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Comparison·Models & Products·2026-10-13 22:37

Drex 1.5 vs Decision-1: The Models That Score, Not Write

Decision models became October's hottest new category: Nace.AI open-sourced Drex 1.5, an 8.95B scoring model, while Microsoft countered with Decision-1, a closed service post-trained from Qwen3.5-9B — both output option probabilities, never text.

AI-generated face-off cover: two decision-chip cards side by side — Drex 1.5 dial at 58.08 (Decision Index 0.3.1), Decision-1 dial at 83.5% (Microsoft 36-benchmark accuracy) — with a white headline on top
AI illustration: Nace.AI Drex 1.5 vs Microsoft Decision-1 decision-model face-off.

Latest

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  1. Compare published: Drex 1.5 vs Decision-1.

Side by side

✓ marks the side that wins the row
Item Drex 1.5 Decision-1
Publisher & dateNace.AI, launched around October 9, 2026 (OpenRouter lists Oct 9)Microsoft, October 9, 2026 (Command Line blog)
Price$0.04 input / $0 output per million tokens (OpenRouter)✓$0.042 input / output free per million tokens (Microsoft)
Context16,384 default, up to 131,072 (model card)✓32,768 (Microsoft)
OpennessOpen weights under Nace.AI Open RAIL-M; runs locally on one GPU or a Mac✓Hosted API only (Microsoft Foundry, OpenRouter); no open weights
Vendor-reported benchmark58.08 on Decision Index 0.3.1 (Nace model card)83.5% average accuracy across 36 benchmarks, highest in Microsoft's test (Microsoft internal testing)

Verdict

How to choose: for local deployment or weight modification, look at Drex 1.5 (open weights, runs on one GPU); for a Microsoft-hosted low-latency scoring service, look at Decision-1 (85ms P50, free output).

01What they are

Drex 1.5 is the decision model Nace.AI released around October 9, with 8.95 billion parameters and open weights (Nace.AI Open RAIL-M license). It generates no text: given a state (text or JSON) plus typed questions (choice, yes/no, ordinal score), a single forward pass returns a calibrated probability for each option via POST /v1/systemone, compatible with TypeSafe's Jev decision API. Default context is 16,384 tokens, expandable to 131,072; bf16 weights are about 18GB, runnable on one CUDA GPU, and a 9.5GB Q8_0 GGUF build runs on Apple silicon or CPU.

Decision-1 is the decision-scoring model Microsoft announced October 9 on its Command Line blog, post-trained from Alibaba's Qwen3.5-9B; Microsoft says it will later rebase it on its own models and OpenAI's. It is hosted-API only (Microsoft Foundry and OpenRouter) with no open weights; context is 32,768 tokens, input $0.042 per million tokens, output free. Microsoft reports the highest average accuracy, 83.5%, in a 36-benchmark comparison (nearly 150,000 questions kept blind from training), with 85ms P50 latency — 2.5x faster than H2O-Lightning-4B and 35x faster than GPT-6 Sol — all from Microsoft's internal testing.

02Side-by-side comparison

The table below compares public pricing, context, openness and vendor-reported benchmarks; note the two cite different benchmark suites, so the scores are not directly convertible.

03Key facts

  1. Launch: Drex 1.5 went live around October 9 (OpenRouter lists 2026-10-09); Microsoft announced Decision-1 on October 9 on its Command Line blog.
  2. Pricing: Drex 1.5 is $0.04 input / $0 output per million tokens on OpenRouter; Decision-1 is $0.042 input per million tokens with free output (Microsoft).
  3. Benchmarks: Drex 1.5 scores 58.08 on Decision Index 0.3.1 (Nace model-card data, highest under 10B parameters); Decision-1 averages 83.5% accuracy in Microsoft's 36-benchmark comparison (Microsoft internal testing). The suites differ and are not directly comparable.
  4. Openness: Drex 1.5 has open weights (RAIL-M license) and supports local deployment; Decision-1 is hosted-API only, with no open weights or local build.

Why it matters

two new 9B-class decision models arrived within a week — Drex 1.5 is open-weight and locally deployable, while Decision-1 runs as a Microsoft-hosted service at 85ms latency.
Useful Tap if this story helped you

SourcesMarkTechPost (2026-10-09, source); OpenRouter (2026-10-09, source); Microsoft Command Line blog (2026-10-09, source); The Register (2026-10-10, source). This article is compiled from public information and does not constitute investment advice.

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