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Posts tagged open-source

10 posts tagged "open-source".

· 3 min read

DeepSeek V4.1 Flash 1017 is live on IndieRouter, same id, same price

DeepSeek's October update to V4.1 Flash now serves deepseek-v4.1-flash: stronger on coding and agent benchmarks, shorter outputs, still ₹20 / ₹60 per M tokens.

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· 6 min read

Ling-3.1-flash: a 560B open model built mostly on linear attention

inclusionAI released Ling-3.1-flash under MIT: 560B parameters, 25B active, 7 of every 8 layers linear attention. What the benchmarks say and what to check.

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· 3 min read

DeepSeek V4.1 Flash is live on IndieRouter, and cheaper than V4

DeepSeek's newest open-weight Flash model, served from our GPUs in India: native vision, tool calling, 262K context, ₹20 / ₹60 per million tokens.

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· 4 min read

DeepSeek opened V4 Flash Vision weights under MIT

Ten days after the API drop, V4 Flash Vision Exp is on Hugging Face under MIT. 305B MoE, 1M context, same token price as text Flash.

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· 5 min read

AMD skipped ROCm 8 and 9. Here is what 10 ships

ROCm 10.0 jumps from 7.14 to a TheRock-built Core SDK plus ROCm.AI. The 3.3x inference claim is real lab data, not a free upgrade.

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· 5 min read

Qwen3.8-Flash-Next previews the Qwen4 architecture

Alibaba's Qwen3.8-Flash-Next is an open-weight Qwen4 architecture preview. Confirmed facts, rumored 125B-A6B specs, and what is still missing.

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· 5 min read

The first 3T-class open model is here. What Kimi K3 changes

Moonshot shipped Kimi K3, a 2.8 trillion parameter open-weight model you can actually self-host. Here is what the largest open model yet means for India.

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· 5 min read

Your frontier model can be switched off by a foreign government

When the US ordered Anthropic to cut foreign access to its frontier models, AI sovereignty became real. Here is what Indian teams should do.

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· 5 min read

The real cost of LLM inference is the GPU you are not using

Token prices have fallen roughly 600x since 2020, but real inference cost is set by GPU utilization, not the sticker price. Here is the math.

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· 5 min read

Qwen3.8-27B is the open-source model Indian teams can build on

Qwen3.8 shipped twice under two licences: an Apache 2.0 27B that keeps vision, and a 2.4T flagship under a revenue-share licence. Which can you build on?

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