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ornith-1.0-9b-q4
Ornith-1.0-9B is an MIT-licensed Qwen3.5 model from Ornith AI for
agentic coding, reasoning, repository-level software tasks, and tool use.
It supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and F16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.0-9b-q8
Ornith-1.0-9B in the higher-quality Q8_0 GGUF format, with the shared F16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-9b-q4
Ornith-1.5-9B is an MIT-licensed Qwen3.5 model from Ornith AI for
agentic coding, reasoning, repository-level software tasks, and tool use.
It supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.5-9b-q8
Ornith-1.5-9B in the higher-quality Q8_0 GGUF format, with the shared BF16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-35b-a3b-q4
Ornith-1.5-35B-A3B is an MIT-licensed Qwen3.5 mixture-of-experts model
from Ornith AI for agentic coding, reasoning, repository-level software
tasks, and tool use. It activates about 3B parameters per token and
supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.5-35b-a3b-q8
Ornith-1.5-35B-A3B in the higher-quality Q8_0 GGUF format, with the shared
BF16 vision projector for multimodal prompts.
Repository: localaiLicense: mit
tiel-coder-35b-a3b-q4
Tiel-Coder-35B-A3B is a 35B-parameter mixture-of-experts model for coding,
reasoning, tool use, and vision tasks. This default entry uses the
Q4_K_XL GGUF and BF16 vision projector.
Repository: localaiLicense: mit
tiel-coder-35b-a3b-q4-mtp
Tiel-Coder-35B-A3B in Q4_K_XL format with MTP speculative decoding and a
BF16 vision projector.
Repository: localaiLicense: mit
tiel-coder-35b-a3b-q8
Tiel-Coder-35B-A3B in the higher-quality Q8_K_XL GGUF format, with the
BF16 vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-397b-q4
Ornith-1.5-397B is Ornith AI's MIT-licensed flagship mixture-of-experts
model for agentic coding, reasoning, repository-level tasks, and tool use.
It supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.5-397b-q8
Ornith-1.5-397B in the higher-quality Q8_0 GGUF format, with the shared
BF16 vision projector for multimodal prompts.
Repository: localaiLicense: mit
qwen3.8-27b-obliterated-q4
Qwen3.8-27B OBLITERATED is an Apache-2.0 Qwen3.8 vision-language model
modified for refusal-removal and red-team research. It retains reasoning,
coding, tool use, image, and video capabilities, but its safety guardrails
have been removed.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. The
linked variant uses the higher-quality Q8_0 model. The publisher recommends
greedy decoding with a 1.15 repetition penalty.
Repository: localaiLicense: apache-2.0
qwen3.8-27b-obliterated-q8
Qwen3.8-27B OBLITERATED in the higher-quality Q8_0 GGUF format. This model
is modified for refusal-removal and red-team research, and its safety
guardrails have been removed.
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
qwen3.8-27b-q4-mtp
Qwen3.8-27B with the official Q4_K_M model and Q4_0 MTP draft model.
MTP speculative decoding can increase generation speed by proposing
multiple tokens for the target model to verify.
Repository: localaiLicense: apache-2.0
qwen3.8-27b-q8
Qwen3.8-27B in the official Q8_0 GGUF format. This variant provides higher
model fidelity for hosts with enough memory.
Repository: localaiLicense: apache-2.0
qwen3.8-27b-ridge
Qwen3.8-27B Ridge is a 3.69-bit mixed quantization that keeps the
Gated-DeltaNet state path at Q8_0 and preserves the embedded MTP head.
It reduces the model weights to 12.59 GB while retaining multimodal,
reasoning, coding, tool-use, and long-context capabilities.
Repository: localaiLicense: apache-2.0
muse-glimmer-30b
Muse Glimmer is Meta Superintelligence Labs' Apache-2.0 dense 30B model for
autonomous agentic work, coding, tool use, long-horizon reasoning, and
multimodal understanding. It supports more than 100 languages, interleaved
text and image input through its 1.8B-parameter perception encoder, and a
131K-token context window.
This entry uses the publisher's higher-quality dynamic K-quant GGUF and
official quantized vision projector. Automatic variant selection can use
the smaller 17 GB quantization or a DFlash-accelerated build when it fits.
Repository: localaiLicense: apache-2.0
muse-glimmer-30b-dflash
Muse Glimmer's higher-quality dynamic K-quant GGUF with the official
quantized perception encoder and DFlash drafter. DFlash proposes blocks of
up to 16 tokens for the target to verify in parallel, accelerating output
without changing model quality. Flash attention is enabled for this path.
Repository: localaiLicense: apache-2.0
muse-glimmer-30b-17gb
Muse Glimmer's smaller 17 GB K-quant GGUF with the official quantized
perception encoder. It preserves the model's agentic, coding, tool-use,
multilingual, and image-understanding capabilities for hosts with less
memory than the dynamic quantization requires.
Repository: localaiLicense: apache-2.0
muse-glimmer-30b-17gb-dflash
Muse Glimmer's smaller 17 GB K-quant GGUF with the official quantized
perception encoder and DFlash drafter. This is the lowest-memory published
build that retains image understanding and block-speculative decoding.
Flash attention is enabled for the DFlash path.
Repository: localaiLicense: apache-2.0
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