Qwen3.5-9B
A 9-billion-parameter model from Alibaba's open-source Qwen series of large language models. It is a mid-scale general-purpose language model suited for scenarios that require a balance between inference cost and model capability.
Core Facts
Timeline (last 90 days)
Microsoft's Microsoft-Decision-1 claims a decision speed 35 times faster than GPT-6, and its base model is Alibaba's open-source Qwen3.5-9B.
On the Qwen3.5-9B model, SchemaShield-Lite raised accuracy on the DICE-300 benchmark from 0.717 to 0.813, recovering 19 of the 22 drift-induced failures.
Dory scores 61.8 on SWE-bench Verified (4 loops, NVIDIA's own testing), while Qwen3.5-9B scores 61.
CARE is currently validated only on four LIBERO suites and two agents (Qwen3.5-9B and Llama-3.1-8B).
The Cloudflare Clef series is entirely open-weight: Clef is based on Qwen3.8-27B, Clef-flash is based on Qwen3.5-9B, and Clef-omni is a 30B mixture-of-experts model (with 3B active parameters).
On LongBench v1/v2 and MemoryAgentBench, NoteBank also reported improvements, covering everything from three 1.3B research models up to Mamba-2-8B and a trained Qwen3.5-9B.
SpatialOPSD internalizes privileged depth information into a single RGB forward pass through self-distillation, raising spatial reasoning accuracy from 45.9 to 51.9 on Qwen3.5-9B.
The anti-fraud model that Coinbase fine-tuned from open-source Qwen3.5-9B beat Claude Opus 4.5 on its own risk-control benchmark.
ReTerm is built on Qwen3.5-9B, and the resulting ReTerm-9B achieves 34.8% Pass@1 on Terminal-Bench 2.0, an improvement of 14.6 percentage points over the base model.
Microsoft released Decision-1 in Foundry, a post-trained Qwen3.5-9B model designed specifically for single-shot decision scoring, priced at $0.042 per million input tokens, with output free.
11 more timeline events
All Facts (20)
On the B200, the per-step time for LoRA SFT training of Qwen3.5-9B decreased from 0.84 seconds to 0.77 seconds.
70%Partially VerifiedDecision-1 is live on Microsoft Foundry, priced at $0.042 per million input tokens, with output being free.
65%UnverifiedMicrosoft's Microsoft-Decision-1 claims a decision speed 35 times faster than GPT-6, and its base model is Alibaba's open-source Qwen3.5-9B.
50%UnverifiedOn the Qwen3.5-9B model, SchemaShield-Lite raised accuracy on the DICE-300 benchmark from 0.717 to 0.813, recovering 19 of the 22 drift-induced failures.
50%UnverifiedDory scores 61.8 on SWE-bench Verified (4 loops, NVIDIA's own testing), while Qwen3.5-9B scores 61.
50%UnverifiedCARE is currently validated only on four LIBERO suites and two agents (Qwen3.5-9B and Llama-3.1-8B).
50%UnverifiedThe Cloudflare Clef series is entirely open-weight: Clef is based on Qwen3.8-27B, Clef-flash is based on Qwen3.5-9B, and Clef-omni is a 30B mixture-of-experts model (with 3B active parameters).
50%UnverifiedOn LongBench v1/v2 and MemoryAgentBench, NoteBank also reported improvements, covering everything from three 1.3B research models up to Mamba-2-8B and a trained Qwen3.5-9B.
50%UnverifiedSpatialOPSD internalizes privileged depth information into a single RGB forward pass through self-distillation, raising spatial reasoning accuracy from 45.9 to 51.9 on Qwen3.5-9B.
50%UnverifiedThe anti-fraud model that Coinbase fine-tuned from open-source Qwen3.5-9B beat Claude Opus 4.5 on its own risk-control benchmark.
50%UnverifiedReTerm is built on Qwen3.5-9B, and the resulting ReTerm-9B achieves 34.8% Pass@1 on Terminal-Bench 2.0, an improvement of 14.6 percentage points over the base model.
50%UnverifiedIn JetBrains' self-reported evaluations, the 12B MoE Mellum2.1 wins on single-shot code generation tasks (LiveCodeBench, HumanEval+) but loses to the dense 9B Qwen3.5-9B on multi-step agentic benchmarks (SWE-bench Pro, Terminal-Bench).
50%UnverifiedMicrosoft-Decision-1 was built through post-training on Alibaba's Qwen3.5-9B
50%UnverifiedMicrosoft-Decision-1 is priced at $0.042 per million input tokens with no charge for output, is plain-text only, and has a 32k context window.
50%UnverifiedMicrosoft stated that Decision-1 completed its task via post-training based on Qwen3.5-9B and will soon migrate the model to other systems, including Microsoft AI and OpenAI's models.
50%UnverifiedMicrosoft conducted post-training on top of Alibaba's open-source Qwen3.5-9B weights, specifically to perform single-pass decision scoring tasks.
50%UnverifiedMicrosoft-Decision-1 was post-trained from Alibaba's Qwen3.5-9B
50%UnverifiedThe 9B parameter scale is a medium size that strikes a balance between inference cost and capability, making it suitable for high-frequency decision-making scenarios
50%UnverifiedDecision-1 was derived from post-training on Qwen3.5-9B.
50%UnverifiedMicrosoft released Decision-1 in Foundry, a post-trained Qwen3.5-9B model designed specifically for single-shot decision scoring, priced at $0.042 per million input tokens, with output free.
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