AI

How Kimi K3 compares to Claude Fable 5, GPT-5.6 Sol, and Opus 4.8 across the Intelligence Index, coding arenas, agentic tasks, and price.

Fable 5's included-in-subscription window ends July 7, 2026. Here's exactly how usage credits work, what Fable 5 costs after the switch, and how to set spend limits so an agent doesn't drain your balance.

Baidu's Unlimited-OCR parses entire multi-page PDFs in a single forward pass. Here's how to run the 3.3B open-weights model locally with Transformers, vLLM, or SGLang.

DSpark is DeepSeek's open-source speculative-decoding module that makes V4-Pro and V4-Flash 51–400% faster — and it works on Qwen3 and Gemma 4 too. Here's how it works and how to use it.

DiffusionGemma 26B-A4B is Google’s first open-weight text-diffusion LLM — a 25.2B MoE built on Gemma 4 that generates text in parallel for up to 4x faster output.

Cohere North Mini Code 1.0 is an open-weight 30B MoE coding model (3B active, 256K context, Apache 2.0) built for agentic software engineering. Specs, benchmarks, access.

A practical GPT-5.6 vs GPT-5.5 comparison: what actually changed across the new Sol/Terra/Luna tiers, pricing, reasoning modes, benchmarks, and a clear decision guide on whether to upgrade or stay put.

OpenAI's GPT-5.6 family — Sol, Terra, and Luna — explained: tiers, pricing, the new max and ultra reasoning modes, preview benchmarks, the government-restricted rollout, and what teams building AI agents should prepare.

OpenAI is retiring the gpt-3.5-turbo API on October 23, 2026. Here are the exact shutdown dates, what replaces GPT-3.5, and how to migrate before it's gone.

Claude Fable 5 is back online as of July 1, 2026, after the U.S. lifted its export-control order. Here's what changed, how Anthropic brought it back, and how to access it.

OpenAI's GPT-5.5 Cyber ships gated under the Daybreak program. What 'trusted access' means, the CyberGym-vs-Mythos-5 benchmark claim (and its caveats), and what defenders and developers should take from it.

A coding head-to-head: GLM-5.2's leaderboard-topping text coding vs MiniMax M3's native multimodality, lower price, and MSA long-context speed — with specs, benchmarks, and a clear verdict.

A practical walkthrough for self-hosting GLM-5.2 (744B MoE, 40B active) on llama.cpp. Quant tables, four hardware paths, exact install commands, verification, and a fallback to the Z.ai cloud API if your rig falls short.

Four credible 128GB-class boxes, four very different price points. We synthesise what practitioners with the hardware on their desks are actually reporting.

VibeThinker-3B is WeiboAI's MIT-licensed 3B reasoning model built on Qwen2.5-Coder-3B. We unpack the viral 'Opus 4.5 performance' claim with the actual HF benchmarks.

Z.ai's GLM-5.2 is the leading open-weights LLM on the Artificial Analysis Intelligence Index v4.1. 744B params (40B active), 1M-token context, MIT-licensed weights. Architecture, benchmarks, pricing, and a 3-path local-inference playbook.

Two open-weights heavyweights from China go head-to-head for the agentic-coding throne. K2.7 leads on MCP tool-use depth; V4 leads on raw per-token economics and proven independent benchmarks. We break down cost, agentic strength, self-host paths, and pick a winner per workload.

Moonshot's open-weights Kimi K2.7 Code goes head-to-head with Anthropic's Claude Opus 4.8. Architecture, benchmarks (and where they don't exist yet), per-task cost, agentic strength, self-host paths, and a clean per-workload verdict.

Moonshot's Kimi K2.7 Code and Z.ai's freshly-released GLM 5.2 are both Chinese open-weights coding flagships, both shipped in June 2026, and they trade on opposite axes. K2.7 leads on MCP tool use and pricing; GLM 5.2 leads on 1M context. We pick per workload.

GLM 5.2 ships 1M-token context and MIT open weights on a flat subscription. Claude Opus 4.8 stays the agentic-coding benchmark at premium per-token pricing. We compare cost, agentic strength, self-hosting and pick a winner per workload.

Two open-weights heavyweights from China go head-to-head for the agentic-coding throne. GLM 5.2 leads on context window; DeepSeek V4 leads on token economics. We break down cost, agentic strength, self-host paths, and pick a winner per workload.

OpenAI's flagship versus Z.ai's freshest open-weights challenger. GPT-5.5 holds frontier coding benchmarks; GLM 5.2 ships a 1M window and self-hostable weights. Where each actually wins for engineering teams.

How Moonshot's open-weight Kimi K2.7 Code stacks up against Claude Opus 4.8, GPT-5.5, and DeepSeek V4 for agentic coding — on price, context, and the benchmarks that exist. K2.7's scores are Moonshot-reported only, so the verdict is subject to change once independent results land.

Moonshot AI's Kimi K2.7 Code — a 1T-parameter open-weight coding model with a 256K context, ~30% fewer thinking tokens than K2.6, and strong MCP tool-use. Benchmarks, pricing, API, and local-deployment guide.