4-bit vision tower (mmproj)
included. Runs on LocalAI's `bonsai` backend. License: Apache 2.0.
Repository: localaiLicense: apache-2.0
minicpm5-1b-claude-opus-fable5-thinking
# MiniCPM5-1B-Claude-Opus-Fable5-Thinking
GGUF quantizations for local deployment: **MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF**
δΈζθ―΄ζ
**MiniCPM5-1B-Claude-Opus-Fable5-Thinking** is a compact 1B **Thinking** language model built on openbmb/MiniCPM5-1B. It is further fine-tuned on **Fable 5** data to improve **coding** and **instruction-following** while keeping MiniCPM5's native Thinking chat template and tool-call format.
For llama.cpp / Ollama / LM Studio deployment, see the **GGUF repository**.
## Overview
## Capabilities
- **Coding** β code generation, debugging, and software-engineering-style tasks
- **Instruction following** β more reliable adherence to user prompts and structured constraints
- **Thinking mode** β chain-of-thought reasoning via the MiniCPM5 chat template
- **Tool calling** β inherits MiniCPM5's XML tool-call format
- **Long context** β up to **128K tokens** (131,072 tokens per `config.json`)
## Quick start
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_id = "GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking"
...
Repository: localaiLicense: apache-2.0
qwopus3.6-35b-a3b-coder-mtp
# π Qwopus3.6-35B-A3B-v1
## π‘ Base Model Overview
**Qwen3.6-35B-A3B** is an advanced hybrid sparse MoE (Mixture-of-Experts) model developed by Alibaba Cloud. It features 35B total parameters with only 3B active parameters per token, ensuring high inference efficiency. Architecturally, it combines Gated DeltaNet linear attention with standard gated attention layers, routing tokens across **256 experts**. It natively supports a massive **262k context window** and is specifically designed for high-performance agentic coding, deep reasoning, and multimodal tasks.
## π Model Refinement & Logic Tuning οΌQwopus3.6-35B-A3B-v1οΌ
πͺ**Qwopus3.6-35B-A3B-v1** is a reasoning-enhanced MoE (Mixture of Experts) model fine-tuned on top of **Qwen3.6-35B-A3B**.
### π Training Strategy
The fine-tuning process for this model is structured into **three distinct stages of distributed SFT (Supervised Fine-Tuning)**, progressively scaling reasoning complexity and data diversity. This systematic approach ensures the model inherits the base MoE capabilities while sharpening its logic-handling depth.
...
Repository: localaiLicense: apache-2.0
qwen-agentworld-35b-a3b
# Qwen-AgentWorld-35B-A3B
π Technical Report |
π Blog |
π€ Hugging Face |
π€ ModelScope |
π» GitHub |
π₯οΈ Demo
> [!Note]
> This repository contains the model weights and configuration files for **Qwen-AgentWorld-35B-A3B**, a native language world model trained for agentic environment simulation.
>
> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, etc.
**Qwen-AgentWorld** is the first language world model to cover seven agent interaction domains within a single model. It simulates agentic environments via long chain-of-thought reasoning, predicting the next environment state given an agent's action and interaction history. Trained through a three-stage pipeline β CPT injects environment knowledge, SFT activates next-state-prediction reasoning, RL sharpens simulation fidelity β Qwen-AgentWorld is a **native world model**: environment modeling is the training objective from the CPT stage onward, not a post-hoc add-on.
## Highlights
...
Repository: localaiLicense: apache-2.0
laguna-xs-2.1
Laguna XS 2.1 is Poolside's 33B-parameter, 3B-active Mixture-of-Experts model for agentic coding and long-horizon work on local machines. It supports tool use, interleaved reasoning, and a native 262K-token context window. This default entry uses the official 20.3 GB Q4_K_M GGUF.
License: OpenMDW 1.1.
Repository: localaiLicense: other
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