Gemma 4 12B Instruct (Unsloth)
Gemma 4 12B Instruct as a Q8 quantization by the Unsloth community, the highest-precision variant among the 12B builds. With twelve billion parameters and a 128,000-token context window, the model delivers near-FP16 quality, is designed for local operation without cloud connectivity, and is fully commercially usable under the Apache 2.0 license.
- Open Weights
- Desktop
- llama.cpp
- Text
- Instruction-Tuned
- Batch
Sovereign Risk: LOW Google DeepMind is a US-based company and subject to the CLOUD Act, which is primarily relevant for API/cloud usage, not for locally operated weights. When running inference exclusively locally without a cloud connection, the risk scenario is minimal.
Key metrics
Score · Latency · Cost · Quality
- Total Score Silver
- 70.74
- Routine
- 43
- Reasoning
- 27.74
- LLM Judge Avg
- 3.65 / 5
- 100 Coverage
- Avg Task Duration
- 94s
- Batch
- Token Rate
- 13.07tok/s
- Output Rate
- P95 Latency
- 175.3s
- Top 5 %
- Total Tokens
- 101200
- Output Volume
- Cost per 1K
- $0
- USD / 1K Requests
- Benchmark Cost
- $0
- Total · 101200 tok
Benchmark modules
10 modules · weighted · vs. model median & top performer
Gemma 4 12B Instruct (Unsloth)
Best model
Ø All models
Code Quality
77.1
CLI Benchmark
87.22
Logical Reasoning
68.75
UX Writing
71.05
Documentation
66.77
Content Transform.
73.31
Cultural Intelligence
67.6
Synthesis Quality
43.33
Tool Execution
83.33
ToolUse Score
62.33
Benchmark Cost
$0
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).
- 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.