I guess Ling-2.6-Flash is actually the stealth model Elephant Alpha that was making waves a few days ago.
Summary
Ling-2.6-Flash appears to be the previously rumored stealth model 'Elephant Alpha' that had recently gained attention.
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Ling-3.0-flash is another potential model to test before qwen3.8 27b
Ling-3.0-flash is a new model that the author tested and found capable of fixing hard software bugs that Qwen3.6-27b could not, with speed similar to DeepSeek V4 flash. Its release has been delayed to August 6.
So... has anyone actually figured out whose model Elephant Alpha is yet?
Community discusses the identity of 'Elephant Alpha', a 100B parameter model ranked #1 on OpenRouter with 256K context window, fast inference speed, and strong coding capabilities but poor Chinese support, speculating on which company might be behind it.
@AntLingAGI: Introducing Ling-2.6-flash, an instruct model with 104B total parameters and 7.4B active parameters. Ling-2.6-flash is …
Ling-2.6-flash is a 104B-total/7.4B-active sparse instruct model optimized for token efficiency, aiming to cut costs and boost throughput on agent tasks.
Ling-3.0-flash weights: SGLang says day-0, vLLM says when they land, llama.cpp closed the 2.6 request as not_planned
The article details the current support status for the Ling-3.0-flash model weights across inference engines: SGLang commits to day-0 integration, vLLM awaits open weights, and llama.ccp lacks conversion for the Bailing MoE variant. It notes that the release pattern involves a free API window followed by open-sourcing, as seen with Ling-2.6-flash.
@Chinazhidx: Ant Group just released Ling-3.0-flash • 124B MoE • 5.1B active params/token • 256K context, expandable to 1M Just 1/8 …
Ant Group released Ling-3.0-flash, a 124B MoE model with 5.1B active parameters per token and 256K context expandable to 1M, matching or outperforming their 1T flagship model on most benchmarks.