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 3

Discover models worth your attention

> **Original model:** NaiveAI/Naive-N0.5-Flash by the > NaiveAI Team, MIT License. > This artifact is quantized from the public FP8 release > NaiveAI/Naive-N0.5-Flash-FP8. > It contains **modified weights** (EXL3 trellis quantization); the original model is © its authors. > Tokenizer and chat template are unchanged from the original. > Served by the veloGB10 engine it is listed by `/v1/models` as **`doth4580/Naive-N0.5-Flash-EXL3-3.5bpw`** (the `model_name:` line of > this card); `base_model:` is the original model it was quantized from, not this pack. An **EXL3 (ExLlamaV3 trellis) 3.5 bpw** quantization of **Naive-N0.5-Flash** — 309B parameters, 15.5B active, native 1M-token context. The pack is **~137 GB (~128 GiB) against ~315 GB for the FP8 original**, which is what lets it fit across **two NVIDIA DGX Spark (GB10)** machines. Quantized with the exllamav3 tooling, adapted for this architecture, run on **8×H100** for speed. It is served on two Sparks with the recipe in **sf-stav/Naive-N0.5-Flash-EXL3-2x-DGX-Spark** — see Serving below.

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

> **Original model:** Qwen/Qwen3.8-Flash-Next by the Qwen > team, released under the Qwen Community License 1.0 — **not** an OSI license; see > License below. This artifact contains **modified weights** (EXL3 trellis quantization); > the original model is © Qwen. **Direct source:** turboderp/Qwen3.8-Flash-Next-exl3, branch/revision **`3.05bpw_h5_ng5`** — 3.05 bpw experts, 5-bit head, n-gram table included. An **EXL3 (ExLlamaV3 trellis) 3.05 bpw** quantization of **Qwen3.8-Flash-Next**: a 125B-parameter mixture-of-experts model with about 6B active parameters, plus a 51B hashed n-gram embedding and a 4B MTP layer, with a vision encoder. The pack is **~85 GB (~79 GiB) against ~360 GB for the original bf16 release**.

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

> **Original model:** Qwen/Qwen3.8-Flash-Next by the Qwen > team, released under the Qwen Community License 1.0 — **not** an OSI license; see > License below. This artifact contains **modified weights** (EXL3 trellis quantization); > the original model is © Qwen. **Direct source:** turboderp/Qwen3.8-Flash-Next-exl3, branch/revision **`4.05bpw_h6_ng6`** (commit `55a732e0c4c3d4614bc42b68493bb930d9b02c0a`) — 4.05 bpw average (4-bit experts), 6-bit head, 6-bit n-gram table. An **EXL3 (ExLlamaV3 trellis) 4.05 bpw** quantization of **Qwen3.8-Flash-Next**: a 125B-parameter mixture-of-experts model with about 6B active parameters, plus a 51B hashed n-gram embedding and a 4B MTP layer, with a vision encoder. It is the higher-quality sibling of the 3.05 bpw pack: about **108 GB on disk** (68 GB of weights plus a 39 GB n-gram table) against ~360 GB for the original bf16 release.

Visual QA
Input Text · Image→ Output Text
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 ↗