migtissera/Tess-4.5-27B-GGUF
image-text-to-text model by migtissera
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Model card & documentation
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October 2026 · Model card · Continuity Research Tess-4.5 is a 27-billion-parameter open-weights model for real engineering work. It reasons through every step, works with the tools and files actually in front of it, and runs on a single GPU or a laptop. On BenchLocal it matches its base, Qwen3.8-27B, with 25% fewer tokens. This repository holds the GGUF quantizations for llama.cpp, the vision projector and the multi-token-prediction draft heads. For benchmarks and the full story, see the model card. With -hf, --spec-type draft-mtp also fetches the matching mtp- draft head. With local files: MTP speculative decoding needs a recent upstream llama.cpp build. On a 24 GB GPU at very long contexts, quantize the KV caches (--cache-type-k…
Read the full model card ↗ · Preview checked 2026-11-06T07:03:52.129Z
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Model overview
migtissera/Tess-4.5-27B-GGUF is a image-text-to-text model repository published by migtissera on Hugging Face. The source reports the gguf library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- gguf
- Recent downloads (30 days)
- 711,026
- Cumulative likes
- 61
- Hugging Face trending score
- 26
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-18T18:32:14.000Z
- Last modified
- 2026-10-18T23:29:39.000Z
Compatibility and lineage
Reported languages: en
Reported base models: migtissera/Tess-4.5-27B
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-06T06:54:50.171Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.