THE AI MODEL DIRECTORY Start exploring models here

Find your ideal AI model.

From language to images, open weights to APIs. Understand capabilities and compare real costs.
Find the right engine for your next idea.

Explore AI models 3

Provider Input Output License

Discover models worth your attention

DeepSeek-V4.1-Flash-EXL3-2.7bpw

sudoingx

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Basic profile indexed · More details to follow

Category pending

Input Not verified→ Output Not verified

Price not verifiedCheck multimodal and channel pricing separately

View details ↗

CompareSource / docs ↗

Offrail-27B-Uncensored

sudoingx

27B for 8GB and 12GB cards. OS-Software's uncensored Heretic build of Ternary Bonsai 2 27B (the 1.75 bpw PTQ1_0 file, 5.95 GB) with the Qwen 3.8 27B multi-token-prediction head grafted back on as block 64, so the PrismML llama.cpp fork runs `--spec-type draft-mtp` on it. The body is not ours: OS-Software baked a Heretic LoRA (rank 128, layers 27-44) into the official PQ2_0 ternary codes and kept the block scales, and their card calls it an approximate merge. Their test: **0/100 refusals** against the original's 95/100 at KL divergence 0.0135, WikiText-2 perplexity 10.1435. Their test, not ours: we have not run a refusal baseline of our own (HarmBench needs a second GPU for its judge model). What is ours: the graft, the two merged files and the graft tooling, plus the PTQ1_0 mat-vec kernel (PrismML-Eng/llama.cpp#218) on top of PrismML's fork. What is not ours: the head's weights are Qwen's, the MTP graph and the `GGML_CUDA_BATCH_INVARIANT` switch are PrismML's fork, the uncensoring is OS-Software's, the compression is PrismML's.

Text generation

Input Text→ Output Text

Price not verifiedCheck multimodal and channel pricing separately

View details ↗

CompareSource / docs ↗

Ternary-Bonsai-2-27B-PTQ1_0-MTP-GGUF

sudoingx

One line installs it on the card you already own, RTX 20, 30, 40 and 50, and AMD Radeon in beta, with 8 GB or more: it picks the build and the model file for your VRAM, checks every SHA256 and starts it, with the chat page at `http://127.0.0.1:8899` and an OpenAI-compatible API at `/v1` (model `bonsai-2-27b`). Windows, in PowerShell (measured on native Windows on an RTX 3060 12GB and an RTX 5070 Ti 16GB; RTX 20 in beta): AMD Radeon (beta): the same two lines, on PrismML's own Vulkan build, no ROCm to install. 8 GB cards get up to 64K, 12 GB about 195K, 16 GB and up the full 262K with vision, all from the files in this repo; the cards and the numbers are in Radeon (beta).

Text generation

Input Text→ Output Text

Price not verifiedCheck multimodal and channel pricing separately

View details ↗

CompareSource / docs ↗

COST EXPLORER

Great models. Clear costs.

Cost analysis

Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

MODEL HANDBOOK

Understand before you choose

Selection guide & FAQ

How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

Find your ideal AI model.

Explore AI models 3

DeepSeek-V4.1-Flash-EXL3-2.7bpw

Offrail-27B-Uncensored

Ternary-Bonsai-2-27B-PTQ1_0-MTP-GGUF

No matching models

Great models. Clear costs.

Understand before you choose

Follow trends. Find tools. Explore models.