Model benchmarks
Swift-1.5-Uncensored local LLM performance
As of November 2026, Swift-1.5-Uncensored runs at up to 69.1 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
Unknown
Peak speed
69.1 tok/s
Average speed
55.9 tok/s
Avg PP
464.6 tok/s
Min memory
58.3 GB
Max context
32,768 tokens
Avg output / run
39,814 tokens
Avg runtime / run
12m 6s
Avg quality
87.4
Benchmark runs
2
GPUs tested
1
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 2 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 86.5 | 87.4 | 88.2 |
| Agent Workflow | 84.7 | 87.0 | 89.2 |
| Code Generation | 79.7 | 82.1 | 84.4 |
| Role Play & Narrative | 92.8 | 92.9 | 92.9 |
| Research & Analysis | 86.4 | 87.6 | 88.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination Swift-1.5-Uncensored has been benchmarked on, ranked by peak token generation speed. Last updated November 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Tesla V100-PCIE-32GB | llama.cpp | — | 69.1 tok/s | 55.9 tok/s | 58.3 GB | 32,768 tokens | 87.4 | 2 |
Benchmark runs
All 2 Swift-1.5-Uncensored runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Swift-1.5-Uncensored good for coding?
- In our benchmarks, Swift-1.5-Uncensored scores 82.1/100 for coding. It runs at about 55.9 tok/s, so if you want more speed, unsloth/Qwen3.8-27B-GGUF:IQ3_S is faster (~104.3 tok/s) and still scores well for coding (83.0/100).
- Is Swift-1.5-Uncensored good for agentic (tool-using) tasks?
- In our benchmarks, Swift-1.5-Uncensored scores 87.0/100 for agentic workflows. It runs at about 55.9 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
- How fast is Swift-1.5-Uncensored for local inference?
- Across 2 community benchmark runs, Swift-1.5-Uncensored reaches up to 69.1 tok/s and averages 55.9 tok/s, with the fastest results on Tesla V100-PCIE-32GB.
- How much memory does Swift-1.5-Uncensored need?
- The leanest observed configuration used about 58.3 GB of memory.
- Which tools have been used to run Swift-1.5-Uncensored?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.