Gemma 4 26B-A4B Q5_K_M (ARA-Abliterated)
This ARA-Abliterated variant removes the safety filters from Google’s Gemma 4 26B-A4B MoE and delivers the model as a Q5-GGUF on Workstation hardware. The architecture remains efficient at 25 billion total and approximately 4 billion active parameters per token; 256,000 tokens of context, Apache 2.0 license. Thinking status and multimodal capabilities have not yet been cleanly verified in this variant — intended for research and red-teaming, not as an end-consumer assistant.
- Open Weights
- Workstation
- llama.cpp
- Text
- Instruction-Tuned
- Uncensored
- Vision
- Interactive
Sovereign Risk: MEDIUM The base weights originate from Google DeepMind and are released under Apache 2.0. However, this card describes a community abliteration by ARA-APEX — a modified derivative variant with removed safety filters and additional quantization. Purely local operation avoids cloud risks, but the lack of official documentation of the modification and the uncensored abliteration increase provenance risk compared to the unmodified base.[web:809][web:812][web:821]
Key metrics
Score · Latency · Cost · Quality
- Total Score Silver
- 73.35
- Routine
- 44.56
- Reasoning
- 28.79
- LLM Judge Avg
- 3.6 / 5
- 100 Coverage
- Avg Task Duration
- 24.32s
- Interactive
- Token Rate
- 53.49tok/s
- Output Rate
- P95 Latency
- 64.96s
- Top 5 %
- Total Tokens
- 72400
- Output Volume
- Cost per 1K
- $0
- USD / 1K Requests
- Benchmark Cost
- $0
- Total · 72400 tok
Benchmark modules
10 modules · weighted · vs. model median & top performer
Token efficiency & latency
Consumption per module vs. model median
Token consumption per module
Performance profile
Key metrics – legend
Score
- Total Score
- Overall score derived from Routine and Reasoning scores. Basis for the fleet rank and tier assignment (Gold / Silver / Bronze / Standard).
- Routine
- Score for standard tasks: code generation, text transformation, structured outputs. Weighted by task complexity.
- Reasoning
- Score for analytical and logical tasks: multi-step problem solving, mathematical reasoning, structured argumentation.
- Rank
- Position in the fleet comparison, sorted by Total Score. Refers to the snapshot at the time of testing.
LLM Judge
- LLM Judge Ø
- Average quality rating by an independent judge model on a scale of 1–5.
- Coverage
- Share of tasks for which a judge rating is available. 100% means all responses were evaluated.
Latency & speed
- Avg. Task Duration
- Average time per task from the first to the last token of the response, measured across all benchmark tasks.
- Token Rate
- Output speed in tokens per second. Relevant for interactive applications and real-time streaming.
- P95 Latency
- 95th percentile of response times — shows outliers. Lower values mean fewer long wait times in edge cases.
Cost
- Cost per 1K
- API price per 1,000 output tokens in US dollars. Basis for cost calculation in production use.
- Benchmark Cost
- Total cost for the complete benchmark run of this model.