llama.cpp
UnknownChecked the exact model config and the runtime architecture registry; no matching declared architecture was found. This is unknown, not evidence of incompatibility.
Checked 2026-10-27 00:08 UTC
Checked source ↗prism-ml · Released Sep 16, 2026 · observed 26 Oct 2026
Public-source support evidence
Ternary-Bonsai-2-27B-gguf
We have not found public evidence yet that Ternary-Bonsai-2-27B-gguf is listed in llama.cpp, Ollama, LM Studio, MLX or vLLM.
prism-ml/Ternary-Bonsai-2-27B-gguf
Ternary-Bonsai-2-27B-gguf is a text generation model published by prism-ml on Hugging Face. We have not written a summary yet; see the model card ↗.
View source model ↗SUPPORT EVIDENCE
Runtime status
Ollama
UnknownThe exact model and runtime-specific sources were checked; no positive model-level evidence was established.
Checked 2026-10-26 23:48 UTC
Version v0.40.11
Checked source ↗LM Studio
UnknownThe exact model and runtime-specific sources were checked; no positive model-level evidence was established.
Checked 2026-10-27 00:28 UTC
Checked source ↗MLX / mlx-lm
UnknownChecked the exact model config and the runtime architecture registry; no matching declared architecture was found. This is unknown, not evidence of incompatibility.
Checked 2026-10-27 00:08 UTC
Checked source ↗vLLM
UnknownChecked the exact model config and the runtime architecture registry; no matching declared architecture was found. This is unknown, not evidence of incompatibility.
Checked 2026-10-27 00:08 UTC
Checked source ↗MLX community uploads may target mlx-vlm; an upload observation does not establish mlx-lm compatibility.
MEMORY ESTIMATES
Which file should I grab?
The summary estimate of about 11 GB is the recommended PQ2_0 quant (7.2 GB observed), from file size × 1.2 + 1.5 GB. Each card is the largest observed quant whose estimate fits that capacity.
16 GB capacity estimate
Which file should I grab?
PQ2_0 · 7.2 GB observed · about 11 GB ↗About 11 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
24 GB capacity estimate
Which file should I grab?
PQ2_0 · 7.2 GB observed · about 11 GB ↗About 11 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
32 GB capacity estimate
Which file should I grab?
PQ2_0 · 7.2 GB observed · about 11 GB ↗About 11 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
64 GB capacity estimate
Which file should I grab?
PQ2_0 · 7.2 GB observed · about 11 GB ↗About 11 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
128 GB capacity estimate
Which file should I grab?
F16 · 53.8 GB observed · about 67 GB ↗About 67 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
192 GB capacity estimate
Which file should I grab?
F16 · 53.8 GB observed · about 67 GB ↗About 67 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
256 GB capacity estimate
Which file should I grab?
F16 · 53.8 GB observed · about 67 GB ↗About 67 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
512 GB capacity estimate
Which file should I grab?
F16 · 53.8 GB observed · about 67 GB ↗About 67 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
Memory estimates are the observed file size plus fixed headroom (20% plus 1.5 GB runtime allowance); real needs also depend on context length, KV cache and runtime settings. Fit is an estimate; it does not establish runtime compatibility, speed, context length, or hardware performance. Text-weights-only estimates do not include a projector or total vision memory where unknown.
Terms: a quant is a lower-precision version of the weights; GGUF is a file format used by llama.cpp and compatible apps; MLX targets Apple silicon; vLLM is a model-serving engine for NVIDIA GPUs; the KV cache is stored attention state that grows with context length. Terms explained ↗
OBSERVED FILES
Quant uploads
Sizes and file groups come from the listed uploader repositories. A size is marked as an estimated fit only for a complete observed GGUF quant group.
| Uploader | Format & quant | Observed size | Estimated fit | Files |
|---|---|---|---|---|
| prism-mlprism-ml/Ternary-Bonsai-2-27B-gguf ↗Observed 27 Oct 2026 | GGUF · F16 | 53.8 GB | 128 GB, 192 GB, 256 GB, 512 GBEstimate only; requires the complete GGUF quant group. | 1 file |
| prism-mlprism-ml/Ternary-Bonsai-2-27B-gguf ↗Observed 27 Oct 2026 | GGUF · PQ2_0 | 7.2 GB | 16 GB, 24 GB, 32 GB, 64 GB, 128 GB, 192 GB, 256 GB, 512 GBEstimate only; requires the complete GGUF quant group. | 1 file |
| prism-mlprism-ml/Ternary-Bonsai-2-27B-gguf ↗Observed 27 Oct 2026 | GGUF · PTQ1_0 | 5.9 GB | 16 GB, 24 GB, 32 GB, 64 GB, 128 GB, 192 GB, 256 GB, 512 GBEstimate only; requires the complete GGUF quant group. | 1 file |
CURATED TRACKING
Known issues
No curated issues verified for this snapshot. An empty list does not mean there are no bugs.
HARDWARE NOTES
Hardware testing planned
No execution or benchmark results are published for this model yet.
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