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primitive-ai
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Model Details
Model Provider
primitive-ai
Model Tree
ornith-ai/Ornith-1.5-35B-A3B
Input Modalities
Output Modalities
Supported Functionality
| call | abstain | knowledge | pooled | tool-calling sd | |
|---|---|---|---|---|---|
| this repo | 77.5 (n=6) | 58.3 (n=6) | 91.5 (n=3) | 89.0 | 1.3 |
| our general build | 74.4 (n=4) | 60.0 (n=4) | 91.7 | 88.7 | 3.1 |
| BF16 reference | 78.6 (n=4) | 61.3 (n=4) | 92.0 | 89.5 | 1.4 |
bash
vllm serve primitive-ai/Ornith-1.5-35B-A3B-agentic-NVFP4-FP8 --max-model-len 32768
Verified to load on Blackwell (native NVFP4/FP8) and on Ampere (A100, weight-only Marlin
path: the BF16 lm_head is what keeps that path loadable).
1,370 items across fourteen public benchmarks. A 1,170-item knowledge suite over nine of them
and a 200-item tool-calling suite over five more (BFCL v4, xLAM/APIGen, ToolACE, Glaive v2, nvidia
When2Call). One fixed protocol for every row: temperature 0.6 / top_p 0.95 / top_k 20, thinking
forced on, a 16,384-token budget, concurrency 32, on one RTX PRO 6000 Blackwell.
| build | size | call | abstain | knowledge | pooled |
|---|---|---|---|---|---|
| BF16 reference | 67.0 G | 78.6 (n=4) | 61.3 (n=4) | 92.0 | 89.5 |
| ornith-ai FP8 | 36.7 G | 79.1 (n=4) | 58.1 (n=4) | 91.2 | 89.0 |
| this repo |
None of the four quants above is distinguishable from another on tool calling. The column spans 2.3 points against per-build sds of 0.6 to 1.3. Every figure is a mean with its n, which matters more on this model than on any other we have measured: a single run of the general build can land anywhere between 67.5 and 75.5, so differences under about 2 points are not differences.
| tensors | format |
|---|---|
all 40 layers' routed experts (gate/up/down_proj) | NVFP4 (group 16) |
self_attn q/k/v/o, linear_attn in/out projections, shared-expert projections | FP8 E4M3 |
lm_head, embeddings, vision tower, MTP block, router gates, norms | BF16 |
Rounding is chosen by GPTQ against a tool-call and agent-trajectory calibration set. Rows sharing a prompt with any eval item were removed first, so the numbers above are measurements, not fits.
call is accuracy on the 160 suite items that require a tool call; abstain is the 40 whose correct action is to call nothing. The two are reported separately because pooling them let abstention discipline masquerade as call accuracy. Split means cover the runs whose per-half records survive; the pooled tool-calling means and their n are unchanged.
| 77.5 (n=6) |
| 58.3 (n=6) |
| 91.5 (n=3) |
| 89.0 |
| ornith-ai NVFP4 | 21.8 G | 76.1 (n=4) | 61.3 (n=4) | 90.9 | 88.3 |
| our general build | 22.6 G | 74.4 (n=4) | 60.0 (n=4) | 91.7 | 88.7 |