AI NEWS.ccAI is happening. The future is updating.
♡ Saved tools 0
AI NEWS · Model intelligenceExplore capabilities. Make informed choices. ↗Profiles indexed first · Details continuously enriched
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.

Popular searches
84,991 model profiles13202 providers / publishers45 capability categories465 with comparable prices · 30 benchmarked
TText generation▧Image generation▷Video generation⌘Code generation◖Speech synthesis♫Music generation⬡3D modeling▤Document analysis
DISCOVER & COMPARE

Explore AI models 84991

Discover models worth your attention

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。

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

An 8B cybersecurity agent (offense + defense) fine-tuned from `Qwen/Qwen3-8B` on **2197 verified agentic + Q&A traces**, distilled from GLM-5.2 (round 4) and Kimi K3/K2.6 (rounds 1–3). Trained to operate an autonomous security harness — plan, run bash, read observations, write files, finish — not just answer security questions. Pipeline per iteration: failure analysis on eval traces → parameterized, decontaminated seed factory → teacher best-of-3 rejection-sampled agentic transcripts (judged + artifact-checked) → full-FT SFT → multi-run attack/defend eval → next round. Run-to-run variance is significant at temperature 0.7; single-run scores are not meaningful for this suite. Known v4 gap: `atk-sqli` — the model prefers to start the staged vulnerable app and fuzz it over HTTP instead of reading the offline artifacts (trace-verified behavioral prior, targeted in round 5).

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

Mithra-2B

Bedirhn77

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

Text generation
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

Anima-FP8

Bedovyy

To use torch.compile on FP8/MXFP8 models, set to `max-autotune-no-cudagraphs` mode and dynamic to `false`. Tested on - RTX5090 (400W), ComfyUI(commit id `c96fcdd`) with `--fast` option, torch2.12.0+cu130 - Generates 832x1216, 30steps, cfg 5.0, er_sde, simple

Image generation
Input Text→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

Anima-GGUF

Bedovyy

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。

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

Anima-INT8

Bedovyy

ComfyUI has native INT8 support as of commit 1a510f0, but it currently rejects the `int8_rowwise` format and offers no real speedup over BF16. I have updated (int8rowwise](anima-base-v1.0-int8rowwise.safetensors) model for ComfyUI native support. If you need better quality (but slower), please use the int8convrot model. - ComfyUI commit 264b003 - ComfyUI-INT8-Fast commit 7ff676c - use `--fast fp16_accumulation fp8_matrix_mult cublas_ops --use-sage-attention --disable-dynamic-vram` options - Tested on 18/05/26 > Δ it/s = (INT8 − BF16) / BF16 × 100 · Δ Time = (BF16 − INT8) / BF16 × 100 · positive = INT8 faster

Image generation
Input Text→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

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。

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

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 ↗
Source / docs ↗

1. Download https://github.com/bedovyy/comfy-dit-quantizer 2. activate python environment from ComfyUI. 3. `quantize.py configs/qwen-image-edit-2511.json uncalibrated.safetensors` 4. `add_input_scale.py calibs/qwen-image-edit-2511.json uncalibrated.safetensors `

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

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。

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗
COST EXPLORER

Great models. Clear costs.

Cost analysis

Adjust monthly token usage to compare estimated API costs.

1 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.

AI NEWS · From information to decisions

Follow trends. Find tools. Explore models.

Explore AI news ↗Discover AI tools ↗