Life & fun · alternatives · 2026

24 alternatives to T0: We trained a 256M SOTA open-weights time-series forecasting model

An open-weights time-series forecasting foundation model from The Forecasting Company. - theforecastingcompany/tfc-t0

T0 is an open-weights time-series forecasting model with 256 million parameters developed by The Forecasting Company. It is designed for users who need to predict future values in sequential data across various… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
OpenAI Open Models▲480
gpt-oss-120b and gpt-oss-20b open-weight language models
2025 · openai.com · its alternatives →
2
TensorFlow 1.0▲823
Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
3
TabPFN v2 – A SOTA foundation model for small tabular data▲153
I am excited to announce the release of TabPFN v2, a tabular foundation model that delivers state-of-the-art predictions on small datasets in just 2.8 seconds for classification and 4.8 seconds for regression compared to strong baselines tuned for 4 hours. Published in Nature, this model outperforms traditional methods on datasets with up to 10,000 samples and 500 features. The model is available under an open license: a derivative of the Apache 2 license with a single modification, adding an enhanced attribution requirement inspired by the Llama 3 license:…
2025 · nature.com · its alternatives →
4
Are You in the Weights?▲471
With more traffic moving off-web and into LLMs, I got curious about what traces we leave "in the weights". My design partner and I built a site in the past few weeks that checks recognition across frontier and small models. It queries many of them in parallel, clusters the responses, and tells you how strongly they recognize you. Happy to answer any questions here!
Jun 2026 · intheweights.com · its alternatives →
5
A high-performance TensorFlow library for quantitative finance▲153
High-performance TensorFlow library for quantitative finance. - google/tf-quant-finance
2021 · github.com · its alternatives →
6
Moonshine Open-Weights STT models – higher accuracy than WhisperLargev3▲316
I wanted to share our new speech to text model, and the library to use them effectively. We're a small startup (six people, sub-$100k monthly GPU budget) so I'm proud of the work the team has done to create streaming STT models with lower word-error rates than OpenAI's largest Whisper model. Admittedly Large v3 is a couple of years old, but we're near the top the HF OpenASR leaderboard, even up against Nvidia's Parakeet family. Anyway, I'd love to get feedback on the models and software, and hear about what people might build with it.
Feb 2026 · github.com · its alternatives →
7
Dream 7B▲191
Powerful Open Diffusion LLM, Beyond Autoregressive
2025 · hkunlp.github.io · its alternatives →
8
Python SDK – forecasting with foundation time-series and tabular models▲43
We’ve built a Python SDK for running inference on foundation models designed for time-series and tabular data. They are new SOTA models for time-series and tabular tasks and work out of the box. They do not require model training or feature engineering. The link to the GitHub repository is: https://github.com/S-FM/faim-python-client
Dec 2025 · github.com · its alternatives →
9
TensorZero▲307
Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
10
Arkor▲142
Fine-tune and Deploy Open-weight Models in TypeScript
Jul 2026 · arkor.ai · its alternatives →
11
TabPFN-2.5 – SOTA foundation model for tabular data▲73
I am excited to announce the release of TabPFN-2.5, our tabular foundation model that now scales to datasets of up to 50,000 samples and 2,000 features - a 5x increase from TabPFN v2, published in the Nature journal earlier this year. TabPFN-2.5 delivers state-of-the-art predictions in one forward pass without hyperparameter tuning across classification and regression tasks. What’s new in 2.5: TabPFN-2.5 maintains the core approach of v2 - a pretrained transformer trained on more than hundred million synthetic datasets to perform in-context learning and output a predictive distribution for…
Nov 2025 · priorlabs.ai · its alternatives →
12
Inkling▲181
Open weights 975B multimodal model built for fine-tuning
Jul 2026 · thinkingmachines.ai · its alternatives →
13
LockedIn▲134
Fast, Accurate Forecasting with your Excel Data
2024 · app.roadmap-tech.com · its alternatives →
14
Fine-tune an 8B model on a 4 GB laptop GPU▲139
Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup
Aug 2026 · github.com · its alternatives →
15
Dolly▲113
Democratizing the magic of ChatGPT with open models
2023 · github.com · its alternatives →
16
Initial release of the distributed TensorFlow runtime▲85
An Open Source Machine Learning Framework for Everyone - tensorflow/tensorflow/core/distributed_runtime at master · tensorflow/tensorflow
2016 · github.com · its alternatives →
17UD
Unify – Dynamic LLM Benchmarks and SSO for Multi-Vendor Deployment▲91
Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024 · its alternatives →
18
ADTK – new Python library for time series anomaly detection▲67
A Python toolkit for rule-based/unsupervised anomaly detection in time series - arundo/adtk
2019 · github.com · its alternatives →
19
A perceptron with stochastic gradient descent in Go▲94
A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go
2017 · github.com · its alternatives →
20
Fine-grained stylistic control of LLMs using model arithmetic▲85
We developed a new framework that enables flexible control of generated text in language models. By combining several models and/or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https://arxiv.org/abs/2311.14479. Feedback and potential applications are welcome.
2023 · github.com · its alternatives →
21
TensorFlow 1.0▲80
Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
22
TuneTrain.ai▲79
Do you know that Small Language Models (SLM) can outperform LLMs if trained (fine-tuned) on domain specific datasets, like your companies knowledge base? The issue: fine-tuning a SLM usually requires a dataset of 10k - 100k records, which is huge. I created a platform for applying "human in the loop" augmentation techniques on your small dataset, so that you can start with maybe 100 records and build-up quickly huge datasets and launch a training without prior knowledge. I implemented 2 techniques, based on LLM distillation, however: more to come. HN, what Do you think? Do you see value in…
2025 · tunetrain.ai · its alternatives →
23
Foundation models for time series forecasting▲5
After months of brewing the perfect recipe in our AI kitchen, we're beyond excited to introduce Sulie - a fully managed (Model as a Service) platform for time series forecasting that actually works! From day one, we've had one mission: make powerful time series forecasting as easy as ordering your morning coffee. Now, businesses can make accurate forecasts from their data without the hassle of building complex models from scratch. We kept hearing the same frustrations from data teams trying to work with foundation models for time series forecasting: 1. "The zero-shot performance is about as…
2024 · github.com · its alternatives →
24
Ideogram 4.0 – open-weight 9.3B text-to-image model▲46
It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch. We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control. It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU. For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/ We will be happy to answer any questions :)
Jun 2026 · github.com · its alternatives →

Also compare

Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →