Nimbus-9B-v2.1

Nimbus-9B-v2.1

A deeper local reasoning model for difficult coding, debugging, and tool-aware problem solving.

Nimbus is a family of local coding models: 2B for speed, 4B for balance, and 9B v2.1 for deeper reasoning. This Transformers repository contains the merged BF16 checkpoint and full multimodal components. The corresponding GGUF repository is text-only.

Choose a Nimbus model

The adjacent assets/nimbus-family-footprint.json contains the plotted values. Download size is not runtime memory: context cache and runtime buffers require additional capacity.

Artifacts

Text-only local files: Nimbus-Labs/Nimbus-9B-v2.1-GGUF

Evaluation

The released Q5_K_M artifact was evaluated with llama.cpp b10007 on Vulkan, native thinking, one answer per task, temperature 0.6, top-p 0.95, top-k 20, seed 42, and the official network-disabled EvalPlus scorer. The base run allowed 32,768 completion tokens. Each original length-plus-empty nonresponse received exactly one preserved 60,000-token recovery attempt; there was no repeated resampling.

Three HumanEval and seven MBPP truncations recovered at the larger limit. Two HumanEval and three MBPP nonresponses remained zero-valued. “Plus” uses EvalPlus' official base-and-plus pass condition.

The adjacent assets/nimbus-9b-v2.1-evalplus.json is the machine-readable source for this chart.

Release landscape

This is a capability and packaging comparison, not a cross-model score claim. Other publishers' benchmarks use different harnesses, prompts, inference budgets, and hardware, so they are not mixed into the Nimbus EvalPlus chart.

Nimbus-9B v2.1 inherits its architecture and foundation capabilities from Qwen3.5 through Ornith. Nimbus' contribution is the post-training, release packaging, quantization, and exact evaluation reported above—not authorship of the foundation model.

Quickstart

Use a recent Transformers release compatible with Qwen3.5. Load the repository with trust_remote_code=False, preserve the supplied processor/tokenizer files, and enable thinking through the supplied chat template where supported. Validate generated code before execution.

from transformers import AutoProcessor, AutoModelForImageTextToText

model_id = "Nimbus-Labs/Nimbus-9B-v2.1"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForImageTextToText.from_pretrained(model_id, torch_dtype="auto", device_map="auto")

Training and provenance

• Immediate upstream: deepreinforce-ai/Ornith-1.0-9B
• Pinned revision: 83dc1f5e24ef8527af019a6b3bf66ac0f1c2c999
• Foundation: Ornith-1.0-9B on Qwen3.5-9B
• Relationship: Nimbus post-training / fine-tune and verified merge
• Exact uploaded file hashes: SHA256SUMS
• Release metadata: release-manifest.json

Nimbus prominently credits Qwen3.5 as the foundation for this model family. Nimbus-9B-v2.1 additionally credits DeepReinforce's Ornith-1.0-9B as its immediate upstream.

Intended use

Local coding assistance, code explanation, debugging, test generation, and bounded tool-aware workflows. Host applications must enforce permissions, sandboxing, timeouts, and verification.

Limitations

The model can produce incorrect, insecure, incomplete, or non-compiling code. Benchmark performance does not guarantee project-level correctness. GGUF artifacts are text-only even though this Transformers checkpoint includes multimodal components.

Licenses and notices

See LICENSES.md, THIRD_PARTY_NOTICES.md, and the bundled Apache-2.0 text. The model is a derivative distribution; Nimbus attribution does not replace upstream attribution.

Project

Nimbus8 · GGUF files