# Qwen3.5-0.8B-decision by MLX Community: Open-Weight Model
Source: https://savrn.com/models/qwen3-5-0-8b-decision
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Runs On

What it takes to serve Qwen3.5-0.8B-decision (873M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
| --- | --- | --- | --- | --- | --- |
| 16-bit | 1.7 GB | 2.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 8-bit | 0.9 GB | 1.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 4-bit | 0.4 GB | 0.5 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 12, 2026.

[Qwen3.5-0.8B-decision on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/qwen3-5-0-8b-decision/gpus)

## Model Card

By MLX Community, published under apache-2.0, revision 36e166ca10c4.

### Qwen3.5-0.8B decision model

Qwen3.5-0.8B turned into a decision model with optiq lora train --decision: a LoRA on the backbone and a new joint schema head that scores noul, choice and score questions in one pass. It runs on Apple Silicon through MLX and OptiQ (optiq serve exposes /v1/systemone).

### Typed Decisions result

Scored on the full 400-case test split (2,000 decisions) with the benchmark's own metrics.

| Model | Accuracy | KL from gold ↓ | Brier ↓ | ECE ↓ | p50 latency |
| --- | --- | --- | --- | --- | --- |
| This model | 0.772 | 0.097 | 0.054 | 0.177 | 0.34 s |
| [gemma-4-e2b-it-OptiQ-4bit-decision](https://savrn.com/models/gemma-4-e2b-it-optiq-4bit-decision) | 0.802 | 0.072 | 0.039 | 0.181 | 0.99 s |
| [clef-OptiQ-4bit](https://huggingface.co/mlx-community/clef-OptiQ-4bit) (27B) | 0.719 | 0.189 | 0.102 | 0.118 | 9.7 s |
| Always answer the train-split average | 0.489 | 0.327 | 0.181 | – | – |

Latency is one request per case with all five questions, on an Apple M3 Max.

[Read the full model card (255 words)](https://savrn.com/models/qwen3-5-0-8b-decision/card)

## Configuration

Architecture

Qwen3_5ForConditionalGeneration

Context length (tokens)

262,144

Layers

24

Hidden size

1,024

Feed-forward size

3,584

Attention heads

8

Key/value heads

2

Head dimension

256

Vocabulary size

248,320

Model type

qwen3_5

## Identity and Version

Repository

mlx-community/Qwen3.5-0.8B-decision

Publisher

MLX Community

Task

Not stated by the source

Modality

Other

Library

mlx

Parameters

873M parameters

Languages

mlx

Revision

36e166ca10c4d16471a231d66cfc22d80039fe34

First published

2026-10-08

Last updated

2026-10-11

## Files and Weights

19 files, 1.9 GB in total. The weights are 3 files totalling 1.8 GB in safetensors.

Weights3 files · 1.8 GB

Configuration8 files · 57.4 KB

Tokenizer4 files · 22.9 MB

Documentation2 files · 13.5 KB

Other1 file · 7.8 KB

Repository1 file · 1.6 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| adapters.safetensors | Weights | 40.9 MB | 7ad3e00365ba |
| joint_head.safetensors | Weights | 54.7 MB | 2ab266645287 |
| model.safetensors-00001-of-00001.safetensors | Weights | 1.7 GB | 04b1c301231d |
| .eval_results/typed-decisions.yaml | Configuration | 2.1 KB | — |
| adapter_config.json | Configuration | 479 B | — |
| config.json | Configuration | 2.9 KB | — |
| decision_config.json | Configuration | 97 B | — |
| joint_head_config.json | Configuration | 116 B | — |
| model.safetensors.index.json | Configuration | 50.9 KB | — |
| preprocessor_config.json | Configuration | 390 B | — |
| video_preprocessor_config.json | Configuration | 385 B | — |
| LICENSE | Documentation | 11.5 KB | — |
| README.md | Documentation | 2.0 KB | — |
| chat_template.jinja | Other | 7.8 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| merges.txt | Tokenizer | 3.4 MB | — |
| tokenizer.json | Tokenizer | 12.8 MB | 5f9e4d4901a9 |
| tokenizer_config.json | Tokenizer | 16.7 KB | — |
| vocab.json | Tokenizer | 6.7 MB | — |

## License and Download

License

apache-2.0

Access

Open weights, no gate

Download size

1.8 GB

[Download from MLX Community](https://huggingface.co/mlx-community/Qwen3.5-0.8B-decision)

Released by MLX Community through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0).

## Built From

- Derived from [Qwen/Qwen3.5-0.8B](https://savrn.com/models/qwen3-5-0-8b)

## Evaluations

Each result is shown as reported, with the conditions its reporter stated. None is a SAVRN measurement. A comparison lines two results up only when their configuration, unit and setup are all stated and identical.

| Benchmark | Conditions | Result | Reported by | Revision | Date |
| --- | --- | --- | --- | --- | --- |
| LocalLLaMA/typed-decisions | Task accuracyMetric accuracySetup Fitted by us on the benchmark's own train split only (1,080 records, LoRA on the backbone plus a new schema head), then scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max.Comparison conditions not established | 0.772 | [Typed Decisions leaderboard (README)](https://huggingface.co/datasets/LocalLLaMA/typed-decisions) Reported by a third party | Evaluated revision not stated | 2026-10-11 |
| LocalLLaMA/typed-decisions | Task brierMetric brierSetup Fitted by us on the benchmark's own train split only (1,080 records, LoRA on the backbone plus a new schema head), then scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max.Comparison conditions not established | 0.054 | [Typed Decisions leaderboard (README)](https://huggingface.co/datasets/LocalLLaMA/typed-decisions) Reported by a third party | Evaluated revision not stated | 2026-10-11 |
| LocalLLaMA/typed-decisions | Task eceMetric eceSetup Fitted by us on the benchmark's own train split only (1,080 records, LoRA on the backbone plus a new schema head), then scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max.Comparison conditions not established | 0.1769 | [Typed Decisions leaderboard (README)](https://huggingface.co/datasets/LocalLLaMA/typed-decisions) Reported by a third party | Evaluated revision not stated | 2026-10-11 |
| LocalLLaMA/typed-decisions | Task kl_from_goldMetric kl_from_goldSetup Fitted by us on the benchmark's own train split only (1,080 records, LoRA on the backbone plus a new schema head), then scored on the full 400-case test split (2,000 decisions): one request per case with all five questions, text only, the benchmark's own metrics, MLX on an Apple M3 Max.Comparison conditions not established | 0.0974 | [Typed Decisions leaderboard (README)](https://huggingface.co/datasets/LocalLLaMA/typed-decisions) Reported by a third party | Evaluated revision not stated | 2026-10-11 |

## Memory Requirements

| Precision | Weights in memory |
| --- | --- |
| As published | 1.8 GB |
| 16-bit | 1.7 GB |
| 8-bit | 0.9 GB |
| 4-bit | 0.4 GB |

Weights only, from the published parameter count; the key-value cache and runtime add to this.

## Questions About Qwen3.5-0.8B-decision

### How much GPU memory does Qwen3.5-0.8B-decision need?

About 2.1 GB at 16-bit and 0.5 GB at 4-bit: the weights (873M parameters) plus a working margin. A long context needs more.

### What is the cheapest GPU to run Qwen3.5-0.8B-decision on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

### Can I use Qwen3.5-0.8B-decision commercially?

Yes. Qwen3.5-0.8B-decision is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

### What is Qwen3.5-0.8B-decision's context length?

262,144 tokens, from the maximum position embeddings in its published configuration.

## MLX Community

[All models and datasets](https://savrn.com/model-publishers/mlx-community)

## Versions

- [36e166ca10c4](https://savrn.com/models/qwen3-5-0-8b-decision/versions/36e166ca10c4) · current 2026-10-11

## Explore More

- [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0)
- [Model comparisons](https://savrn.com/models/comparisons)
- [The model directory](https://savrn.com/models)
- [Open model prices by host](https://savrn.com/ai-index/pricing/open-models)

## Source

- Repository metadata, read 2026-10-11.
- [Hugging Face record](https://huggingface.co/mlx-community/Qwen3.5-0.8B-decision)
- [How the hub is built](https://savrn.com/model-hub/methodology)