Is swift-1.5-iq3_xxs good for coding?

In our benchmarks, swift-1.5-iq3_xxs scores 78.4/100 for coding. It runs at about 63.6 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~80.3 tok/s) and still scores well for coding (84.5/100).

Is swift-1.5-iq3_xxs good for agentic (tool-using) tasks?

In our benchmarks, swift-1.5-iq3_xxs scores 85.4/100 for agentic workflows. It runs at about 63.6 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).

How fast is swift-1.5-iq3_xxs for local inference?

Across 6 community benchmark runs, swift-1.5-iq3_xxs reaches up to 116.5 tok/s and averages 63.6 tok/s, with the fastest results on NVIDIA GeForce RTX 5090.

Which tools have been used to run swift-1.5-iq3_xxs?

Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.

Model benchmarks

swift-1.5-iq3_xxs local LLM performance

As of October 2026, swift-1.5-iq3_xxs runs at up to 116.5 tok/s for local inference (best of 6 community benchmark runs across 2 GPUs).

llama.cpp

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Model size

Unknown

Peak speed

116.5 tok/s

Average speed

63.6 tok/s

Avg PP

341.4 tok/s

Min memory

n/a

Max context

262,144 tokens

Avg output / run

25,827 tokens

Avg runtime / run

7m 1s

Avg quality

84.3

Benchmark runs

GPUs tested

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 6 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	82.0	84.3	85.8
Agent Workflow	77.9	85.4	90.4
Code Generation	74.3	78.4	82.4
Role Play & Narrative	81.8	88.1	92.0
Research & Analysis	82.7	85.4	88.8

Performance by hardware and tool

Every hardware/tool/quantization combination swift-1.5-iq3_xxs 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
NVIDIA GeForce RTX 5090	llama.cpp	—	116.5 tok/s	116.5 tok/s	n/a	262,144 tokens	85.9	1
AMD Radeon RX 7900 XTX	llama.cpp	—	55.5 tok/s	53.1 tok/s	n/a	65,536 tokens	84.0	5

Benchmark runs

All 6 swift-1.5-iq3_xxs runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is swift-1.5-iq3_xxs good for coding?: In our benchmarks, swift-1.5-iq3_xxs scores 78.4/100 for coding. It runs at about 63.6 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~80.3 tok/s) and still scores well for coding (84.5/100).
Is swift-1.5-iq3_xxs good for agentic (tool-using) tasks?: In our benchmarks, swift-1.5-iq3_xxs scores 85.4/100 for agentic workflows. It runs at about 63.6 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
How fast is swift-1.5-iq3_xxs for local inference?: Across 6 community benchmark runs, swift-1.5-iq3_xxs reaches up to 116.5 tok/s and averages 63.6 tok/s, with the fastest results on NVIDIA GeForce RTX 5090.
Which tools have been used to run swift-1.5-iq3_xxs?: Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.