Model benchmarks
Underdog-Saluki-27B-1.0-IQ2-mix-MTP local LLM performance
As of October 2026, Underdog-Saluki-27B-1.0-IQ2-mix-MTP runs at up to 39.4 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
27B
Peak speed
39.4 tok/s
Average speed
35.1 tok/s
Avg PP
356.4 tok/s
Min memory
12.2 GB
Max context
131,072 tokens
Avg output / run
19,039 tokens
Avg runtime / run
8m 52s
Avg quality
82.1
Benchmark runs
2
GPUs tested
2
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 | 82.0 | 82.1 | 82.2 |
| Agent Workflow | 86.2 | 87.3 | 88.3 |
| Code Generation | 75.3 | 76.0 | 76.7 |
| Role Play & Narrative | 85.6 | 86.8 | 88.1 |
| Research & Analysis | 76.9 | 78.3 | 79.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination Underdog-Saluki-27B-1.0-IQ2-mix-MTP 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 5060 | llama.cpp | — | 39.4 tok/s | 39.4 tok/s | 18.2 GB | 131,072 tokens | 82.0 | 1 |
| AMD Radeon RX 6700/6700 XT/6750 XT / 6800M/6850M XT | llama.cpp | — | 30.8 tok/s | 30.8 tok/s | 12.2 GB | 72,000 tokens | 82.2 | 1 |
Benchmark runs
All 2 Underdog-Saluki-27B-1.0-IQ2-mix-MTP runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Underdog-Saluki-27B-1.0-IQ2-mix-MTP good for coding?
- In our benchmarks, Underdog-Saluki-27B-1.0-IQ2-mix-MTP scores 76.0/100 for coding. It runs at about 35.1 tok/s, so if you want more speed, K2-Horizon-MoVA-36B-A4B-MLX-4bit is faster (~48.5 tok/s) and still scores well for coding (82.5/100).
- Is Underdog-Saluki-27B-1.0-IQ2-mix-MTP good for agentic (tool-using) tasks?
- In our benchmarks, Underdog-Saluki-27B-1.0-IQ2-mix-MTP scores 87.3/100 for agentic workflows. It runs at about 35.1 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 Underdog-Saluki-27B-1.0-IQ2-mix-MTP for local inference?
- Across 2 community benchmark runs, Underdog-Saluki-27B-1.0-IQ2-mix-MTP reaches up to 39.4 tok/s and averages 35.1 tok/s, with the fastest results on NVIDIA GeForce RTX 5060.
- How much memory does Underdog-Saluki-27B-1.0-IQ2-mix-MTP need?
- The leanest observed configuration used about 12.2 GB of memory.
- Which tools have been used to run Underdog-Saluki-27B-1.0-IQ2-mix-MTP?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.