TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF overview
TobDeBer/Mellum2 12B A2.5B Instruct Q3 K L GGUF This model was converted to GGUF format from JetBrains/Mellum2 12B A2.5B Instruct https://huggingface.co/JetBra…
Runs locally from ~6.14 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| mellum2-12b-a2.5b-instruct-q3_k_l.gguf | GGUF | Q3_K_L | 6.14 GB | Download |
Model Details
| Model ID | TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF |
|---|---|
| Author | TobDeBer |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | JetBrains/Mellum2-12B-A2.5B-Instruct |
| Last modified | 2026-06-06T20:51:16.000Z |
Model README
---
library_name: transformers
language:
- en
pipeline_tag: text-generation
license: apache-2.0
base_model: JetBrains/Mellum2-12B-A2.5B-Instruct
tags:
- llama-cpp
- gguf-my-repo
model-index:
- name: Mellum2 Instruct
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: LiveCodeBench v6
type: livecodebench
metrics:
- type: pass@1
value: 37.2
name: pass@1
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: EvalPlus (HumanEval+ / MBPP+ mean)
type: evalplus
metrics:
- type: pass@1
value: 78.4
name: pass@1
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: MultiPL-E (7 languages)
type: multipl-e
metrics:
- type: pass@1
value: 67.1
name: pass@1
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: BFCL v3
type: bfcl
metrics:
- type: acc
value: 66.3
name: accuracy
verified: false
- type: acc
value: 44.2
name: accuracy
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: AIME 2025+2026 (mean, 30 questions each)
type: aime
metrics:
- type: exact_match
value: 41.7
name: exact match
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM-Plus
type: gsm-plus
metrics:
- type: exact_match
value: 80.5
name: exact match
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-Redux
type: mmlu-redux
metrics:
- type: acc
value: 78.1
name: accuracy
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA Diamond
type: gpqa
metrics:
- type: acc
value: 40.9
name: accuracy
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (prompt-level strict accuracy)
type: ifeval
metrics:
- type: acc
value: 75.8
name: accuracy
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: MixEval
type: mixeval
metrics:
- type: acc
value: 62.2
name: accuracy
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: BS-Bench (detection rate)
type: bs-bench
metrics:
- type: detection_rate
value: 18.0
name: detection rate
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: HarmBench (harmful rate, lower is better)
type: harmbench
metrics:
- type: harmful_rate
value: 23.1
name: harmful rate
verified: false
- task:
type: text-generation
name: Text Generation
dataset:
name: XSTest (safe compliance)
type: xstest
metrics:
- type: safe_compliance
value: 81.2
name: safe compliance
verified: false
---
TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF
This model was converted to GGUF format from JetBrains/Mellum2-12B-A2.5B-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF --hf-file mellum2-12b-a2.5b-instruct-q3_k_l.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF --hf-file mellum2-12b-a2.5b-instruct-q3_k_l.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF --hf-file mellum2-12b-a2.5b-instruct-q3_k_l.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF --hf-file mellum2-12b-a2.5b-instruct-q3_k_l.gguf -c 2048Run TobDeBer/Mellum2-12B-A2.5B-Instruct-Q3_K_L-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models