Model benchmarks

mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF local LLM performance

As of August 2026, mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF runs at up to 193.7 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

vLLM
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Model size

35B

Peak speed

193.7 tok/s

Average speed

190.9 tok/s

Min memory

n/a

Max context

65,536 tokens

Avg runtime / run

2m 30s

Avg quality

82.1

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)
Overall81.682.182.5
Agent Workflow85.685.785.7
Code Generation72.273.474.6
Role Play & Narrative79.984.488.8
Research & Analysis83.584.986.2

Performance by hardware and tool

Every hardware/tool/quantization combination mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 5090vLLM—193.7 tok/s190.9 tok/sn/a65,536 tokens82.12

Benchmark runs

All 2 mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

Is mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF good for agentic (tool-using) tasks?
In our benchmarks, mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF scores 85.7/100 for agentic workflows. It runs at about 190.9 tok/s, so if you want more speed, swift-1.5-qwen3.8-27b-uncensored is faster (~277.4 tok/s) and still scores well for agentic workflows (84.1/100).
How fast is mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF for local inference?
Across 2 community benchmark runs, mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF reaches up to 193.7 tok/s and averages 190.9 tok/s, with the fastest results on NVIDIA GeForce RTX 5090.
Which tools have been used to run mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF?
Benchmarks were submitted using vLLM. Results are community-contributed and updated as new runs arrive.