peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF-MTP
image-text-to-text model by peculiar-ragdoll
From the publisher
Model card & documentation
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Tiel is the fast coder of the arsenal. At 4-bit quantization and 23 GB it fixes real codebase issues at the rate (and speed, with the right GPU) of Opus 4.6 medium, while holding the best multi-turn conversation of any local model we have measured. It is also cheerfully bad at trivia. Pick it for work. Pick something else for exams. Where it sits against the other local builds Multi-turn conversation Reasoning and knowledge Where it stands. On 25 SWE-bench-Live problems Tiel fixes 12 — the same as Opus 4.6 (medium), four more than Ornith-1.5 itself, three more than Nail, and four more than Sonnet 5 (medium). Among models of its own class it is first; the ones ahead are dense 27Bs and Opus 5. Its time per attempt is also steadier than Nail's: an 8.6 minute median against 7.2, but a 12.3 minute mean against 15.7, because it lacks…
Read the full model card ↗ · Preview checked 2026-10-30T02:30:27.785Z
Inside the original model card — Document outline
- Straight to the point
- The numbers
- Run it
- The multi-token-prediction head
- How the imatrix was made
- Limitations
- Credits
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Model overview
peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF-MTP is a image-text-to-text model repository published by peculiar-ragdoll 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)
- 2,957,124
- Cumulative likes
- 330
- Hugging Face trending score
- 22
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-08-24T18:51:06.000Z
- Last modified
- 2026-10-25T15:44:54.000Z
Compatibility and lineage
Reported languages: en, zh
Reported base models: ornith-ai/Ornith-1.5-35B-A3B
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 2026-11-01T06:51:30.840Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.