Chris Scott @greatscottdev
Software Engineer | LLM hobbyist | Problem Solver github.com/chriswritescod… Florida Joined October 2023-
Tweets309
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Following156
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@ryanvogel Thats a good question? What?
Nice feature, something I will take advantage of
Very cool, …loading for some real world testing
Second big release from us today: Nemotron-3.5-ASR-Streaming! 🌎40 languages ⚡️80ms - 1s controllable latency 🔥240 - 2400 concurrent streams on 1xH100 🧱FastConformer Cache-Aware RNN-T architecture huggingface.co/nvidia/nemotro…
@Alibaba_Qwen @ivanfioravanti Nice graphs. show me the weights… tech report, rl methodology.
@rblalock @MichaelDell @RobTiffany @nvidia @Dell @CoreWeave Me too!!
@opencode @MichelleBakels I really like this model, even more running it at home 🏠. Original weights. At 200 t/s
Chris Scott retweeted
Introducing MiniMax M3: The First Open-Weights Model to Combine Three Frontier Capabilities - Coding & Agentic Frontier: 59.0% SWE-Bench Pro, 66.0% Terminal Bench 2.1, 34.8% SWE-fficiency, 28.8% KernelBench Hard, 74.2% MCP Atlas - MiniMax Sparse Attention scales context to 1M - Natively Multimodal from Step Zero API: platform.minimax.io Token Plan: platform.minimax.io/subscribe/toke… 🚀New! MiniMax Code: code.minimax.io Weights & Tech Report in ~10 Days
looks like the sm120 gemm was merged!
vLLM v0.22.0 is out! 459 commits from 230 contributors (63 new). 🎉 Highlights: DeepSeek V4 hardening (NVFP4 fused MoE, full+piecewise CUDA graph, ROCm support), experimental Rust frontend in-Tree, batch-invariant Cutlass FP8 (28.9% lower e2e latency), Model Runner V2 advances,
Good reminder, nothing is free
Chris Scott retweeted
⚡️ Step 3.7 Flash is here: The new frontier is agent efficiency. #1 ClawEval-1.1 (67.1), #1 SimpleVQA Search (79.2), #2 SWE-PRO (56.3), 95.3 on V* Python. Open weights under Apache 2.0. Built for agentic, coding, search, and multimodal workflows — balancing speed, cost, and reliable execution. - 400 TPS. 198B sparse MoE, ~11B active. 256K context, 3 reasoning levels. - Understands UIs, charts, docs, images — then writes code or calls tools to act on what it sees. - Web + visual search reaches further: more sources, deeper follow-up. - Reliable tool use — less drift, fewer broken toolcalls. 98%+ on τ²-bench across all difficulty levels. - Works with Claude Code, KiloCode, Hermes Agent, OpenClaw, and protocols like MCP. - Runs locally on Mac Studio M4 Max, DGX Spark, AMD AI Max+ 395. GitHub: github.com/stepfun-ai/Ste… HuggingFace: huggingface.co/stepfun-ai/Ste… GGUF: huggingface.co/stepfun-ai/Ste… ModelScope: modelscope.cn/models/stepfun… API: platform.stepfun.ai Blog: static.stepfun.com/blog/step-3.7-…
@Alibaba_Qwen @arena Yes if you actually going to release weights for 397b variant! This is what I am still running at home but stuck on 3.5
@jahooma Missing @XiaomiMiMo is that to keep it in the lead?
轻轻地来🕯️�... @qingqingdilaiP
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