The fifty models worth knowing about.

Tops the Artificial Analysis Intelligence Index at roughly 66. Cache reads at $0.25, a quarter of Fable 5 and of every other Claude model.

Fable 5.1's specs and price, restricted to Project Glasswing participants. Scores 60.9 on Terminal-Bench 4.0 against Fable's 55.8.

Anthropic's recommended starting tier and the coding arena leader. 63.1 on the Artificial Analysis index at half Fable pricing.

Leads OCR and visual question answering on the Nanonets document leaderboard, and handles sparse tables at 94% where most pipelines break.

The prior OpenAI flagship and still the right default for most production work at two and a half times less than Astra.

First model rated Critical for cyber under the Preparedness Framework. Records on computer use and terminals, fourth on a third-party intelligence index.

Consistently in the top five on public leaderboards. We have not run it on customer tasks, so we do not have a view worth publishing yet.

Beats Claude Opus 4.6 Max on SWE-bench Pro and OSWorld in Alibaba's table, at 27B under Apache 2.0. Second most-liked model on Hugging Face.

The largest open-weight model shipped, at 2.8 trillion parameters, and third on the Artificial Analysis index by third-party trackers.

The DeepSeek flagship, MIT licensed. Second on CyberGym behind GLM-5.3, and a long-standing favourite for self-hosted agent work.

OpenAI's open-weight release under Apache 2.0. Notable less for its scores than for existing at all, and 5.2M downloads a month.

Beats Claude Opus by 22 points on AndroidWorld device automation. Frontier scores at roughly 6B inference cost, on a 180B machine.

MIT at 304B and 4.5M downloads a month. Widely described as the strongest cost-and-agent option among downloadable weights.

Google's open-weight line, 8.6M downloads a month. The gemma-4 family dominates the any-to-any category on Hugging Face.

MIT at 320B, multimodal, and four points behind its own flagship. The most permissive licence attached to a model this size.

Level with GPT-5.6 Sol on Terminal-Bench 2.1 at a seventh of the input price, and state of the art on CyberGym vulnerability discovery.

Meta's move to Apache 2.0 and to a dense architecture, away from the Llama Community Licence and mixture-of-experts.

21M downloads a month, more than any frontier open model. Small enough for on-device, browser and edge-runtime inference.

The workhorse size. Still 13M downloads a month a year after release, and where most self-hosted pilots start.

Top of the Hugging Face trending list on the day we checked, on 697 likes against 7.2k downloads. Attention arriving well ahead of adoption.

2.7M downloads and 4.2k likes. Document extraction as a dedicated model rather than a prompt to a general vision-language model.

14.5M downloads a month. Fits on a single accelerator, which makes it the open-weight default for document and screen work.

Tops OmniDocBench at 94.37 overall, ahead of every general model on that test. A parser rather than a reasoner.

The most-liked model on Hugging Face, full stop, at 14,508 likes. Note the licence: the dev weights are non-commercial.

The commercially usable FLUX. Apache 2.0 where the dev weights are not, which is the version most products actually ship.

5.2k likes and 690k downloads. The Alibaba-adjacent entry in open image generation, and a genuine FLUX alternative.

Token-priced rather than per-image, so you cannot quote a cost per picture until you measure your own prompts.

Per-image pricing you can put in a quote: $0.134 at 1K or 2K, $0.24 at 4K, half that on batch. SynthID on every output.

5M downloads and 5k likes, with a whole ecosystem of turbo, quantised and LoRA derivatives already on Hugging Face.

1.6M downloads and 3.1k likes. The other serious open video model, and the one with the longer track record.

The model that made transcription a commodity. Still 6.2k likes and 5M downloads, and still the answer when audio cannot leave your network.

9.1M downloads a month for the job the transcription models do not do: working out who was speaking.

6.9M downloads a month, more than the model it distils. The default self-hosted transcription choice on constrained hardware.

Very fast transcription at 0.6B. The pick when throughput per GPU matters more than the last point of accuracy.

3.3M downloads a month. Open-weight transcription at a size you can genuinely self-host on modest hardware.

Mistral's realtime speech model under Apache 2.0, at 2.2M downloads. The European option where that matters for procurement.

Whisper rebuilt as a streaming model. Removes the chunk-and-stitch layer every live Whisper deployment has had to write.

About $0.27 an hour, cheaper than the legacy whisper-1 endpoint and stronger. The model most transcription pipelines should default to.

6.8k likes and 11.5M downloads at 82 million parameters. Proof that speech synthesis does not need a large model.

2.6M downloads. Voice cloning on open weights, which is a capability and a governance question in equal measure.

251 million downloads a month, the most-downloaded model on Hugging Face by a factor of three. Still the default first embedder.

37.7M downloads. Multilingual, multi-granularity, and the usual upgrade from MiniLM once retrieval quality starts to matter.

Google's small embedder, trending hard at 2.3M downloads. Built for on-device retrieval where the vectors never leave the phone.

16.2M downloads, with Matryoshka dimensions so you can trade vector size against recall without re-embedding.

18M downloads. Reranking is the cheapest quality win in a RAG pipeline and this is the model most teams reach for first.

85.9M downloads a month, the second most-downloaded model on Hugging Face. Old, small, and still extremely hard to beat on cost.

Zero-shot forecasting from a pretrained model, no per-series training. Trending at 272k downloads within days of release.

23.9M downloads a month. Foundation models for forecasting have quietly become the default, and this is the most used of them.

50.7M downloads a month, seven years on. A reminder that most production NLP is not a frontier model and never was.

20.5M downloads a month. Still the backbone under a large share of image search, moderation and zero-shot classification.