Model benchmarks
IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 local LLM performance
As of September 2026, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 runs at up to 25.9 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
Unknown
Peak speed
25.9 tok/s
Average speed
25.7 tok/s
Avg PP
158.9 tok/s
Min memory
3.4 GB
Max context
131.072 tokens
Avg output / run
44.852 tokens
Avg runtime / run
30m 10s
Avg quality
84.7
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 | 82.2 | 84.7 | 87.2 |
| Agent Workflow | 81.0 | 85.5 | 90.1 |
| Code Generation | 83.6 | 85.0 | 86.4 |
| Role Play & Narrative | 79.8 | 83.8 | 87.9 |
| Research & Analysis | 81.8 | 84.6 | 87.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 2060 | llama.cpp | — | 25.9 tok/s | 25.7 tok/s | 3.4 GB | 131.072 tokens | 84.7 | 2 |
Benchmark runs
All 2 IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 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:1 good for coding?
- In our benchmarks, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 scores 85.0/100 for coding, currently the best-scoring model for coding that runs on consumer hardware (≤24 GB VRAM). It runs at about 25.7 tok/s, so if you want more speed, /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf is faster (~35.6 tok/s) and still scores well for coding (84.9/100).
- Is IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 good for agentic (tool-using) tasks?
- In our benchmarks, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 scores 85.5/100 for agentic workflows. It runs at about 25.7 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 IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 for local inference?
- Across 2 community benchmark runs, IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 reaches up to 25.9 tok/s and averages 25.7 tok/s, with the fastest results on NVIDIA GeForce RTX 2060.
- How much memory does IsValorum/Nex-N2.5-mini-APEX-I-MiniPlus-V2.1-GGUF:1 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:1?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.