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Rookie training. Commissioned by: Anon Ada Wong model by: Rigid3D Leon model by: Scamarai Ada Wong voice by: MIKO_DESH 🔞EN/JP NSFW VA (COMM OPEN) Audio SFX by: 🔊RandomTide🔞 Support me for full 1080p uncompressed version at P4treon! Also your name will appear on my credits too! All info below!

153,478 Aufrufe • vor 9 Monaten •via X (Twitter)

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Summary 2025 🎨 This year has definitely been the most incredible, prolific in my artistic career! Won two official Art contest organized by PlayStation, had my art exhibited at the Fluctuart Galerie in Paris, I also had the honor and opportunity to be officially commissioned by some extremely talented people and studios that I admire, to create official illustrations for Control by Remedy Entertainment, Blades of Fire by 505 Games and MercurySteam, as well as by indie studios that I love with all my heart too, such as Digixart and Lowbirth Games to create special, festive goodies for their teams🖤many thanks to Juha, Antonela, Raphaelle and Chloe, Aicha, I appreciate you all a lot and I am so grateful for the trust. ✨️ The highlight for me was without a doubt being commissioned by the family of Guillaume Broche, creative director of the GOTY Clair Obscur Expedition 33, to create an unique piece for his birthday, a large 1-meter panoramic artwork 🖤 (A big thank you to his brother, Adrien, for his trust.) Then I had the opportunity to collaborate with all the voice actors of Expedition 33 and their agency. Even though the year started off in the best possible way with my work, I had a very difficult and painful year physically, with my health. I don't talk about it often, I'm not really recovered, and the daily pain is sometimes really, really hard to bear. To everyone, I hope you enjoyed this year of non-stop drawings, time lapses, paintings, cosplays, goodies, and I hope you'll still be here with me next year, because I have so many cool things planned for you all!🥰 Thank you for all the love, constant support, the kindness and all the encouragement I received every single day here and on every social media. You made my 2025 an amazing year and I will never forget it. Thank you to all the beautiful people who commissioned me and trusted me enough to let me draw your pets, your kids, your families. This means the world to me. Thank you for all the person who helped me every time my art was stoten, I am so, so grateful. For everything. 🙏🏻🖤

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680,500 Aufrufe • vor 2 Monaten

Cerebras inference is very fast. So fast that it changes how we think about configuring our LLMs for voice agent use cases. Kimi K2.6 is a 1T parameter reasoning model that Cerebras serves at 650 - 1,000 tokens per second (end-to-end throughput), with time to first token metrics as low as 150ms (latency). These numbers are two to three times faster than other similarly capable models. The biggest lever we get from this kind of speed is that we can use the model in reasoning mode, and still have excellent "time to first non-thinking token." This solves a big pain point we have in 2026 for voice agent use cases. Almost all recent innovation in post-training has focused on making models good at reasoning ("test time compute"). This is great, but it makes the user-facing model latency much, much slower. Which is a problem for conversational voice agents. We can run Kimi K2.6 with reasoning turned on, and get responses faster than other models produce with reasoning disabled. On my 30-turn voice agent benchmark, Kimi K2.6 with reasoning enabled ties GPT 5.1 and Haiku 4.5 with reasoning disabled, and is still about 200ms seconds faster! On my primary task agent benchmark, Kimi K2.6 is now the #2 model. It ranks just behind Gemini 3.5 Flash in "high" reasoning mode, and tied with GLM 5, Sonnet 4.6, and GPT 5.4 with reasoning set to "low." But Kimi K2.6 completes each turn in the agent loop in under 500ms. The other four models are all at least 3x slower. (Models only qualify for this benchmark if they can complete task turns at a P50 <4s.) A couple of other things that this speed buys us, for production voice agents: - Tool calls happen fast enough that we don't have to work around tool call latency in our pipeline design. - We can prompt the model to output structured data at the beginning of a response, followed by plain text for voice generation. This opens up possibilities like asking the model to do complex classification/generation tasks that influence the rest of the pipeline. For example, the model could create a detailed style prompt for a steerable TTS model, for each individual conversation turn. And, of course, you can use Kimi K2.6 with reasoning turned off. Cerebras calls this "instant" mode. Here's a video of a Cerebras Kimi K2.6 voice agent with voice-to-voice response time, measured at the client, under 500ms. This is the true response latency as perceived by the user, including all network and audio codec overhead, transcription and turn detection, Kimi K2.6 token generation, and voice generation. 500ms is, effectively, instant. So the Cerebras naming for this mode is a propos. :-)

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40,593 Aufrufe • vor 2 Monaten