| --- |
| license: other |
| license_name: qwen |
| license_link: https://huggingface.co/Qwen |
| base_model: |
| - Qwen/Qwen3.5 |
| tags: |
| - agent |
| - tool-calling |
| - function-calling |
| - gguf |
| - ollama |
| - long-context |
| pipeline_tag: text-generation |
| library_name: transformers |
| --- |
| |
| # Engrym Seed Base 9B |
|
|
| Orvyth's seed-tier brain — the recommended member of a local model family built for **tool-using |
| agents**. Qwen3.5 hybrid linear-attention architecture, **262,144-token native context**, first-class |
| tool calling. |
|
|
| **Weights are distributed via the Ollama registry.** |
|
|
| ```bash |
| ollama run Orvyth/engrym-seed:base |
| ``` |
|
|
| ## The ladder |
|
|
| | Tag | Class | Size | 77-task | Tool calls | |
| |---|---|---:|---:|---:| |
| | `:nano` | Nano 2B | 2.1 GB | 90.8/143 | 12/12 | |
| | `:flash` | Flash 4B | 4.6 GB | 124/143 | 12/12 | |
| | **`:base`** | **Base 9B** | **9.5 GB** | **131/143** | **12/12** | |
| | `:pro-27b-q4` | Pro 27B v2 Q4 | 16.5 GB | 134/143 | 12/12 | |
| | `:pro` | Pro 27B v2 Q8 | 28.6 GB | 137/143 | 12/12 | |
| | `:pro-e` | Pro-E 27B *(experimental)* | 28.6 GB | 137/143 | 12/12 | |
|
|
| ## Evaluation |
|
|
| 77 tasks · 143 points · `temperature=0` · `max_tokens=16384` · `seed=42` · one attempt · deterministic |
| validators · **no LLM judge**. Scores are bound to the exact published blobs. |
|
|
| These are **first-party** numbers. Repeated runs on an uncontended GPU are deterministic (zero spread |
| across n=2 for every model measured), but public reproduction receipts are still pending. |
|
|
| ## Compute modes — the score above is a floor |
|
|
| Asking the model to work *deliberately* (reason step by step, verify against every constraint, then |
| answer) recovers points on tasks it otherwise fails. Base: **131 → 134**. The gain is largest for the |
| smallest models — Nano gains **+11.8**. On the small end, that is worth more than a model upgrade. |
|
|
| ## Defaults |
|
|
| `temperature 0.2` · `top_p 0.9` · `top_k 20` · `num_ctx 32768` · `num_predict 8192` |
|
|
| Native context is 262,144; larger requests are clamped. Default is 32,768 because defaulting to the |
| native maximum made a 9.5 GB model request ~19 GB of RAM to start. If a prompt exceeds `num_ctx`, |
| Ollama returns HTTP 400 — it does not silently truncate. |
|
|
| ## Lineage |
|
|
| | Stage | Provenance | |
| |---|---| |
| | Base | `Qwen/Qwen3.5` — hybrid linear-attention | |
| | Merge | Ornith-1.0-9B × Qwythos-9B — TIES, 0.5 / 0.5 | |
| | Tune | Orvyth identity + chip-calling; LoRA merged into the weights | |
| | Build | Converted and quantized in-house with Orvyth trainkit | |
|
|
| ## What is in the artifact |
|
|
| Weights, identity, and tool-call generation. Memory, governed tool execution, safety enforcement, |
| adapters and multi-agent routing are Orvyth platform concerns, not part of the GGUF. Tool calling is |
| an output capability — the host validates, authorizes and executes. |
|
|
| ## Limits |
|
|
| - Scores are first-party and single-suite. Treat small gaps between adjacent models as unresolved. |
| - The identity tune is light; under a heavy external system prompt behavior can defer to the base model. |
| - The 27B is substantially slower per tool call than the 9B. Prefer Base or Flash for agent loops. |
| - The MTP speculative-decoding head is not included in these builds. |
| - Tags are mutable — pin the digest for production and evaluations. |
|
|
| --- |
|
|
| **ORVYTH** — Intelligence. Governed. *Ground truth over hype. Prove before you claim.* |
|
|
