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O ṣe apejuwe ibi-afẹde rẹ. Novera ngbaradi awọn orisun, ṣiṣe iṣẹ-ṣiṣe ati ṣeto awọn abajade.
Oluranlọwọ AI ti ominira nipasẹ TRON-ABS, lati ifilọlẹ akọkọ si awọn abajade: ọrọ, awọn aworan, orin ati fidio ni ibaraẹnisọrọ kan.
Wa fun Windows, Linux, macOS ati Android · 80 awọn ede ni wiwo · 42 awọn olupese awọsanma · 49 media tito tẹlẹ · Apache 2.0
Adaṣiṣẹ · Dasibodu · Awọn awoṣe AI nṣiṣẹ ni agbegbe lori ẹrọ rẹ · Awọn ọna kika & Ipele · Awọsanma · Français · Tiwon
Olubasọrọ osise: contact.novera.tronabs@gmail.com
Awọn profaili awujọ Novera osise: Facebook · Instagram · TikTok · YouTube · X · Bluesky
Pin awọn ẹda rẹ, awọn awoṣe, awọn eto, awọn ibeere, esi ati awọn imọran.
> Itumọ iranlọwọ nipasẹ awọn irinṣẹ itumọ, da lori Gẹẹsi README ti ọjọ 2026-11-03. Atunwo ede abinibi jẹ itẹwọgba. Awọn iwe aṣẹ ti o ni asopọ ṣe idaduro ede atilẹba wọn.
---
## Wiwa — 2026-11-03
**Novera 1.0.0 wa fun Windows, Linux, macOS ati Android.** [Windows x64 / Linux x64](https://github.com/TRON-ABS/Novera/releases/tag/v1.0.0) · [Windows ARM64](https://github.com/TRON-ABS/Novera/releases/tag/v1.0.0-windows-arm64). Awọn idii tabili, mejeeji CLI awọn ile ifi nkan pamosi, awọn ibuwọlu ati awọn ifihan imudojuiwọn jẹ ti gbogbo eniyan ati rii daju.
| Platform | Wiwa |
| --- | --- |
| Windows x64 | Insitola ti gbogbo eniyan NSIS, imudojuiwọn ti fowo si; abinibi fifi sori ati rirọpo wadi. |
| Linux x64 | Gbangba AppImage, imudojuiwọn ti fowo si; abinibi fifi sori ati rirọpo wadi. |
| Windows x64 / Linux x64 CLI | [Novera CLI](https://github.com/TRON-ABS/Novera/releases/tag/v1.0.0-cli-novera): `novera.exe` / `novera`, pẹlu ikanni imudojuiwọn ti a fowo si igbẹhin. |
| Windows ARM64 | [Insitola gbangba NSIS](https://github.com/TRON-ABS/Novera/releases/tag/v1.0.0-windows-arm64), CPU abinibi ẹrọ ọrọ; fifi sori ẹrọ, rirọpo ati awọn sọwedowo ikanni ti gbogbo eniyan jẹri. |
| Android ARM64 | [Ti gbogbo eniyan fowo si APK 1.0.0](https://github.com/TRON-ABS/Novera/releases/tag/v1.0.0-android-1000012), Android 7+, aiyipada ipele 512. Olutọju naa jẹrisi pe 1000012 ṣiṣẹ lori foonu wọn. Apo mimọ laisi awọn ibaraẹnisọrọ, awọn awoṣe tabi awọn bọtini API ti ara ẹni. [Ẹri ati awọn idiwọn](docs/RELEASE_ANDROID_1.0.0.md). |
| macOS Intel / Apple Silicon | [Itusilẹ 1.0.0 DMG osise](https://github.com/TRON-ABS/Novera/releases/tag/v1.0.0-macos), macOS 13+ Intel / 14+ Apple Silicon; Novera-fọwọsi awọn imudojuiwọn. Ko Apple notarized; Aládàáṣiṣẹ sọwedowo koja lọtọ lori mejeji faaji, visual sọwedowo da duro. [Fifi sori ẹrọ ati ẹri](docs/RELEASE_MACOS_1.0.0.md). |
| iOS | Kọ simulator inu; Apple fawabale / ipese wa ni ti beere ṣaaju ki o to iPhone fifi sori. [Atẹle](docs/REPRISE_MACOS_IOS.md). |
| Windows x64 to šee gbe | [Ti wole ZIP pamosi](https://github.com/TRON-ABS/Novera/releases/tag/v1.0.0-windows-portable); data duro ni Data, wole Program rirọpo ti wadi. |
| Oju opo wẹẹbu, MSI, Debian | Onibara wẹẹbu ti gbalejo ati awọn ọna kika miiran wa ninu inu; Aaye igbejade Pages wa. |
Lori Mac, ṣii DMG ki o daakọ Novera sinu Awọn ohun elo. Ti ifilọlẹ akọkọ ba dina, gba Novera wọle **Eto Eto → Asiri & Aabo → Ṣii Lonakona**. [Awọn ilana Apple](https://support.apple.com/guide/mac-help/mh40616/mac).
Awọn ibuwọlu imudojuiwọn kii ṣe Windows Authenticode tabi notarization Apple. Awọn sọwedowo ẹya-ọwọ lọwọlọwọ kọja lodi si ikanni gbogbo eniyan; iyipada laarin awọn ẹya gbangba meji jẹ idanwo itusilẹ atẹle. [Ẹri ati awọn idiwọn](docs/LAUNCH_STATUS.md).
Lori Android, foonu igbalode pẹlu iranti to ni iṣeduro fun awọn awoṣe agbegbe; lo olupese API lori awọn ẹrọ ti ko lagbara. Fun wiwa wẹẹbu, ọrọ-ọrọ ti o kere ju **Awọn ami 16K (16,384)** ni a ṣe iṣeduro, ni igbagbogbo kọja awọn ẹya.
**Windows x64 to šee gbe 1.0.0 wa.** Awọn ijiroro, awọn eto ati awọn awoṣe ti a ṣe igbasilẹ duro si inu folda to ṣee gbe labẹ `Data`. Jade ni kikun pamosi ki o si bẹrẹ `Novera.exe`. Pa Novera ṣaaju gbigbe folda tabi yiyọ ibi ipamọ USB jade. [Itọsọna gbigbe ati awọn idiwọn](docs/WINDOWS_PORTABLE.md).
## Dasibodu kan fun gbogbo ẹda
Novera dagba pẹlu rẹ. Awọn apẹẹrẹ ati eto rẹ le ṣe iranlọwọ fun awọn olumulo miiran lati wa iṣeto to dara. Pin awọn ibeere, awọn ọran ati awọn imọran lori wa [Facebook page](https://www.facebook.com/profile.php?id=61596114515071) tabi nipasẹ [imeeli](mailto:contact.novera.tronabs@gmail.com). Ti o ba ṣeeṣe, pẹlu ẹya Novera rẹ, ẹrọ ati awoṣe agbegbe/API. Yọ alaye ti ara ẹni kuro ki o ma ṣe pin awọn bọtini API tabi awọn ọrọigbaniwọle.
*Sikirinifoto ohun elo Windows gidi ti a pese nipasẹ olutọju lori 1 Kọkànlá Oṣù 2026, ẹniti o jabo pe ohun elo naa ṣiṣẹ daradara. O ṣe afihan ala-ilẹ ti ipilẹṣẹ, awọn iṣakoso faili ti o fipamọ ati dasibodu ẹda ti iṣọkan; eyi kii ṣe ẹgan.*
Panel kan, awọn ipo marun: **Aifọwọyi / Ọrọ / Aworan / Orin / Fidio**. Awọn iṣakoso tẹle ipo ti o yan: ipin, ipinnu, iye akoko, iwọn, didara, ohun elo, awọn orin, irugbin ati opoiye. Iwọn igbimọ ati awọn bọtini ṣe deede si window ati awọn aami itumọ.
- **1–10 awọn iran ti o tẹle**, aiyipada si 1, pẹlu awọn iwọn ominira fun aworan, orin ati fidio. Da pawonre awọn ti nṣiṣe lọwọ-ṣiṣe ati awọn ti o ku isinyi.
- **Laileto, ti o wa titi, +1 ati -1 awọn irugbin**, tito tẹlẹ tabi awọn ipin aṣa ati iyan **Real-ESRGAN ×2/×4** igbega pẹlu awọn iwọn ipari ti o han.
- Awoṣe ti a yan, iranti aifọwọyi, awọn asomọ, awọn itọnisọna, wiwa wẹẹbu ati awọn irinṣẹ duro ni igi kanna. Awọn irinṣẹ da lori awọn agbara awoṣe ati iwọle ti a funni.
## Lati ifilọlẹ akọkọ si awọn abajade
**Adaṣiṣẹ wa so igbaradi si ṣiṣan iṣẹ ṣiṣe pipe.** Novera mu awọn igbesẹ imọ-ẹrọ ti o wa fun iṣeto ti o yan, lakoko ti o tọju awọn iṣakoso ilọsiwaju ni wiwọle.
| Igbesẹ | Kini Novera mu |
| --- | --- |
| **1. Bẹrẹ** | Yan ede eto atilẹyin ni ifilọlẹ akọkọ ati fi ayanfẹ rẹ pamọ. Ṣe afihan awọn awoṣe ibẹrẹ ati alaye hardware to wulo. |
| **2. Murasilẹ** | Fifi sori itọsọna nfunni ni ọrọ, awọn ifibọ, aworan, orin, fidio ati igbega. O ṣe awotẹlẹ awọn paati, titobi ati aaye ọfẹ ṣaaju ifọwọsi rẹ, lẹhinna tọpinpin awọn igbasilẹ pẹlu ilọsiwaju, da duro/bẹrẹ ati ijẹrisi SHA-256. |
| **3. Tunto** | Awọn awoṣe forukọsilẹ ati awọn paati wọn, mura awọn profaili to wulo ati awọn ijabọ ti o nilo awọn igbẹkẹle. Awọn ifibọ imupadabọ bẹrẹ lori CPU pẹlu yiyan CPU/GPU ti o fipamọ. Awọn profaili orin titun aiyipada si ipo irinse. |
| **4. Loye ibeere naa** | Awọn ipa-ọna aifọwọyi mọ awọn ibeere ẹda si ọrọ, aworan, orin tabi fidio. O tun le ni ṣoki yan ipo iṣelọpọ ati awoṣe agbegbe tabi awọsanma. |
| **5. Ṣiṣe** | Iranti aifọwọyi nduro fun iṣẹ ṣiṣe, tu awọn awoṣe ti ko nilo ati gbejade awọn orisun ti o nilo. jara iṣẹ 1–10 nṣiṣẹ ni aṣẹ ati tu awọn orisun jade ṣaaju iṣẹ atẹle. Awọn olupese awọsanma lo akọọlẹ ti a yan ati iṣeto. |
| **6. Gba pada ki o tun lo** | Ṣafipamọ media ni awọn folda eto Novera, ṣafihan awọn abajade ati awọn akoko to wa, lẹhinna nfunni ni awọn iyatọ, ile-ikawe, didakọ, okeere tabi pinpin eto. Fifiranṣẹ si ohun elo miiran ku iṣẹ rẹ. |
Automation ni wiwa awọn ẹrọ iṣọpọ ati ṣiṣan iṣẹ; ko ṣe gbogbo awoṣe Ipele ti o ṣiṣẹ. Hardware, awọn paati ti a fi sori ẹrọ ati iraye si olupese pinnu ohun ti o le ṣiṣẹ. Awọn folda, awọn iyipada faili ati awọn pipaṣẹ ikarahun tẹle awọn ifunni iraye si ibaraẹnisọrọ naa.
[Itọsọna olumulo](docs/USER_GUIDE.md) · [Awọn ẹrọ ati afọwọsi](docs/SUIVI_MOTEURS.md) · [Idagbasoke](docs/DEVELOPMENT.md)
Ninu awọn orisun imudojuiwọn, **Awọn atunto ṣe deede awọn iṣeduro rẹ si alagbeka ati ohun elo ihamọ**: LFM3-1.7B Q4, tabi LFM3-Omni-2B Q4 pẹlu pirojekito rẹ nigbati iranti royin ati awọn ibeere engine ti pade. Iran agbegbe ti ko si ti wa ni pamọ tabi dina; aworan awọsanma ti a tunto, orin ati fidio wa. Itọnisọna ni wiwo tun lo awọn iwe kika ede 80. Awọn iṣiro wọnyi tun nilo idanwo ẹrọ ati atunkọ lati de awọn ohun elo ti a fi sii.
## Awọn agbara ni orisun
Awọn ayẹwo iwadii itọju aṣayan ni bayi ṣe iyatọ awọn ile-itumọ ati awọn ikuna ti ohun elo ti a mu bi daradara bi awọn imukuro JavaScript, pẹlu ifọkansi lọtọ ati awọn aaye imọ-ẹrọ filtered. Itaniji imeeli iṣelọpọ wakati kan jẹ tunto fun olutọju naa. Awọn maapu orisun aladani ati awọn alaye itaniji tẹle awọn [runbook itọju](docs/MAINTENANCE.md); iwe-ẹri imeeli idanwo jẹ timo, lakoko ti o ti fi idiwe aami-iṣipopada ati idanwo ni awọn sọwedowo itusilẹ alakomeji atẹle.
| Agbegbe | Awọn ẹya ara ẹrọ |
| --- | --- |
| **Ọrọ ati oye aworan** | Ifọrọwanilẹnuwo, awọn asomọ iwe, awọn idahun ṣiṣan ati awọn awoṣe agbegbe tabi awọsanma. Iran da lori awoṣe; oye ati ti o npese awọn aworan ni o wa lọtọ agbara. |
| **Aworan** | Iran ibaraẹnisọrọ inu, awọn irugbin, awọn ipin, ipinnu, awọn paati GGUF/Safetensors, tunto awọn folda Diffusers ati abinibi NVFP4 CUDA profaili ti o ni atilẹyin. |
| **Orin** | Iran agbegbe tabi awọsanma, iye akoko, didara, ohun elo tabi awọn ohun orin nibiti atilẹyin, awọn orin eleto ati ẹrọ orin ohun. Awọn aṣayan olupese yatọ. |
| **Fidio** | Iran agbegbe tabi awọsanma, iye akoko, kika fireemu / cadence fun awọn profaili agbegbe, awọn ipin, ipinnu ati ẹrọ orin fidio kan. |
| **Wa ati awọn irinṣẹ** | Wiwa wẹẹbu, ifibọ-orisun iwe-ipamọ, MCP, awọn aaye iṣẹ ati awọn irinṣẹ agbegbe ni ibamu si atilẹyin awoṣe ati iraye si. |
| **Awọn abajade ati pinpin** | Media ikawe, awọn iyatọ, idahun / awọn okeere ibaraẹnisọrọ, awọn iwe aṣẹ ati media atilẹba, titẹ sita/PDF ati pinpin eto ti o gbẹkẹle pẹpẹ. |
| **Isakoso orisun** | Iranti aifọwọyi ṣiṣẹ nipasẹ aiyipada, awọn eto CPU/GPU fun awọn paati atilẹyin ati awọn profaili afọwọṣe nigbati awọn orisun ba gba laaye. |
## Awọn awoṣe AI nṣiṣẹ ni agbegbe lori ẹrọ rẹ
Awọn awoṣe wọnyi ṣe agbekalẹ iṣeto itọsọna lọwọlọwọ. O le gbe awọn awoṣe ibaramu miiran wọle tabi yi awọn profaili pada.
| Ipa | Awoṣe / tunto irinše |
| --- | --- |
| **Ọrọ - awoṣe akọkọ-ṣiṣe** | **Nemotron-3.5-Bolt-E4B**, faili `Nemotron-3.5-Bolt-E4B-Q4_K_M.gguf`. |
| **Gbigba iwe-ipamọ** | **Qwen3-Embedding-0.6B Q8_0**, **CPU nipa aiyipada**, pẹlu yiyan CPU/GPU ti o fipamọ. |
| **Aworan** | **FLUX.2 Klein 4B Q4_K_M**, **Qwen3-4B Q4_K_M** kooduopo ati osise FLUX.2 VAE. |
| **Aworan — aṣayan hardware** | **FLUX.2 Klein 4B NVFP4**, nipasẹ ọna abinibi CUDA nigbati GPU ati ayika wa ni ibamu. |
| **Orin** | **ACE-Step 1.5 Turbo 2B Q4_K_M**, `acestep-5Hz-lm-1.7B-Q8_0.gguf` Alakoso, iyasọtọ orin Qwen oluyipada ati VAE. |
| **Fidio** | **Wan2.1 T2V 1.3B Q4_K_M**, **UMT5-XXL Q4_K_M** kooduopo ati Wan 2.1 VAE. |
| **Igbesoke** | Yiyan **Real-ESRGAN ×2 ati ×4**, pẹlu awọn sọwedowo igbẹkẹle. |
Ayipada orin Qwen ati awoṣe imupadabọ Qwen jẹ **oriṣiriṣi awọn faili**, ti o ti fipamọ lọtọ. Awọn iwe-aṣẹ awoṣe jẹ ti awọn olutẹwe wọn.
[Afihan ọrọ](web-app/src/constants/text-manifest.json) · [Embeddings](web-app/src/constants/embedding-manifest.json) · [Orin](web-app/src/constants/music-manifest.json) · [Aworan/awọn paati fidio](src-tauri/src/core/creation_bundle.rs)
## Awọn olupese awọsanma
**42 awọn profaili olupese** ti wa ni idapo. **ElevenLabs** ni bayi farahan ninu iṣafihan lẹgbẹẹ awọn ipa ọna orin lati Stability AI, fal ati Replicate.
| | | |
| --- | --- | --- |
| 
[OpenAI](https://platform.openai.com/docs/models) | 
[Microsoft Azure](https://oai.azure.com/deployments) | 
[Anthropic](https://platform.claude.com/docs/en/models/overview) |
| 
[OpenRouter](https://openrouter.ai/models) | 
[Mistral](https://docs.mistral.ai/models) | 
[Groq](https://console.groq.com/docs/models) |
| 
[xAI](https://docs.x.ai/developers/models) | 
[Google Gemini](https://ai.google.dev/gemini-api/docs/models) | 
[MiniMax](https://platform.minimax.io/docs/api-reference/text-openai-api) |
| 
[Hugging Face](https://huggingface.co/models?pipeline_tag=text-generation&inference_provider=all) | 
[NVIDIA NIM](https://build.nvidia.com/models) | 
[DeepSeek](https://api-docs.deepseek.com/) |
| 
[Kimi · Moonshot AI](https://platform.kimi.ai/docs/models) | 
[Alibaba Cloud · Qwen](https://www.alibabacloud.com/help/en/model-studio/models) | 
[Cerebras](https://inference-docs.cerebras.ai/models/overview) |
| 
[Together AI](https://docs.together.ai/docs/serverless/models) | 
[Fireworks AI](https://docs.fireworks.ai/getting-started/models) | 
[Perplexity](https://docs.perplexity.ai/docs/agent-api/models) |
| 
[Meta AI](https://dev.meta.ai/docs/models) | 
[Cohere](https://docs.cohere.com/docs/models) | 
[Z.ai](https://docs.z.ai/guides/llm/glm-5.3) |
| 
[AI21 Labs](https://docs.ai21.com/docs/jamba-foundation-models) | 
[BytePlus · ByteDance](https://docs.byteplus.com/en/docs/modelark/model-parameter-support) | 
[Baidu Qianfan](https://cloud.baidu.com/doc/qianfan/s/rmh4stp0j) |
| 
[Tencent TokenHub](https://cloud.tencent.com/document/product/1823/130078) | 
[Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-chat-completions.html) | 
[IBM watsonx](https://www.ibm.com/docs/en/watsonx/saas?topic=preview-inferencing-gateway-models) |
| 
[ElevenLabs](https://elevenlabs.io/docs/api-reference/music/compose) | 
[Black Forest Labs](https://docs.bfl.ai/quick_start/generating_images) | 
[Stability AI](https://docs.stability.ai/api-reference) |
| 
[Recraft](https://www.recraft.ai/docs/api-reference/agents.md) | 
[Ideogram](https://developer.ideogram.ai/ideogram-api/api-overview) | 
[Adobe Firefly](https://developer.adobe.com/firefly-services/docs/firefly-api/) |
| 
[Runway](https://docs.dev.runwayml.com/api/) | 
[Luma](https://docs.agents.lumalabs.ai/guides/model/) | 
[LTX (Lightricks)](https://docs.ltx.io/models) |
| 
[fal](https://fal.ai/docs/documentation/model-apis/inference/queue) | 
[Replicate](https://replicate.com/docs/reference/http) | 
[Leonardo.Ai](https://docs.leonardo.ai/reference/creategeneration) |
| 
[Krea](https://www.krea.ai/docs/developers/krea-3/overview) | 
[Vidu](https://platform.vidu.com/docs/model-map) | 
[PixVerse](https://docs.platform.pixverse.ai/changelog-2394996m0) |
### Aworan, orin ati fidio
**Awọn olupese 20 ṣafihan awọn ipa ọna iran**, pẹlu **49 tito tẹlẹ: aworan 25, fidio 20 ati orin 4**. Awọn ipa ọna orin jẹ **ElevenMusic v2.5**, **Stable Audio 3**, **ACE-Step nipasẹ fal** ati **Stable Audio 2.5 nipasẹ Replicate**.
| Olupese | Awọn abajade ni Novera | Awọn awoṣe katalogi |
| --- | --- | --- |
| [ElevenLabs](https://elevenlabs.io/docs/api-reference/music/compose) | Orin | `ElevenMusic v2.5` |
| [Stability AI](https://docs.stability.ai/api-reference/stable-audio/text-to-audio) | Aworan / Orin | `Stable Audio 3` · `Stable Image Ultra` · `Stable Image Core` |
| [fal](https://fal.ai/models/fal-ai/ace-step/api) | Aworan / Orin / Fidio | `ACE-Step · cloud` · `Pika 2.2 · fal` · `Qwen Image 2512 · fal` · `FLUX.2 Max · fal` · `Kling 3 Pro · fal` · `Kling 3 Standard · fal` |
| [Replicate](https://replicate.com/stability-ai/stable-audio-2.5/api/schema) | Aworan / Orin | `Stable Audio 2.5 · Replicate` · `FLUX.2 Max · Replicate` |
| [BytePlus · ByteDance](https://docs.byteplus.com/en/docs/ModelArk/image-generation-api) | Aworan / Fidio | `Dola Seedream 5 Pro` · `Dreamina Seedance 2.5` |
| [Adobe Firefly](https://developer.adobe.com/firefly-services/docs/firefly-api/api/) | Aworan / Fidio | `Adobe Firefly Image 5` · `Adobe Firefly Video` |
| [Google Gemini](https://ai.google.dev/gemini-api/docs/omni) | Aworan / Fidio | `Gemini Omni 1.1 Flash` · `Gemini Nano Banana 2.1` |
| [Krea](https://www.krea.ai/docs/developers/krea-3/overview.md) | Aworan | `Krea 3` |
| [Leonardo.Ai](https://docs.leonardo.ai/docs/lucid-origin) | Aworan | `Lucid Origin` · `Krea 2 Turbo · Leonardo` · `Ideogram 3 · Leonardo` |
| [Vidu](https://platform.vidu.com/docs/api-reference/video-models/vidu-q4-preview/image-to-video) | Fidio | `Vidu Q4 Preview` · `Vidu Q3 Pro` · `Vidu Q3 Turbo` |
| [OpenAI](https://developers.openai.com/api/docs/guides/image-generation) | Aworan | `GPT Image 2.5 Sunburst` · `GPT Image 2.5 Flare` |
| [xAI](https://docs.x.ai/developers/model-capabilities/imagine) | Aworan / Fidio | `Grok Imagine Image 2.0` · `Grok Imagine Video 1.5` · `Grok Imagine Video 1.5 Lite` |
| [Black Forest Labs](https://docs.bfl.ai/quick_start/generating_images) | Aworan | `FLUX.2 [max]` · `FLUX.2 [pro]` · `FLUX.2 [klein] 9B` |
| [Recraft](https://www.recraft.ai/docs/api-reference/agents.md) | Aworan | `Recraft V4.1` · `Recraft V4.1 Flash` · `Recraft V4.1 Pro` |
| [Ideogram](https://developer.ideogram.ai/ideogram-api/api-overview) | Aworan | `Ideogram 4.5` |
| [Runway](https://docs.dev.runwayml.com/api/) | Fidio | `Runway Gen-4.5` |
| [Luma](https://docs.agents.lumalabs.ai/guides/model/) | Aworan / Fidio | `Luma Uni-1 Max` · `Luma Uni-1` · `Luma Ray 3.2` |
| [LTX (Lightricks)](https://docs.ltx.io/models) | Fidio | `LTX-2.5 Pro` · `LTX-2.5 Fast` |
| [MiniMax](https://platform.minimax.io/docs/api-reference/video-generation-v2-create) | Aworan / Fidio | `MiniMax H3 Max` · `MiniMax H3` · `MiniMax H3 Highspeed` · `MiniMax Image-01` |
| [PixVerse](https://docs.platform.pixverse.ai/changelog-2394996m0) | Fidio | `PixVerse V6 Max` · `PixVerse V6` |
Ṣafihan ọrọ ati awọn atokọ kukuru awoṣe iran nipasẹ olupese
| Olupese | Awọn ID awoṣe ti a nṣe ni orisun |
| --- | --- |
| [OpenAI](https://platform.openai.com/docs/models) | `gpt-6.1-sol` · `gpt-6-astra` · `gpt-6-luna` · `gpt-6-sol` |
| [Microsoft Azure](https://oai.azure.com/deployments) | Ifiranṣẹ pato-ipamọ tabi ẹnu-ọna |
| [Anthropic](https://platform.claude.com/docs/en/models/overview) | `claude-sonnet-5-5` · `claude-opus-5-5` · `claude-fable-5-1` · `claude-haiku-5-5` |
| [OpenRouter](https://openrouter.ai/models) | `moonshotai/kimi-k3.1-pro` · `minimax/minimax-m3.1-flash` · `deepseek/deepseek-v4.1-flash-1017` · `nvidia/nemotron-3.5-super-vl:free` |
| [Mistral](https://docs.mistral.ai/models) | `mistral-large-4` · `mistral-medium-3-5` · `mistral-small-2603` · `ministral-3b-2512` |
| [Groq](https://console.groq.com/docs/models) | `openai/gpt-oss-120b` · `openai/gpt-oss-20b` · `llama-3.3-70b-versatile` · `llama-3.1-8b-instant` |
| [xAI](https://docs.x.ai/developers/models) | `grok-4.7` |
| [Google Gemini](https://ai.google.dev/gemini-api/docs/models) | `gemini-4-argon` · `gemini-3.8-flash` · `gemini-3.6-flash` · `gemini-3.5-flash-lite` |
| [MiniMax](https://platform.minimax.io/docs/api-reference/text-openai-api) | `MiniMax-M3.1-Flash` · `MiniMax-M3` |
| [Hugging Face](https://huggingface.co/models?pipeline_tag=text-generation&inference_provider=all) | `deepseek-ai/DeepSeek-V4.1-Flash-1017` · `Qwen/Qwen3.8-27B` · `moonshotai/Kimi-K3` · `zai-org/GLM-5.3` |
| [NVIDIA NIM](https://build.nvidia.com/models) | `minimaxai/minimax-m3.1-flash` · `deepseek-ai/deepseek-v4.1-flash` · `nvidia/nemotron-3.5-super-vl-120b-a12b` · `nvidia/nemotron-3.5-lightning-30b-a3b` · `z-ai/glm-5.3` |
| [DeepSeek](https://api-docs.deepseek.com/) | `deepseek-flash` · `deepseek-v4-pro` |
| [Kimi · Moonshot AI](https://platform.kimi.ai/docs/models) | `kimi-k3.1-pro` · `kimi-k3.1-pro-highspeed` · `kimi-k3` |
| [Alibaba Cloud · Qwen](https://www.alibabacloud.com/help/en/model-studio/models) | `qwen3.8-max` · `qwen3.7-plus` · `qwen3.8-flash` |
| [Cerebras](https://inference-docs.cerebras.ai/models/overview) | `qwen-3.8-27b` · `gpt-oss-120b` |
| [Together AI](https://docs.together.ai/docs/serverless/models) | `deepseek-ai/DeepSeek-V4.1-Flash-1017` · `moonshotai/Kimi-K3` · `Qwen/Qwen3.8-Flash` · `Qwen/Qwen3.8-2.4T-A95B` |
| [Fireworks AI](https://docs.fireworks.ai/getting-started/models) | `accounts/fireworks/models/deepseek-v4p1-flash-1017` · `accounts/fireworks/models/kimi-k3` · `accounts/fireworks/models/minimax-m3` |
| [Perplexity](https://docs.perplexity.ai/docs/agent-api/models) | `perplexity/sonar` · `openai/gpt-6.1-sol` · `google/gemini-4-argon` · `perplexity/kimi-k3` |
| [Meta AI](https://dev.meta.ai/docs/models) | `muse-wonder-1.0` · `muse-spark-1.3` |
| [Cohere](https://docs.cohere.com/docs/models) | `command-a-plus-05-2026` |
| [Z.ai](https://docs.z.ai/guides/llm/glm-5.3) | `glm-5.3` · `glm-5.3-flash` · `glm-5.3-flashx` |
| [AI21 Labs](https://docs.ai21.com/docs/jamba-foundation-models) | `jamba-large` · `jamba-mini-2` |
| [BytePlus · ByteDance](https://docs.byteplus.com/en/docs/modelark/model-parameter-support) | `dola-seed-2-1-turbo-260628` |
| [Baidu Qianfan](https://cloud.baidu.com/doc/qianfan/s/rmh4stp0j) | `ernie-5.1` |
| [Tencent TokenHub](https://cloud.tencent.com/document/product/1823/130078) | `hy4-preview` |
| [Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-chat-completions.html) | `openai.gpt-6.1-sol` |
| [IBM watsonx](https://www.ibm.com/docs/en/watsonx/saas?topic=preview-inferencing-gateway-models) | Ifiranṣẹ pato-ipamọ tabi ẹnu-ọna |
Oja ti ṣayẹwo lodi si orisun lori **29 Oṣu Kẹwa 2026**. Awọn orukọ wọnyi ṣapejuwe awọn tito tẹlẹ Novera, kii ṣe iraye si ẹri fun gbogbo akọọlẹ. Awọn katalogi jijin, awọn agbegbe, awọn iwe-aṣẹ, awọn ipin ati ìdíyelé wa ni pato olupese. Awọn profaili ibaramu le sọ awọn katalogi wọn sọtun; Azure ati diẹ ninu awọn ẹnu-ọna lo awọn imuṣiṣẹ akọọlẹ. Awọn adehun awọsanma ni awọn idanwo afọwọṣe; ko si iran isanwo ti a ṣe fun imudojuiwọn iṣafihan yii.
[Media katalogi](web-app/src/constants/mediaProviders.ts) · [Awọn awoṣe Ọrọ / iran](web-app/src/constants/cloudModels.ts) · [Iṣeto awọsanma](docs/USER_GUIDE.md#cloud) · [Aami afihan](docs/DEVELOPMENT.md#logos)
## Ipele ati awọn awoṣe ibaramu
**GGUF, boṣewa ati titobi Safetensors, ONNX, ati MLX**: ṣawari awọn awoṣe nipasẹ iṣẹ-ṣiṣe ki o yan awọn iyatọ ti o ni ibamu pẹlu ẹrọ ati ohun elo rẹ.
| Idile | Atilẹyin ni orisun | Awọn ibeere |
| --- | --- | --- |
| **GGUF** | Iran ọrọ nipasẹ llama.cpp; aworan ati awọn paati fidio fun awọn profaili to ni atilẹyin. | Itumọ faaji ti a mọ nipasẹ ẹrọ ti a ṣajọpọ. |
| **Pipin GGUF** | Iyatọ kan fun jara pipe, iwọn akopọ, igbasilẹ gbogbo-shard ati iwọn/SHA-256/awọn sọwedowo akọsori. | Awọn orukọ faili ti o ni idiwọn; gbigba lati ayelujara 500 GB ko tumọ si awoṣe baamu PC. yii |
| **Standard Safetensors** | Pari awọn folda nipasẹ Transformers, ọrọ idi lori CPU tabi NVIDIA CUDA. | Iṣeto ni, tokenizer ati gbogbo shard ti a beere. |
| **ONNX Runtime** | Agbewọle agbegbe ti nomba/awọn aworan bool ati awọn igbejade ọrọ okeere GenAI ti pese sile. | Ifọwọsi pipe folda; iṣẹ-ṣiṣe-pato preprocessing/postprocessing beere; [iṣeto ati awọn opin](onnx-server/README.md). |
| **LoRA / PEFT oluyipada** | Ṣe agbewọle ipilẹ pipe pẹlu ohun ti nmu badọgba agbegbe lọtọ ni olupese Safetensors. | Ipilẹ Transformers ti ko ni iwọn, idanimọ ti o baamu, awọn sọwedowo tensor ati iṣiro iranti akopọ; [iṣeto ati awọn opin](transformers-server/README.md#local-lora--peft-adapters). |
| **FP8 LLM / ModelOpt** | Ipaniyan CUDA abinibi fun ibaramu ipon Llama/Qwen2/Qwen3 fun-tensor FP8 okeere. | Awọn iṣayẹwo faaji / tensor ati iwadii ekuro gidi; [iṣeto ati awọn opin](transformers-server/README.md#modelopt-fp8-and-nvfp4-llms). |
| **NVFP4 LLM / ModelOpt** | Idina ti a kojọpọ-16 FP4 awọn asọtẹlẹ nipasẹ abinibi CUDA GEMMs; yato si aworan NVFP4. | Ibaramu Blackwell GPU, awọn iwọn atilẹyin / okeere ati iwadii ekuro gangan; awọn imuduro ti ko ni ikẹkọ ni idanwo lori RTX 5070. |
| **AWQ** | 4-bit GEMM awọn aaye ayẹwo awoṣe laisi idapọ iṣẹ. | NVIDIA CUDA ati iyan GPTQModel/Transformers agberu. |
| **GPTQ** | 2/3/4/8-bit atunto, gptq/gptq_v2 ọna kika. | NVIDIA CUDA, GPTQModel ati Optimum; ipaniyan gidi ni idanwo ni awọn iwọn 4. |
| **bitsandbytes** | 4-bit NF4/FP4 tabi 8-bit INT8. | NVIDIA CUDA ati awọn igbẹkẹle iyan; gidi NF4 ati INT8 igbeyewo. |
| **EXL3** | Pari titobi Safetensors awoṣe awọn folda ti kojọpọ nipasẹ ExLlamaV3; iran gangan pẹlu CUDA ni idanwo. | NVIDIA GPU, agbegbe Python 3.12 lọtọ ati faaji ibaramu; ko si CPU fallback. |
| **EXL2** | Igbẹhin ExLlamaV2 agberu; sisanwọle, ifagile ati unload ni idanwo lori GPU. | CUDA akiyesi gbọdọ jẹ ti yan ni gbangba fun akopọ sọfitiwia ti idanwo; aaye ayẹwo awoṣe pipe ati VRAM ti o wa ni a nilo. |
| **MLX** | Awọn awoṣe ibaramu lori Apple Silicon. | MLX engine ati pẹpẹ ti o ni atilẹyin. |
Ipele naa pin bayi **LFM3-1.7B** gẹgẹbi iṣeduro LiquidAI rẹ fun awọn atunto ibaramu, pẹlu Q4_K_M, Q6_K ati awọn iyatọ Q8_0. Awoṣe akọkọ-ṣiṣe jẹ eyiti a ṣe akojọ si ni iṣeto itọsọna loke.
Ajọ igbasilẹ awọn iwuwo lati **labẹ 1 GB si 500 GB ati loke**, lẹhinna too nipasẹ ibamu hardware, iwọn, recency tabi awọn igbasilẹ. Awọn abajade fifuye ni ilọsiwaju; Ajọ lo si awọn awoṣe ti a mu ati iyatọ aiyipada wọn. Imọran iranti nlo RAM/VRAM to wa, ọrọ-ọrọ ati awọn paati ẹlẹgbẹ, laisi kika ilọpo meji pinpin iranti GPU.
AWQ 4-bit, GPTQ 4-bit, NF4 ati INT8 kọọkan ti ipilẹṣẹ ọrọ lori ohun RTX 5070 Laptop lilo aami untrained si dede da offline. Eyi ṣe idaniloju ikojọpọ ati ipaniyan, kii ṣe didara tabi iṣẹ ti gbogbo awoṣe. **Awọn afikun wọnyi wa ni orisun: atunṣe ati awọn igbẹkẹle ibaramu ni a nilo; imudojuiwọn README yii ko ṣe igbesoke alakomeji ti a fi sii.**
**Tiwọn lori RTX 5070 Laptop:** Qwen2.5-0.5B-Instruct, ipo 2,048, awọn ami 272 tọ, awọn ami ti ipilẹṣẹ 128, awọn ṣiṣe igbona marun: ipinnu agbedemeji **GGUF Q4_K_M 402.7 tokens/s · EXL3 4 bpw 312.5 · EXL2 4 bpw 146.9**. Ko si anfani iyara lori GGUF ti a ṣe afihan nibi. Quantization/atunṣe yatọ, ati EXL3 kuna ọkan ẹfin ẹfin iṣiro kan; awọn abajade wọnyi kii ṣe iyara gbogbogbo tabi ipo didara. [Awọn wiwọn ni kikun ati awọn opin](deliverables/exllama-2026-10-30/validation.md).
**TabbyAPI** jẹ iyan, ti iṣakoso lọtọ OpenAI asopọ olupin ibaramu, alaabo nipasẹ aiyipada. Awari awoṣe EXL3 ti o ni idaniloju ati ṣiṣanwọle ni idanwo. Ọna agbegbe ti iṣakoso ExLlama wa ni pato. [Eto ExLlama ati asopọ TabbyAPI](transformers-server/README.md#exl3-first-exl2-second--nvidia-execution).
Iru ohun elo ti o ni ibamu pẹlu aifọwọyi ṣe ojurere awọn idasilẹ tuntun laarin ibaramu kanna ati ipele iranti ti o wa. Awọn awoṣe ti a fi sori ẹrọ ko ni rọpo laifọwọyi.
[Iṣeto Safetensors ti o ni iwọn](transformers-server/README.md#quantized-safetensors--source-integration-29-october-2026) · [Awọn ọna kika, awọn ayo ati afọwọsi](docs/SUIVI_MOTEURS.md)
Awọn orisun imudojuiwọn ṣafikun **awọn paati iṣakoso iyan ni Awọn atunto fun Windows x64**: Awọn agbegbe Python ikọkọ, awọn profaili CPU/CUDA pinned, awọn iṣiro ati ijẹrisi ṣaaju awọn igbasilẹ, ijẹrisi, atunṣe ati yiyọ kuro. Awọn ọna onitumọ aṣa duro labẹ awọn aṣayan ilọsiwaju. Abinibi GGUF enjini pa wọn tẹlẹ irinše; alagbeka ati awọsanma ko ṣe igbasilẹ tabili Python/PyTorch. Meta ikọkọ CPU / okeere profaili won idaraya pẹlu gidi sintetiki amuse; Olutọju ṣe ijabọ lilo tabili aṣeyọri lori 1 Oṣu kọkanla 2026; Awọn profaili GPU ati mimọ-PC fifi sori si tun nilo lọtọ, alaye afọwọsi. [Awọn profaili ati awọn opin idanwo](docs/REPRISE_COMPOSANTS_GERES_80_LANGUES.md). Ifisinu akopọ ninu EXE ti wa ni idaduro.
## 80 ni wiwo awọn ede ati awọn iyatọ
**Gbogbo awọn katalogi 80 bo awọn bọtini Gẹẹsi lọwọlọwọ 2,429** kọja awọn aaye orukọ 15, pẹlu awọn akojọ aṣayan, awọn atunto, eto, iranlọwọ ati awọn iṣakoso media. Awọn fọọmu pupọ ati itọsọna wiwo tẹle ede ti o yan. Idahun ati awọn ede ohun gbarale lọtọ lori awoṣe.
Agbegbe imọ-ẹrọ yii ko jẹri didara ede: **atunwo abinibi ati aṣamubadọgba agbegbe wa pataki**. Wo awọn akole abinibi ati awọn opin ti a mọ ninu [ede itọnisọna](docs/LANGUAGES.md) ati [se ayewo iroyin](deliverables/interface-audit-2026-10-29/RAPPORT.md).
## Iranlọwọ eniyan, ni gbogbo eka
Ni ikọja ile-iwe ati ẹkọ, ipinnu wa ni lati ṣe iranlọwọ fun awọn eniyan lati kọ ẹkọ, yanju awọn iṣoro, ṣẹda ati idagbasoke awọn iṣẹ ti o wulo ni agbaye. Novera ni ero lati jẹ ki awọn ilọsiwaju AI lọwọlọwọ rọrun lati ni oye ati lo, kọja awọn ede, awọn ipele ti iriri ati ohun elo ti o wa.
| Awọn apakan ti a fẹ lati ṣe iranlọwọ idagbasoke | Awọn apẹẹrẹ ti awọn ifunni to wulo |
| --- | --- |
| Awọn ile-iwe, ẹkọ ati ẹkọ igbesi aye | Ṣalaye awọn imọran, mu awọn ohun elo ẹkọ ṣiṣẹ ati awọn olukọ atilẹyin, awọn ọmọ ile-iwe ati awọn idile. |
| Iwadi, imọ-jinlẹ ati aaye | Ṣawari awọn iwe-iwe, ṣe alaye awọn ọna, ṣe itupalẹ data ati pin imọ. |
| Ilera, itọju ati atilẹyin awujọ | Jẹ ki alaye rọrun lati ni oye ati atilẹyin iwadii ati ṣiṣan iṣẹ alamọdaju. |
| Ogbin, ounje ati agbegbe igberiko | Pin imọ ti o wulo, eto atilẹyin ati idagbasoke awọn irinṣẹ to wulo ni agbegbe. |
| Ayika, afefe, omi ati ipinsiyeleyele | Ṣe alaye ẹri, ṣe atilẹyin akiyesi ati iranlọwọ awọn agbegbe gbero awọn iṣẹ akanṣe. |
| Agbara, ile-iṣẹ, ikole ati iṣẹ ọnà | Iwe atilẹyin, apẹrẹ, itọju, ẹkọ imọ-ẹrọ ati ilọsiwaju ilana. |
| Awọn iṣowo, iṣowo, iṣuna ati iṣẹ | Iranlọwọ ṣeto iṣẹ, loye alaye, dagbasoke awọn iṣẹ akanṣe ati kọ ẹkọ awọn ọgbọn alamọdaju. |
| Awọn iṣẹ ti gbogbo eniyan, ofin ati ikopa ti ara ilu | Ṣe awọn iwe aṣẹ ati ilana rọrun lati ni oye ati alaye rọrun lati wọle si. |
| Iṣiro, cybersecurity, roboti ati awọn ibaraẹnisọrọ | Iranlọwọ idagbasoke sọfitiwia, loye awọn eto ati kọ awọn irinṣẹ to wulo. |
| Iṣẹ ọna, asa, media, awọn ede ati iní | Atilẹyin kikọ, itumọ, awọn aworan, fidio, awọn iṣẹ akanṣe ati pinpin aṣa. |
| Gbigbe, eekaderi, irin-ajo, ere idaraya ati igbesi aye agbegbe | Iranlọwọ pẹlu eto, ibaraẹnisọrọ, ẹkọ ati awọn ipilẹṣẹ agbegbe. |
| Wiwọle, iṣẹ omoniyan ati igbesi aye ojoojumọ | Din ede ati awọn idena imọ ati atilẹyin awọn eniyan pẹlu iranlọwọ to wulo. |
Iwọnyi jẹ awọn itọnisọna fun idasi ati idagbasoke, kii ṣe ẹtọ pe gbogbo ohun elo kan pato ti eka ti wa tẹlẹ jiṣẹ tabi fọwọsi. A fẹ itọsọna ti o rọrun fun lilo lojoojumọ, ko awọn aṣayan ilọsiwaju nigbati o nilo, ohun elo itanna ati awọn ibeere awọsanma, ati ifowosowopo pẹlu awọn eniyan ti o mọ aaye kọọkan ati agbegbe agbegbe.
## Ipo ise agbese
**Novera 1.0.0 wa fun Windows, Linux, macOS ati Android.** Sikirinifoto n ṣe afihan ohun elo Windows ti a ṣajọpọ ni agbegbe nipasẹ olutọju. Awọn iyipada orisun, awọn idanwo ifọkansi ati afọwọsi ohun elo jẹ akọsilẹ lọtọ; eyi ko fọwọsi gbogbo awoṣe, Syeed tabi iroyin awọsanma.
Afọwọṣe GitHub Actions kọ ni ṣiṣẹ fun gbogbo awọn iyatọ pinpin mọkanla. Tẹle awọn [kọ awọn abajade ati awọn gbigba lati ayelujara oludije ti a fọwọsi](docs/CI_DISTRIBUTIONS.md); wiwa ti wa ni gba silẹ lọtọ fun kọọkan Syeed. Awọn oludije yatọ si awọn idasilẹ iṣelọpọ ti o fowo si. Pinpin awọn ibeere ti wa ni apejuwe ninu awọn [Ilana itusilẹ osise](OFFICIAL_RELEASES.md) ati [tu iwe](https://github.com/TRON-ABS/Novera/releases). Awọn oludije alaabo imudojuiwọn ti o wa tẹlẹ wa ti inu. Awọn idasilẹ ti gbogbo eniyan nilo atunto ati ẹrọ imudojuiwọn ti o jẹrisi; [Awọn sọwedowo ibuwọlu tabili tabili ati awọn ibeere ifilọlẹ ti o ku jẹ akọsilẹ](docs/LAUNCH_STATUS.md).
## Iwe-ipamọ ati awọn ifunni
- [Itọsọna olumulo alaye](docs/USER_GUIDE.md), [ọja ati alaye olumulo awọn ofin goolu (Faranse)](docs/REGLES_D_OR.md), [si dede ati enjini](docs/SUIVI_MOTEURS.md).
- [Idagbasoke](docs/DEVELOPMENT.md), [kọ ati itọsọna itusilẹ](docs/BUILD_AND_RELEASE.md), [awọn ẹya iwaju ati igbaradi imudojuiwọn](docs/FUTURES_VERSIONS.md).
- [Dasibodu ise agbese](TABLEAU_DE_BORD_NOVERA.md), [ọna maapu](ROADMAP.md), [changelog](docs/CHANGELOG.md).
- [Ilowosi](CONTRIBUTING.md): koodu, awọn idanwo, atunyẹwo abinibi kọja awọn ede 80 ati awọn esi ṣiṣan iṣẹ gidi.
## Idanimọ ati iwe-aṣẹ
Novera ni itọju nipasẹ **TRON-ABS** ninu [ibi ipamọ yii](https://github.com/TRON-ABS/Novera). Wo awọn [Ilana idanimọ](BRANDING.md) ati [Ilana itusilẹ osise](OFFICIAL_RELEASES.md).
Novera duro lori [Jan](https://github.com/janhq/jan), ti a ṣẹda nipasẹ Menlo Research ati awọn oluranlọwọ rẹ. Atilẹba ati ẹni-kẹta abuda ati awọn [Apache 2.0 iwe-aṣẹ](LICENSE) ti wa ni idaduro. Awọn igbasilẹ Jan kii ṣe awọn idasilẹ Novera.
## Atilẹyin Novera
Gẹgẹbi oluṣewadii ominira, Mo mọ bi aini inawo ṣe le jẹ ki o nira lati lepa iwadii.
Ti o ba fẹ lati jẹ apakan ti ìrìn Novera, o le ṣe atilẹyin fun iwadii mi ati idagbasoke iṣẹ akanṣe pẹlu ifunni bitcoin atinuwa.
O ṣeun si gbogbo eniyan fun atilẹyin rẹ, awọn ifunni, esi ati iwuri. Gbogbo idari ni iye ninu ìrìn yii!
**Bitcoin (BTC) — nẹtiwọki Bitcoin**
Adirẹsi gbigba: `17TXpB1aBj5DxjwEfM3K44zyqhixRzY78i`
Lati ṣe alabapin, ṣayẹwo koodu QR yii pẹlu apamọwọ rẹ tabi daakọ adirẹsi ti o wa loke. Yan **Bitcoin (BTC), lori nẹtiwọki Bitcoin**, lẹhinna yan iye eyikeyi ti o fẹ.
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Si gbogbo eniyan ti o bẹrẹ irin-ajo wọn pẹlu Novera: jẹ ki iwariiri rẹ ṣii awọn ilẹkun tuntun, awọn imọran rẹ wa si igbesi aye ati pe gbogbo ẹda mu ọ lọ siwaju diẹ sii.
TRON-ABS
Ọgbẹni Sachet Jean-Marc - Oniwadi olominira - Faranse
Iṣẹ ọna Eniyan pẹlu AI
O ṣeun fun gbogbo eniyan ti o ṣe alabapin si aye to dara julọ. Nipasẹ awọn awari wọn, iṣẹ, atilẹyin ara wọn ati imọ ti wọn kọja, wọn ti ṣe iranlọwọ fun wa lati de ibi ti a wa loni.
A fẹ wọn ni ohun ti o dara julọ fun ọjọ iwaju, pẹlu gbogbo eniyan ti o gbe ẹmi pinpin ati iranlọwọ fun awọn miiran siwaju.
Ohun elo Idagbasoke: 🧠 Codex — GPT-6.1 Sol