MoE enthusiast**~36B total, ~3B active per token (MoE)** - the local-favorite Ornith-1.5 size, released 2026-08-18. Activates only 3B parameters per token yet outperforms dense models like Gemma 4-31B and Qwen 3.6-35B on agentic coding. 262K context, MIT-licensed on HuggingFace at ornith-ai/Ornith-1.5-35B-A3B
(GGUF, FP8, and NVFP4 quantizations). #
**Coding (vendor self-reported):** Terminal-Bench 2.1 67.8, SWE-bench Verified 79.0, SWE-bench Pro 59.6, NL2Repo 46.2. -
**Reasoning:** HLE 25.6 (no tools) / 33.4 (with tools), GPQA-Diamond 89.2. -
Agentic: MCP-Atlas 70.2, Toolathlon-Verified 48.7, ClawEval 72.5.
Local-friendly. Runs on enthusiast-class GPUs via GGUF quantizations; a strong open-weight pick for local agentic coding. Vendor benchmarks are claims pending independent replication.
- 36.0B
- 262k
- mit
- 🇺🇸 USA
- Aug 2026
Scores #
Run it locally #
Per-quant memory needs and a static "can you run it?" reference - no rig entry required
Can you run it? - reference rigs
| Rig | Q4_K_M | Q5_K_M | Q6_K | Q8_0 | BF16 |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | |||||
no -> cloudno -> cloudno -> cloudno -> cloudno -> cloudno -> cloudno -> cloudno -> cloudno -> cloudno -> cloudno -> cloudFit tiers use the same will-it-run logic as the rig finder. For comfortable fits, the badge reflects decode speed: fast >=20 t/s, ok 8-20 t/s, slow <8 t/s. t/s is a bandwidth estimate, not a measured benchmark.
Download options #
Or run it in the cloud #
No per-token API provider pricing tracked for Ornith-1.5-35B-A3B yet.
For flagship list prices, see the
[calculator](/calculator).
Inference cost over time #
Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.