Model benchmarks

IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF local LLM performance

As of September 2026, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF runs at up to 135.9 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

llama.cpp
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Model size

Unknown

Peak speed

135.9 tok/s

Average speed

135.7 tok/s

Avg PP

1757.7 tok/s

Min memory

3.4 GB

Max context

65.536 tokens

Avg output / run

50.776 tokens

Avg runtime / run

6m 21s

Avg quality

84.2

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.

TaskP5 (low)AvgP95 (high)
Overall83.784.284.8
Agent Workflow82.784.586.3
Code Generation80.682.183.6
Role Play & Narrative84.487.290.0
Research & Analysis82.783.083.4

Performance by hardware and tool

Every hardware/tool/quantization combination IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
AMD Radeon RX 7900 XT/7900 XTX/7900 GRE/7900Mllama.cpp—135.9 tok/s135.7 tok/s3.4 GB65.536 tokens84.22

Benchmark runs

All 2 IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

Is IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF good for coding?
In our benchmarks, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF scores 82.1/100 for coding. It runs at about 135.7 tok/s, so if you want more speed, Qwen3.6-35B-A3B-Q4_K_XL is faster (~156.9 tok/s) and still scores well for coding (82.2/100).
Is IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF good for agentic (tool-using) tasks?
In our benchmarks, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF scores 84.5/100 for agentic workflows. It runs at about 135.7 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-Q4_K_S is faster (~162.4 tok/s) and still scores well for agentic workflows (87.8/100).
How fast is IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF for local inference?
Across 2 community benchmark runs, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF reaches up to 135.9 tok/s and averages 135.7 tok/s, with the fastest results on AMD Radeon RX 7900 XT/7900 XTX/7900 GRE/7900M.
How much memory does IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF need?
The leanest observed configuration used about 3.4 GB of memory.
Which tools have been used to run IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF?
Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.