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Run this exact model through an API. Open Ornith-1.5 35B-A3B on tiyuvta and use model idornith-ai/ornith-1.5-35b-a3b. The first 200 requests each month are free, then pay per token with no subscription or minimum. Get an API key and send the first request →
memra-server)<think> reasoning)| Base | ornith-ai/Ornith-1.5-35B-A3B (MIT), official BF16 GGUF (qwen35moe, 41 blocks incl. NextN) |
| Head training | mtp.* only, continued-trained on the model's own generations (4,044 prompts, ~2.1M sampled tokens at the vendor serving temperature), depth-3 chain-rollout, frozen trunk; recipe + receipts: memra research/ornith15-mtp-train-20260820/ |
| Quantization | llama-quantize NVFP4 ftype (imatrix-aware branch), --output-tensor-type q5_k --token-embedding-type q5_k; head quantized after training (NVFP4 head measured at zero acceptance cost on this pipeline) |
| Main file | Ornith-1.5-35B-A3B-NVFP4-Q5K-mtp.gguf, 20,188,038,400 B, sha256 72ff9600aa2b0de77a5b27041a84448c2ce88c7b2055529fc23b3cd5bf518fd3 |
| Exactness | memra batteries, 2026-08-20: run-spec K=1..8 self-consistency PASS (spec ≡ plain greedy, token-identical) · chat-templated generation probes coherent · serve-level A/B accounted per-request (usage.spec) |
mtp-Ornith-1.5-35B-A3B-NVFP4-frspec-owngen32768.gguf (0.9 GB, sha256 46f0dd4c…73fe899) —
standalone speculative-decode draft from the trained MTP block: lm head masked to the
top 32,768 of 248,320 rows, ranked by the model's own generations (external text used as
prompts only), then requantized in the mask-first order — NVFP4 head, Q4_K_M block. Ranks ship
as ornith15-ranks-owngen-32768.txt (drives memra's load-time head mask on safetensors trunks
via MEMRA_FRSPEC_TRIM) and as .gguf. A mask can never change output; it moves draft
acceptance (measured 0.393 vs 0.431 embedded at K=3) against a smaller head read.head-Ornith-1.5-35B-A3B-frspec-owntrim-q5k-32768.gguf (46 MB, sha256
d7c47026e232c0d19240e6ecb3ec9702751fc68dec82909bec79b909846b3b4d) — the top-32,768
own-generation-ranked rows of this artifact's own Q5_K output.weight, byte-gathered
(zero requant) plus the d2t map. memra's MEMRA_FRSPEC_TRIM consumes it (or the ranks
file directly) to trim the DRAFT lm_head from 248,320 to 32,768 rows (~221 → ~29 µs per
draft step). Verify stays full-vocab, so output is unchanged by construction; measured
serve effect on one RTX PRO 6000 Blackwell (ABBA, N=6/shape, 2026-08-22): single-stream
short prompts +10%, shared-prefix c8 +2.9%.MEMRA_SPEC_PHASE=1 the round splits verify-issue 50–58%, host-commit 24–26%, draft 19–25%
and verify-wait 0.0% — the GPU is never what the host waits for. Measured consequence,
same GPU / same binary / same artifact: a Zen 3 host (~3.4 GHz) serves 195–230 tok/s
while a Zen 5 host serves 326–354. A cold host also reads low until its clocks ramp.
Receipts: memra research/orndecode-20260822/.1MEMRA_FRSPEC_TRIM=ornith15-ranks-owngen-32768.gguf \
2MEMRA_PRIME_CHUNK=0 \
3memra-server --model Ornith-1.5-35B-A3B-NVFP4-Q5K-mtp.ggufmtp-…-frspec-owngen32768.gguf) remains published for
external-attach engines; on memra the self-trim of the embedded head is the faster route
(the external attach forgoes the resident graph-draft path). Built with
tools/make-trimmed-draft.sh + frspec-owngen from the memra repo.