SiliconFlow

🎁 Free Access for First 2 Weeks Meet Tencent Hunyuan's Hy3 Now with T+0 support on SiliconFlow 🎉 Hy3: 295B MoE / 21B active / 262K context ✅ Refined iteratively through 50+ real business scenarios ✅ Cuts hallucinations & knowledge errors in half ✅ Stays on-intent over long-horizon tasks ✅ Stable agent execution with more tool-call wins, no infinite loops Put it to real work on SiliconFlow ⬇️ https://lnkd.in/g9EGnnW5

The full model behind "Owl Alpha" on OpenRouter is here🦉  Let's meet Meituan LongCat's latest flagship model, LongCat-2.0   Now Day 0 live on SiliconFlow 🔥 💰 Input Cache/Input/Output: $ 0.015/0.75/2.95 per 1M tokens ⚙️ 1.6T-param MoE (~48B active) · Native 1M context window 🧠 Built for agentic coding from the ground up:  ◆ LSA: sparse attention that scales efficiently to 1M  ◆ Zero-Compute Experts: dynamic 33B–56B active/token, no wasted compute  ◆ MOPD: three specialized expert groups (Agent / Reasoning / Interaction), gate-routed per task  🏆 59.5 SWE-bench Pro: on par with mainstream close-sourced models Start building with 🐱👇 https://lnkd.in/eRq29NrK

Code like a real G 😎 Congrats to Z.ai's GLM 5.2 ranks #1 as available model on CodeArena 💪 SiliconFlow is proud to be T+0 launch partner🔥 💰 Input Cache/Input/Output: $ 0.26/1.40/4.40 per 1M tokens 📚 Usable 1M context for entire codebases and project-scale workflows ⚙️ Reliable long-horizon execution that stays on track through complex tasks 💪 Production-grade coding on par with Opus 4.8 🧠 Dual thinking modes: max for depth, high for quality-cost balance And it's still fully open-source. Big shoutout to Z.ai for keeping frontier model accessible to builders and the community 🙌 Get started today 👇 https://lnkd.in/g6WadhSz

Better Coding with Less Overthinking. K2.7 Code takes K2.6's strong base and goes deep. Meet Kimi (Moonshot AI) K2.7 Code on SiliconFlow — coding-focused, agentic, purpose-built on K2.6. 💰 Cache Input/Input/Output: 0.19/0.94/4.00 per 1M tokens 💪Improved coding & agentic performance, approaches GPT5.5 & Opus 4.8 🧠Less overthinking: 30% lower reasoning-token usage vs K2.6 ⚙️Long-horizon coding: better instruction following, higher end-to-end task completion rates 32B Activated/ 1T Params | VLM | Interleaved Thinking | Multi-Step Tool Call Try it on SiliconFlow ⬇️ https://lnkd.in/gKi-jaki

If you need one model for agents, long context, and multimodal inputs — this is it. Meet Google's Gemma 4 12B on SiliconFlow🔥 💰Input / Output: $0.1 / $0.3 per 1M tokens on SiliconFlow 🛠️ 262K Context | Built-in Thinking | Native Tool Calling | 140+ Languages ✨ Encoder-free architecture: vision and audio inputs flow directly into the LLM backbone, reducing process latency 🧠 12B Size, 26B Brain: nearing Google's 26B performance, excel at multi-step reasoning and agentic workflows Try it on SiliconFlow ⬇️ https://lnkd.in/gMpRCHur

Post-training is having a moment — Nex-N2-Pro from neolab Nex-AGI proves it. Built on Qwen3.5-397B-A17B, delivers GPT-5.5 and Claude Opus 4.7–level performance. 🎉 T+0 Support on SiliconFlow · Free for First 2 Weeks N2-Pro: 397B MoE / Reasoning Model / 262K context / VLM → Auto-adjusts reasoning depth, 30–50% fewer thinking tokens, no performance trade-off → SOTA performance on Terminal Bench 2.1, GDPVal, SWE-Verified → Excels at agentic coding, deep search, tool use → Plug-and-play with Claude Code, Cursor, OpenClaw, etc. Try it on SiliconFlow ⬇️ https://lnkd.in/e4CyutPs

Coding like Opus4.7 / 1M context window / Native multimodal MiniMax M3 is now on SiliconFlow with day-0 support 🔥 🎉 Limited-time 50% off for 7 days Cache / Input / Output: $0.06 / $0.30 / $1.20 per 1M tokens (Regular: $0.12 / $0.60 / $2.40) M3 is the first open-source model combining all three frontier capabilities: → Coding & Agentic: beats GPT-5.5 and Gemini 3.1 Pro on SWE-Bench Pro → 1M context via MiniMax Sparse Attention → Native multimodal from step zero — image, video & computer use Try it on SiliconFlow ⬇️ https://lnkd.in/gfd-QkcW

~15% off for Kimi (Moonshot AI) K2.6 on SiliconFlow💰 Input pricing: $0.90/M → $0.77/M But a lower price is only part of the story. For developers, reliability matters just as much as cost — and the numbers back it up: → 0.21% avg tool call error rate — top-tier performance on OpenRouter → 80%+ cache hit rate — faster responses, lower costs on repeated context → FP8 quantization + Zero Data Retention Lower price. Fewer errors. More reliable workflows. Now's the time to ship more with K2.6 on SiliconFlow 👉 https://lnkd.in/g9uXV4GR

Think small. Build big🔥 Qwen 3.5 & Qwen3.6 series are now live on SiliconFlow 🎉 9B to 397B · MoE & Dense · Native Multimodal ✅ Qwen3.6-35B-A3B · Qwen3.6-27B ✅ Qwen3.5-397B-A17B · Qwen3.5-122B-A10B ✅ Qwen3.5-35B-A3B · Qwen3.5-27B · Qwen3.5-9B Smaller models. Bigger results. Community's favorite. Now, pick your size and start building 👇 https://lnkd.in/gg582acv

Builders are voting with their tokens 🔥 SiliconFlow is now the #1 third-party model provider by daily token usage On OpenRouter, • ~280B tokens/day • ~1.9T tokens/month • 33 frontier models: DeepSeek V4 series, GLM 5.1, Kimi K2.6 etc. Big thanks to every dev building with us And more is coming🚀 Try it now on SiliconFlow: https://lnkd.in/g-rFhNcj SiliconFlow BYOK on OpenRouter: https://lnkd.in/gGYiqVqs Explore more on OpenRouter: https://lnkd.in/gzHEgY8h