peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF-MTP
Image-Text-to-Text • 0.4B • Updated • 3.02M • 340
jay armstrong
jayarmstrong
·
AI & ML interests
building the next
Recent Activity
liked a model 3 days ago
peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF-MTP liked a model 3 days ago
Cloudflare/clef liked a model 5 days ago
Qwen/Qwen3.8-Flash-NextOrganizations
None yet
liked 2
models 3 days ago
liked a
model 5 days ago
liked a
model 6 days ago
liked a
model 8 days ago
liked a
model 23 days ago
liked 3
models 25 days ago
reacted to SeaWolf-AI's post with 👍 27 days ago
Post
4,122
🏆 Darwin-27B-ZTC-v2 just took #1 on the System One Mosaic Benchmark (S1MB).
S1MB compares 102 models across 137 specialized benchmarks, in three task types: Noul (assess a condition), Choice (select an option), Score (rate on a scale). Ranking is by overall Borda score.
📊 Top of the board
🥇 Darwin ZTC v2 (FINAL-Bench) 89.58
🥈 OpenJev-27B 87.50
🥉 AutoJev-27B 87.07
4️⃣ Eikos 27B 85.43
5️⃣ Jev 1.13 85.05
🔎 Ranks 2 to 5 are all the JEV family (TypeSafe AI's System One model, from ex-OpenAI researchers). S1MB exists to compare these System One judges, so leading it is the headline.
⚙️ Why a zero-token judge wins here
🔹 It does not generate. It reads the input and typed questions and returns a calibrated distribution in a single forward pass.
🔹 Zero generated tokens, no decoding loop, so latency and cost stay low.
🔹 Holds up out of distribution too: General Noul 96.00, General Choice 99.34.
It is also #1 on the typed-decisions leaderboard (0.743, zero-shot). Same message from both: a deterministic, calibrated judge at one forward pass per call.
🔗 Model: FINAL-Bench/Darwin-27B-ZTC-v2
🔗 Leaderboard: hotchpotch/S1MB-leaderboard
Standings move as new models are added. Numbers reflect the board at the time of writing. 🙌
S1MB compares 102 models across 137 specialized benchmarks, in three task types: Noul (assess a condition), Choice (select an option), Score (rate on a scale). Ranking is by overall Borda score.
📊 Top of the board
🥇 Darwin ZTC v2 (FINAL-Bench) 89.58
🥈 OpenJev-27B 87.50
🥉 AutoJev-27B 87.07
4️⃣ Eikos 27B 85.43
5️⃣ Jev 1.13 85.05
🔎 Ranks 2 to 5 are all the JEV family (TypeSafe AI's System One model, from ex-OpenAI researchers). S1MB exists to compare these System One judges, so leading it is the headline.
⚙️ Why a zero-token judge wins here
🔹 It does not generate. It reads the input and typed questions and returns a calibrated distribution in a single forward pass.
🔹 Zero generated tokens, no decoding loop, so latency and cost stay low.
🔹 Holds up out of distribution too: General Noul 96.00, General Choice 99.34.
It is also #1 on the typed-decisions leaderboard (0.743, zero-shot). Same message from both: a deterministic, calibrated judge at one forward pass per call.
🔗 Model: FINAL-Bench/Darwin-27B-ZTC-v2
🔗 Leaderboard: hotchpotch/S1MB-leaderboard
Standings move as new models are added. Numbers reflect the board at the time of writing. 🙌
liked a
model about 1 month ago
🚩 Report: Spam
👍 16
11
#5 opened 3 months ago
by 
mansour94
liked 6
models 3 months ago
meta-models/Muse-Glimmer-30B-GGUF
Image-Text-to-Text • 28B • Updated • 237k • 391
rdtand/Qwen3.8-27B-PrismaAQUA-5.5bit-vllm
Image-Text-to-Text • 19B • Updated • 648 • 29
cyankiwi/Qwen3.8-27B-AWQ-INT4
Image-Text-to-Text • 28B • Updated • 1.1M • 131
Qwen/Qwen3.8-27B
Image-Text-to-Text • 28B • Updated • 8.04M • • 19.2k
RichWoollcott/architect-agent-gemma4-26b-moe
Text Generation • 27B • Updated • 13 • 1
google/diffusiongemma-26B-A4B-it
Image-Text-to-Text • 26B • Updated • 626k • 1.32k
upvoted a collection 4 months ago
liked a
model 4 months ago
