Where it runs 8K context · ≥ 5 t/s floor
Same plan engine as the planner, with its default reserves and RAM. How plans are chosen.
Files exact Hugging Face bytes
| Artifact | Size | Files | Revision | Source |
|---|
| Q8_0 lmstudio-community/rnj-1-instruct-GGUF | 8.23 GiB | 1 | 1572a7a650 | HF files |
| Q5_K_M unsloth/rnj-1-instruct-GGUF | 5.54 GiB | 1 | cc745e1175 | HF files |
| Q4_K_M EssentialAI/rnj-1-instruct-GGUF | 4.76 GiB | 1 | 502f3ae9c2 | HF files |
| MLX 8-bit 8-bit mlx-community/rnj-1-instruct-8bit | 8.71 GiB | 2 | 04662a4d95 | HF files |
| MLX 4-bit 4-bit mlx-community/rnj-1-instruct-4bit | 4.84 GiB | 1 | 958948da64 | HF files |
| EXL3 4-bit isogen/rnj-1-instruct-exl3-4bpw | 4.98 GiB | 1 | 789a3e33ba | HF files |
| Native safetensors F32 EssentialAI/rnj-1-instruct | 30.96 GiB | 7 | 5ef96d7a82 | HF files |
Not found in the representative quant search (not proven unavailable): GGUF FP16, AWQ, GPTQ. Complete selected file sets; projectors, MTP/draft and lookup files are listed separately and budgeted only by plans that use them. File bytes are not allocated memory.
Quality
No Artificial Analysis evaluation mapped to this checkpoint.
Publisher-reported benchmarks
None extracted from the model card.
AA and Arena describe the hosted model in the stated mode, not each quantized file; scores are never inherited by base, pruned, abliterated or quantized variants and never averaged together.
How to run it
vLLM · unknown
publisher-documented, not executed source
vllm serve EssentialAI/rnj-1-instruct --enable-auto-tool-choice --tool-call-parser hermes
Prerequisites: See source setup/dependencies; these snippets were inspected, not executed.
- Cardbase repository documents instruct runtime; recipe explicitly targets EssentialAI/rnj-1-instruct, not base.
- Hermes tool parser; do not inherit Gemma 3 sliding attention since Rnj uses global attention.
Recipes are source examples (settings are the publisher’s or author’s, not measured optima) and were not executed by LocalFit. A downloadable file does not prove your backend build supports the architecture.
Reported speeds 0
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