Add corrections, implementation notes, pricing changes, or usage caveats for other readers.
Input modalities
Output modalities
Capabilities
32,768 tokens
Recent tweets and retweets from Regolo AI
Both models are MIT-licensed.
Both run on European infrastructure.
Both work via a single OpenAI-compatible API on @regolo_ai
Full 2-tier benchmark breakdown — pricing, radar scores, self-hosting guide, and a 4-model routing pattern:
👉…
Comparing MiniMax-M2 vs DeepSeek-V4-Pro is like comparing a GTX 4070 to an H200.
Wrong question.
The right comparison is by parameter tier:
→ Tier 1 (~230–284B): MiniMax-M2.7 vs DeepSeek-V4-Flash
→ Tier 2 (~456B active): MiniMax-M1 vs DeepSeek-V4-Pro
Here's what the…
The resulting gains?
Generation speedups from ~90 tok/s up to 400+ tok/s on synchronous workloads.
3× to 5× throughput increases.
Zero loss in text quality (the verifier retains final validation control).
Want to build your own DFlash pipeline? I have put together a…
How does DFlash work?
Instead of predicting token-by-token, it uses a transformer with a non-causal attention mask.
Using intermediate hidden states from your verifier (main LLM) and mask tokens, it predicts distributions for a whole block of draft tokens concurrently.
👇
Discuss this model
Add corrections, implementation notes, pricing changes, or usage caveats for other readers.