Model benchmarks
swift-1.5-iq2_xs local LLM performance
As of October 2026, swift-1.5-iq2_xs runs at up to 91.4 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
Unknown
Peak speed
91.4 tok/s
Average speed
88.1 tok/s
Avg PP
539.9 tok/s
Min memory
56.1 GB
Max context
16,384 tokens
Avg output / run
20,985 tokens
Avg runtime / run
3m 52s
Avg quality
72.0
Benchmark runs
3
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 3 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 | 51.8 | 72.0 | 85.3 |
| Agent Workflow | 25.6 | 62.6 | 89.1 |
| Code Generation | 7.6 | 52.1 | 80.0 |
| Role Play & Narrative | 89.8 | 91.4 | 93.8 |
| Research & Analysis | 79.2 | 81.7 | 83.6 |
Performance by hardware and tool
Every hardware/tool/quantization combination swift-1.5-iq2_xs has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XTX | llama.cpp | — | 91.4 tok/s | 88.1 tok/s | 56.1 GB | 16,384 tokens | 72.0 | 3 |
Benchmark runs
All 3 swift-1.5-iq2_xs runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is swift-1.5-iq2_xs good for coding?
- In our benchmarks, swift-1.5-iq2_xs scores 52.1/100 for coding. It runs at about 88.1 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-iq2_xs good for agentic (tool-using) tasks?
- In our benchmarks, swift-1.5-iq2_xs scores 62.6/100 for agentic workflows. It runs at about 88.1 tok/s, so if you want more speed, Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp is faster (~102.7 tok/s) and still scores well for agentic workflows (91.1/100).
- How fast is swift-1.5-iq2_xs for local inference?
- Across 3 community benchmark runs, swift-1.5-iq2_xs reaches up to 91.4 tok/s and averages 88.1 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does swift-1.5-iq2_xs need?
- The leanest observed configuration used about 56.1 GB of memory.
- Which tools have been used to run swift-1.5-iq2_xs?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.