Posts tagged “open-weights”

• DeepSeek V4 Flash Vision Is Open. The API Is Still Harder to Beat

  DeepSeek released MIT-licensed V4 Flash Vision weights. Here is the cost, deployment reality, benchmark caveats, and agent-builder playbook.

• Cohere’s North Micro Vision Gives Documents Their Pixels Back

  Cohere’s 2.4B North Micro Vision preserves native page detail for local OCR, but builders must supply the runtime and reasoning layer.

• LFM2.5-VL-3B Gives the Edge Eyes. Keep Its Hands Tied.

  Liquid AI’s LFM2.5-VL-3B brings screen grounding, OCR, and tool calling to local devices—but builders should separate sight from action.

• Meta Muse Glimmer Fits a 30B Agent Stack on 24 GB—With Fine Print

  Meta’s open-weight Muse Glimmer 30B targets 24 GB hardware with vision, long context, tools, and DFlash. Here is what builders should test first.

• JoyAI-Video-Edit Hits 30 FPS. The Stream Still Runs on Five Clocks.

  JD’s open-weight JoyAI-Video-Edit reports 30 FPS on one B200. Here’s what latency, stream state, and single-session serving mean for builders.

• DeepSeek V4-Flash-0731 Makes the Harness Part of the Model

  DeepSeek V4-Flash-0731 adds major agent gains, Codex-ready Responses API support, and open weights. Here is how builders should evaluate it.

• LG’s K-EXAONE 2.0 Makes Open Weights a Cluster Procurement Decision

  LG’s 750B K-EXAONE 2.0 is Apache 2.0, agent-ready, and built for eight H200s. Here is what its open-weight economics mean for builders.

• Inkling-Small Puts Open Weights Back in the Agent Router

  Thinking Machines’ Inkling-Small pairs 12B-active MoE compute with open weights. Here is where it fits—and where it should escalate.

• Poolside Laguna S 2.1 Makes Open-Weight Coding an Operations Problem

  Laguna S 2.1 pairs cheap hosted inference with open weights. The tradeoff is a deployment contract that changes by checkpoint, runtime, and mode.

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