Qwen 3.6 35B-A3B (Unsloth)
Qwen 3.6 35B-A3B is Alibaba’s MoE model with 35 billion total and approximately 3 billion active parameters per token, released on April 22, 2026 under Apache 2.0 with open weights for local deployment. The hybrid attention architecture combines classic attention with a linear variant; Multi-Token Prediction noticeably accelerates generation.
- Open Weights
- Workstation
- vLLM
- Text
- Vision
- Video
- Instruction-Tuned
- Real-Time
Sovereign Risk: MEDIUM The model originates from the Qwen team (Alibaba), based in China. The classification of risk as ‘medium’ rather than ‘high’ reflects that this is an open-source model under the permissive Apache 2.0 license, which can be run entirely locally without any cloud connection to Alibaba servers. In purely local operation, NSL relevance is virtually eliminated; a theoretical residual risk due to the Chinese developer jurisdiction remains for the purposes of the provenance assessment.
Key metrics
Score · Latency · Cost · Quality
- Total Score Silver
- 70.53
- Routine
- 43.03
- Reasoning
- 27.5
- LLM Judge Avg
- 3.67 / 5
- 100 Coverage
- Avg Task Duration
- 11.72s
- Real-Time
- Token Rate
- 67.54tok/s
- Output Rate
- P95 Latency
- 31.4s
- Top 5 %
- Total Tokens
- 71300
- Output Volume
- Cost per 1K
- $0
- USD / 1K Requests
- Benchmark Cost
- $0
- Total · 71300 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).
- 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.