Model benchmarks

IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 local LLM performance

As of November 2026, IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 runs at up to 23.1 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

llama.cpp
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Model size

35B

Peak speed

23.1 tok/s

Average speed

22.9 tok/s

Avg PP

277.9 tok/s

Min memory

8.2 GB

Max context

65,536 tokens

Avg output / run

27,685 tokens

Avg runtime / run

19m 30s

Avg quality

81.7

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.

TaskP5 (low)AvgP95 (high)
Overall79.381.784.1
Agent Workflow75.476.176.8
Code Generation73.875.777.6
Role Play & Narrative86.088.791.3
Research & Analysis81.886.390.7

Performance by hardware and tool

Every hardware/tool/quantization combination IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 has been benchmarked on, ranked by peak token generation speed. Last updated November 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 3050llama.cpp—23.1 tok/s22.9 tok/s8.2 GB65,536 tokens81.72

Benchmark runs

All 2 IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

Is IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 good for coding?
In our benchmarks, IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 scores 75.7/100 for coding. It runs at about 22.9 tok/s, so if you want more speed, Qwen3.8-27B-Turbo-Brilliance-50X-RI-GSQ-RCO-IQ3_XXS-mtp is faster (~37.5 tok/s) and still scores well for coding (83.8/100).
Is IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 good for agentic (tool-using) tasks?
In our benchmarks, IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 scores 76.1/100 for agentic workflows. It runs at about 22.9 tok/s, so if you want more speed, muse-glimmer:latest is faster (~33.3 tok/s) and still scores well for agentic workflows (91.6/100).
How fast is IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 for local inference?
Across 2 community benchmark runs, IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 reaches up to 23.1 tok/s and averages 22.9 tok/s, with the fastest results on NVIDIA GeForce RTX 3050.
How much memory does IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1 need?
The leanest observed configuration used about 8.2 GB of memory.
Which tools have been used to run IsValorum/Ornith-1_5-35B-A3B_APEX-I-MiniPlus-V2_1?
Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.