If you want a writing model you can run yourself, fine-tune, or build a product on without asking anyone, you need open weights and a licence that lets you use them. Hemmingway-1 has both, and it was built for one job: writing that sounds like a person wrote it.
What it is
| Parameters | 27B |
|---|---|
| Built on | Qwen3.8-27B |
| Context | 262,144 tokens |
| Licence | Apache-2.0, including commercial use |
| Weights | huggingface.co/Altworld/Hemmingway-1 |
| Code | github.com/lukeckprobierts/Hemmingway-1 |
How it scores against open and closed models
The most telling comparison for an open model is against the model it started from. Hemmingway-1 is Qwen3.8-27B trained further for writing, so the base model's scores show what the training did.
| Test | Hemmingway-1 | Qwen3.8 27B (base) |
|---|---|---|
| CommunicationBench (everyday writing) | 1026 | 954 |
| Human-Likeness | 1032 | 952 |
| StoryBench (creative writing) | 1197 | 693 |
Against much larger models, on everyday writing it came first of all we tested, level with Fable 5.1 and ahead of Fable 5, GLM-5.3, Kimi K3, GPT-6 Astra, Grok 4.6 and DeepSeek V4 Pro. On the public EQ-Bench 4 it placed third. On long stories it sits level with Kimi K3, ahead of Qwen3.8 Max and DeepSeek V4 Pro, and behind Fable 5 Max and GLM-5.3. All of the scores are on the model card.
CommunicationBench, Human-Likeness and StoryBench are our own benchmarks. Every matchup was blind, run in both orders, and judged by a model that was not one of those being judged. EQ-Bench 4 is not ours.
Running it
With vLLM:
vllm serve Altworld/Hemmingway-1 --max-model-len 262144
Or with Transformers, as a normal chat model: load Altworld/Hemmingway-1 with AutoModelForCausalLM and AutoTokenizer, and build the prompt with the tokenizer's chat template. The README on GitHub has a full example.
Or skip the hardware
If you would rather not run a 27B model yourself, the same model is behind an OpenAI-compatible API as hemmingway-27b. Most code that already talks to a model needs two lines changed. The API docs are here, and keys are on the API platform.
What it is not good at
It is English-first. It can be wrong and still sound certain, so do not use it to decide anything medical, legal or financial. And for very long fiction, the largest story models are better.