Swift Qwen 3.8 27B (Thinking)

Swift Qwen 3.8 27B is UkisAI’s reasoning-efficiency fine-tune on Qwen 3.8 27B: up to 58 percent fewer thinking tokens at under one percent performance loss and roughly twice the throughput on reasoning tasks. NVFP4 quantization with 262,000 tokens of context, MTP head for speculative decoding, and documented tool use — license with a commercial ARR threshold.

UkisAI Version 3.8 Commercial use permitted Dense 28 B 262 K Context 12/2025 locally tested

  • Restricted Weights
  • Workstation
  • vLLM
  • Text
  • Vision
  • Batch

Sovereign Risk: MEDIUM This checkpoint is a UkisAI fine-tune and an NVFP4 quantization of Qwen/Qwen3.8-27B. The base lineage is documented, but the weights are distributed under the gated Swift Open License v1.0 with an ARR threshold and are optimized for Blackwell/vLLM deployment — provenance is therefore clear, but not fully open in the OSS sense.

Key metrics

Score · Latency · Cost · Quality

Total Score Gold
80.48
Routine
49.15
Reasoning
31.33

Rank #5

LLM Judge Avg
4.09
100 Coverage
Avg Task Duration
110.61
Batch
Token Rate
15.96
Output Rate
P95 Latency
290.93
Top 5 %
Total Tokens
115800
Output Volume
Cost per 1K
$0
USD / 1K Requests
Benchmark Cost
$0
Total · 115800 tok

Benchmark modules

10 modules · weighted · vs. model median & top performer

Swift Qwen 3.8 27B (Thinking) Best model Ø All models
Code Quality 84.44
CLI Benchmark 90.67
Logical Reasoning 75.27
UX Writing 81.41
Documentation 83.35
Content Transform. 82.23
Cultural Intelligence 76.8
Synthesis Quality 59.17
Tool Execution 90
ToolUse Score 74.79
Benchmark Cost $0

Token efficiency & latency

Consumption per module vs. model median

Token consumption per module

Performance profile