JiRackUltra_14b
A fast and efficient 14B model optimized for CPU inference. The model was refactored with BitNet features and an updated tokenizer that includes new Routing, Media, Vision, Sound, Tool call, and Robotics tags. Built on a DeepSeek R1-14B architecture with native ternary (BitNet-style) support and ready-to-run GGUF quantizations. - JiRack is a cloud-ready model that helps save money on cloud infrastructure. It can be u...
Params
14.8 B
Context
131,072
Downloads 30d
1.0 M
Likes
2
Download history
daily snapshots · 8 days1.0 M229 K
Sep 14Sep 16Sep 19Sep 21
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| JiRackUltra_14b_Q2_K.gguf | Q2_K | 5.8 GB | 9.1 GB | ✅ Runs comfortably |
| JiRackUltra_14b_Q3_K_M.gguf | Q3_K_M | 7.3 GB | 10.8 GB | ✅ Runs comfortably |
| JiRackUltra_14b_Q4_K_M.gguf | Q4_K_M | 9.0 GB | 12.6 GB | ✅ Runs comfortably |
| JiRackUltra_14b.Q5_K_M.gguf | Q5_K_M | 10.5 GB | 14.3 GB | ✅ Runs comfortably |
| JiRackUltra_14b.Q6_K.gguf | Q6_K | 12.1 GB | 16.1 GB | ✅ Runs comfortably |
| JiRackUltra_14b.Q8_0.gguf | Q8_0 | 15.7 GB | 20.0 GB | ⚠️ Tight — reduce context |
| JiRackUltra_14b.gguf | GGUF | 29.5 GB | 35.2 GB | ❌ Won’t fit |
| model.safetensors | bf16 | 29.5 GB | 35.2 GB | ❌ Won’t fit |
| model.safetensors (bf16, full) | bf16 + 128K ctx | 29.5 GB | 68.4 GB | ❌ Won’t fit |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ ollama run jirackultra:14b # pin the quantization explicitly $ ollama run jirackultra:14b-q4_k_m
$ huggingface-cli download CMSManhattan/JiRackUltra_14b-GGUF \
JiRackUltra_14b_Q4_K_M.gguf --local-dir .
$ llama-cli -m JiRackUltra_14b_Q4_K_M.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/jirackultra-14b
{
"hf_id": "CMSManhattan/JiRackUltra_14b",
"params_b": 14.77,
"context_length": 131072,
"license": { "id": "mit", "commercial": "yes" },
"downloads_30d": 1000579,
"vram_estimates": [
{ "quant": "Q5_K_M", "gb": 14.3 },
{ "quant": "Q6_K", "gb": 16.1 }
],
"updated_at": "2026-09-20T01:00:07Z"
}
Specifications
- Architecture
- Qwen2ForCausalLM
- Parameters
- 14.8 B
- Tensor type
- BF16
- Context length
- 131,072
- Vocabulary
- 152,064
- Layers / heads
- 48 / 40
- Licence
- mit
- First seen on the Hub
- 2026-08-03
- Training datasets
- undisclosed
- Added to our catalog
- 2026-09-14
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