Topic
Large language models - benchmarks, capabilities, and how to choose the right one.
109 resources - 92 posts, 16 tools, 1 guide

Qwen3.8-27B is a 27B dense Apache-2.0 model that scores 61.7 on SWE-bench Pro and 42.2 on DeepSWE 1.1 - ahead of Opus 4.6 Max on both - while running on consumer hardware. Benchmarks, hardware math, and an honest when-to-use-it guide.

xAI shipped Grok 4.6 on August 12, 2026: it matches GPT-5.6 Sol on the AA Intelligence Index (61), beats it on CursorBench 3.2, and keeps Grok 4.5's $2/$6 per million token pricing. Available in Cursor and Grok Build today, and in OpenCode as opencode/grok-4.6.

Liquid AI released LFM2.5-VL-3B on August 12, 2026: a 3.1B open-weights vision-language model that averages 80.7 on ScreenSpot-v2, doubles ToolSandbox to 59.5, and decodes at 228 tokens/s on an M5 Max in about 3 GB of memory. Here is what shipped, the benchmark caveats, and how to run it.

Cactus open-sourced Needle 2, a 45M-parameter agentic LLM in a single 14MB binary that runs a full tool-calling session in 28MB of RAM. 500 tok/s on a Raspberry Pi 5, ESP32-S3 class parts, Apache 2.0. Here is what the benchmarks actually show.

A new arXiv paper shows the encrypted reasoning blocks that Anthropic, OpenAI, and Google return to API clients can be replayed into weaker models from the same provider and transcribed verbatim. The authors decoded 315,320 blocks from public repositories and recovered 367 PII artifacts and 182 credentials.

Meta open-sourced Muse Glimmer, a 30B Apache 2.0 multimodal agent model that runs in a 24GB envelope at up to 233 tok/s. MCP Atlas 75.5, SWE-Bench Verified 76.0, 131K context. Here is what the numbers actually say.

xAI released Grok Imagine Image 2.0 on August 7 as the new Quality Mode on grok.com and mobile, ranked second worldwide on both text-to-image and image-editing leaderboards. A 2.0 preview build is already callable through Vercel's AI Gateway with the AI SDK, before xAI's own API access goes live.

WeatherNext Cyclones adds a full day of lead time to tropical cyclone forecasts - roughly a decade of meteorological progress - and now the weights, code, and data feeds are public. What the paper actually shows and how to run it.

GitHub made Kimi K3 generally available in Copilot on August 6 at $3/$15 per million tokens, hosted on Fireworks AI. It is off by default for Business and Enterprise, the rollout was paused mid-day by a GitHub Actions incident, and it changes the price/quality calculus in the model picker.

Meta released Muse Code, a terminal coding agent, and Muse Spark 1.2 on August 5, 2026. The model co-trains with the harness, logs every call to a replay-safe event log, and offers a $0.10/$0.20 contributor tier if Meta may train on your data.

GPT-5.6 Sol gets a chat-focused retune with 68% fewer factual errors in OpenAI's internal eval, a new effort slider, and GPT-5.6 Luna becomes the default model for Free and Go users with unlimited text chats. What the API did not change and why the split matters.

Liquid AI shipped LFM2.5-2.6B on August 4, 2026: a 2.6B open-weight model trained for agentic work inside real harnesses, decoding at 220 tokens/s on an M5 Max and 113 tokens/s on a Ryzen CPU. Here is how it was trained, what the benchmarks say, and how to run it.

Alibaba released Qwen 3.8 Max on August 3, 2026 - a 2.4T-parameter MoE with 95B active per token, a 1M context window, and $2/$6 per million tokens on QwenCloud. It leads PaperBench at 93.0, and the weights open next week.

GitHub deprecated Gemini 2.5 Pro and Gemini 3 Flash in every Copilot surface on July 31, 2026. The suggested replacements are Gemini 3.1 Pro and Gemini 3.6 Flash. Here is what changed, what it costs, and how to migrate cleanly.

An analysis from the Earendil team behind the Pi harness documents how OpenAI, Anthropic, and Google now return provider-sealed state instead of portable transcripts - encrypted reasoning blobs, opaque compaction, hidden subagent messages. The five tests and seven rules for session portability, and why session lock-in matters more than model lock-in.

The sub-$1.50 coding tier just got serious: DeepSeek V4 Flash 0731 posts frontier-adjacent agent scores at $0.14/$0.28 (peak/off-peak pricing from Aug 16), GPT-5.6 Luna dropped 80% to $0.20/$1.20, and Gemini 3.5 Flash and Claude Haiku 4.5 hold the hosted middle. Prices verified July 31 and August 15, 2026.

Claude Mythos Preview is the model that found thousands of zero-days, and you could not buy it. Here is what it is, who got access through Project Glasswing, what it actually found, and where the model line went after it retired.

DeepSeek re-post-trained V4 Flash into an agent workhorse: Terminal Bench 82.7, DeepSWE 54.4, native Responses API, and first-party Codex support - all at $0.14/$0.28 per million tokens. What changed, what the numbers actually mean, and how to wire it up today.

DeepSeek shipped the official V4 Flash release on July 31, 2026. The re-post-trained 0731 build beats V4-Pro-Preview on agent benchmarks at $0.14/$0.28 per million tokens. Here is what changed and how to run it through OpenCode today.

Inkling-Small is a 276B-parameter MoE with 12B active per token, Apache 2.0, and open weights. It beats the 975B Inkling on SWEBench Verified (80.2), HLE (31.6), and tool use at a quarter of the size and a third of the output price.

MiniMax launched H3, an omni-modal generation model that takes text, image, video, and audio input and outputs 2K video with native stereo sound at 0.80 CNY per second. Open weights are promised in the coming days.

Google DeepMind's Gemini Robotics 2 family gives humanoid robots whole-body control, dexterous hands, and multi-robot teamwork - with an ER 2 model devs can try today. The HN thread (575 points, 459 comments) debated how real the progress is.

OpenAI slashes GPT-5.6 Luna by 80% to $0.20/M input tokens, cuts Terra by 20%, adds Sol Fast mode at 2.5x speed, and reveals Sol autonomously optimized its own production kernels.

A companion guide to the Grok 4.5 video: xAI's most intelligent model with a 500K context window, function calling, structured outputs, and a build-mode agent workflow for developers.

Effort levels and model choice both cost more for more capability, but they are not interchangeable. Here is when to move the effort dial and when to switch models instead.

Moonshot AI released the full Kimi K3 weights on HuggingFace today - 2.8T parameters, 1M context, native MXFP4 quantization, ~1.63TB download. The HN community reaction, what the license really says, and why this matters for the open-weights AI market.

Anthropic released Opus 5 on July 24, 2026 - same price as Opus 4.8, within 0.5% of Fable 5 on CursorBench, and the new #1 on Artificial Analysis. We break down the benchmarks, HN reaction, and what it means for every developer choosing a daily-driver model.

Claude Opus 5 ships today with Frontier-Bench SOTA, near-Fable-5 coding at half the price, and self-verification that catches its own bugs. Here is what changed, what to migrate, and when the price-performance curve makes Opus 5 the right default.

A new multi-model orchestration system routes requests across open-weight models to match frontier performance at reduced inference cost. Here is what we know.

Black Forest Labs released FLUX 3, a single multimodal model trained jointly on images, video, and audio that also drives robots on Audi production lines. Here is what it does, how it works, and how to try it.

Kimi K3 is the first open-source 3T-class model with a 1M-token context window, native vision, and OpenAI-compatible API. Here is what it does, how to call it, what it costs, and how it benchmarks against Fable 5 and GPT-5.6 Sol.

Compare every verified Kimi K3 access route, including Moonshot, Together, Fireworks, Baseten, Modal, Vercel AI Gateway, Cloudflare, RunPod, SiliconFlow, OpenRouter, and OpenCode Go.

Kimi K3 brings 2.8 trillion parameters, native vision, a 1M-token context window, and long-horizon agent workflows. Here is what developers should know before adopting it.

Kimi K3 adds native vision, a 1M-token window, and longer agent runs, but K2.7 remains cheaper and easier to deploy. Here is the practical upgrade decision.

Moonshot AI releases Kimi K3 with 2.8 trillion parameters, 1M context window, and Delta Attention architecture. Here's what developers need to know about pricing, performance, and where it fits in the frontier model landscape.

A new American open-weights frontier model with multimodal capabilities, 1M token context, and competitive benchmarks. Here's what the HN community thinks.

PrismML's Bonsai 27B uses 1-bit quantization to compress a 27B model to 3.9GB - small enough to run on an iPhone. Here's how it works and what HN thinks.

A companion guide to the Claude Fable 5 video: what the first general-use Mythos class model is, the walkthrough beats from the review, hands-on developer takeaways, and the pricing and context specs from primary sources.

OpenAI's GPT-5.6 Sol, Terra, and Luna tiers versus Anthropic's Claude Fable 5 and Mythos 5. Verified pricing, benchmarks, and a practical framework for picking a coding model in July 2026.

xAI's Grok 4.5 ships at $2/$6 per million tokens with 80 TPS speeds, a 500k context window, and benchmark results that put it in the Opus and GPT 5.5 tier. What actually shipped, how the pricing compares, and when it makes sense over Claude, GPT, or Gemini.

Tencent's Hy3 ships 295B parameters but activates only 21B per token, matching flagship performance at flash-tier pricing under Apache 2.0.

xAI launched Grok 4.5, trained on trillions of Cursor interaction tokens. At $2/M input pricing, it undercuts Claude and GPT while benchmarking near Opus 4.7 level.

Meta's Muse Image is now in Meta AI, but it is not a public model API. Here is what the launch confirms, what remains preview-only, and how developers should evaluate it.

Meta launches Muse Spark 1.1 through the new Meta Model API - a 1M-token-context model for personal agentic tasks with OpenAI-compatible endpoints, $20 free credits, and pricing that undercuts the competition.

Meta's first paid API model arrives with $1.25/M input tokens, 1M context window, and strong tool-use benchmarks. HN debates what it means for the open-weights company.

Martin Alderson's argument for why open-weights models like GLM 5.2 will compress frontier lab margins is sparking debate on HN. Here is what the thesis actually says, where HN agrees and disagrees, and why it matters for developers choosing models.

Everything developers need to migrate from Sonnet 4.6 to Sonnet 5 - three breaking API changes, the new effort parameter, tokenizer impact, and when to use each effort level. Verified against Anthropic's official docs on July 4, 2026.

Claude Sonnet 5 lands near Opus 4.8 on some tasks for a fraction of the price - but a new tokenizer runs about 30 percent more tokens. Here is the upgrade decision for builders, with the numbers.

Standing up a fleet of Fable 5 agents is the easy part. This is the operations layer - data retention rules, refusal-rate alerting, effort tuning, observability, and availability planning - that keeps the fleet running.

Anthropic's most capable model launched, got suspended by a US export-control order, and returned today. Here is what Fable 5 is, what changed on the way back, and whether builders should reach for it.

The orchestrator is the most important model choice in an agent fleet. A fair head-to-head between Fable 5 and Opus 4.8 for that role, with a decision matrix by run length, budget, compliance, and refusal-handling tolerance.

A companion guide to the GLM 5.2 video: an open-weight model positioned against GPT-5.5, walked through with benchmarks, pricing, and a live OpenCode demo. Here is what the video covers and where to go deeper.

A companion guide to the GPT-5.5 video: OpenAI's newly released model rolling out to ChatGPT and Codex, reviewed through benchmarks, agent capabilities, context window, and pricing. Here is what the video covers and where to go deeper.

Anthropic releases Claude Sonnet 5 with improved agentic capabilities, better tool use, and an introductory pricing deal. Here's what developers need to know.

Switzerland's fully open foundation model promises transparent training data and EU compliance. The HN crowd has questions about actual performance.

Sakana says Fugu Ultra stands with Fable, Mythos, GPT-5.5, Gemini, and Opus by orchestrating models instead of being one giant model. Here is what the benchmarks show, what is novel, and what still needs proof.

Sakana Fugu makes a timely argument for model routing: frontier performance should come from swappable systems, not a hard dependency on one proprietary API.

Sakana Fugu Ultra is not just another giant model. It is a learned orchestration layer that routes work across expert models, matches frontier benchmark claims, and makes a serious case for multi-model AI systems.

Codex can point at OpenAI-compatible model providers, local Ollama servers, and internal model proxies. Here is the practical config pattern, the sharp edges, and when to use it.

No single model wins every task anymore, and the companies that never trained one - Factory, Devin, Perplexity, Cursor, OpenCode - are turning that into a moat. This is how model routing works, why open weights and neoclouds make it cheap, and the honest counter-argument.

Z.ai's GLM-5.2 lands as a 753B open-weights coding model that beats GPT-5.5 on SWE-bench Pro for roughly one-sixth the per-token cost. Here is the real cost math, a worked cost-per-task example, and a when-to-use-which decision guide.

A code-heavy field guide to model routing. Real, runnable-style configs for tiering tasks by complexity, routing simple work to open-weights, reserving frontier models for hard reasoning, building failover chains, and keeping prompt caches warm with OpenRouter, LiteLLM, and Factory Router.

OpenRouter Fusion turns multi-model panels into an API feature. The useful lesson is not to run every prompt through more models. It is to define when a task deserves an expensive second opinion.

Anthropic's docs say the tokenizer introduced with Opus 4.7 can use up to 35% more tokens for the same text. Here is what that does to per-request cost, max_tokens, and cross-model comparisons.

Fable 5 1M context workflows that actually work: whole-repo reviews, log archaeology, multi-doc synthesis - plus the honest math on when RAG still wins.

Fable 5 effort levels explained: what low, medium, high, xhigh, and max actually change, which models support each level, and how effort drives your token bill.

Fable 5 long-running requests can run for many minutes per turn and hours per autonomous run. Here is how to configure client timeouts, streaming keepalive, batch polling, and background patterns so they actually finish.

A practical playbook for running Claude Fable 5 as the orchestrator over Sonnet and Haiku workers, with verified cost math on when the premium pays off.

A verified directory of the frontier AI models in July 2026 - Claude Fable 5, Opus 5, GPT-5.6 Sol/Terra/Luna, Sonnet 5, Gemini 3.1 Pro, Kimi K3, and DeepSeek V4 - with pricing checked against official docs.

How to use Claude Fable 5 across every access path: claude.ai plans through June 22, the Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry, with setup effort and first-prompt tips.

Claude Fable 5 latency measured: 109 seconds to first token at max effort vs 1.4s for Sonnet 4.6. When slow is fine, when it hurts, and how to route around it.

Migrating off retired GPT models in 2026: the live retirement table, what maps to what, an eval-before-switch day plan, and when to jump providers.

Alibaba shipped Qwen 3.7 Max on May 19, 2026 with a 1M token context window, Anthropic-compatible API, and agent-first architecture. Here is what developers need to know about pricing, performance, and when to use it.

Twelve documented Claude Fable 5 use patterns - agent orchestration, overnight runs, 1M-context refactors, effort tuning - each with a how-to seed and doc link.

Anthropic broke its own naming ladder when it introduced the Mythos class and Claude Fable 5. Here is what the shift means, how to map each tier to a real workload, and what questions it leaves open.

Apple shipped a LanguageModel protocol at WWDC 2026 that lets iOS and macOS developers swap between Claude, Gemini, and local models with a single dependency change. Here is what OS-level provider abstraction actually means for switching costs, moats, and your architecture decisions.

Fable 5 posts an 80.3% SWE-Bench Pro score and costs 2x Opus 4.8 - here is the task-profile scoring guide that tells you when the premium pays off.

Anthropic shipped two names for one architecture on June 9, 2026. Here is what separates Fable 5 from Mythos 5, who can actually get unrestricted access, and what developers should do right now.

The AI coding market is noisy. The changes that matter are easier to spot when you separate model capability, editor loops, terminal agents, background agents, agent frameworks, UI layers, context, security, and cost.

The models.dev project is trending because AI teams need one boring source of truth for model specs, pricing, context windows, modalities, and tool support.

DeepSeek V4 is trending because it is close enough to frontier coding models at a much lower token price. The real question for developers is where cheap reasoning belongs in an agent stack.

DeepSeek V4 splits into Flash and Pro, ships a 1M context window, and undercuts every closed model on price. Here's how to wire it up with the OpenAI SDK, when to pick it over Claude or GPT, and what changed since V3 and R1.

A practical walkthrough of Nemotron 3 Super: latent mixture of experts, hybrid Mamba transformer architecture, 1M context, reasoning modes, and the code you actually need to run it on NVIDIA hardware.

Anthropic's Claude Haiku 4.5 delivers Sonnet 4-level coding performance at one-third the cost and twice the speed. Here is what developers need to know.

DeepSeek's R1 and V3 models deliver frontier-level performance under an MIT license. Here's how to use them through the API, run them locally with Ollama, and decide when they beat closed-source alternatives.

Meta's Llama 4 family brings mixture-of-experts to open source with Scout and Maverick. Here's how to run them locally, access them through APIs, and decide when they beat the competition.

Claude vs GPT for real TypeScript work: benchmarks, pricing, model families, and the practical differences that matter when picking a coding model.

A developer's comparison of OpenAI and Anthropic ecosystems - models, coding tools, APIs, pricing, and which to choose for different use cases.

NVIDIA's Nemotron 3 Super combines latent mixture of experts with hybrid Mamba architecture - 120B total parameters, 12B active per token, 1M context, and up to 4x more experts at the same cost.

xAI has launched Grok 4, claiming the title of the world's most powerful AI model. With a $300/month Super Grok tier, saturated AMI benchmarks, and a coding model on the horizon, this is xAI's bigge...

Alibaba released Qwen 3 with eight models under an Apache 2 license, including a 235B mixture-of-experts flagship that beats Llama 4 Maverick on nearly every benchmark while being smaller and cheaper to run.

xAI launched Grok 3 with 200,000 GPUs, outperforming GPT-4o, Sonnet 3.5, and DeepSeek R1 on reasoning benchmarks. Here is what the hardware, the benchmarks, and the new features actually mean for developers.
Anthropic's AI. Opus 4.6 for hard problems, Sonnet 4.6 for speed, Haiku 4.5 for cost. 200K context window. Best coding model I've tested. Max plan ($200/mo).
AI ModelsOpenAI's flagship. GPT-4o for general use, o3 for reasoning, Codex for coding. 300M+ weekly users. Tasks, agents, web browsing, DALL-E, code interpreter.
AI ModelsUnified API for 200+ models. One API key, one billing dashboard. OpenAI, Anthropic, Google, Meta, Mistral, and more. Automatic fallbacks and load balancing.
AI ModelsOpen-source reasoning models from China. DeepSeek-R1 rivals o1 on math and code benchmarks. V3 for general use. Fully open weights. Extremely cost-effective API.
AI ModelsMeta's open-source model family. Llama 4 available in Scout (17B active) and Maverick (17B active, 128 experts). Free to use, modify, and deploy commercially.
AI ModelsEuropean open-weight models. Mistral Large for complex tasks, Mistral Small for speed, Codestral for code. Strong multilingual support. Open and API options.
AI ModelsOpenAI's latest flagship model. Major leap in reasoning, coding, and instruction following over GPT-4o. Powers ChatGPT Plus/Pro and the API. Available via API and ChatGPT.
AI ModelsGoogle's frontier model family. Gemini 2.5 Pro has 1M token context and top-tier coding benchmarks. Gemini 3 Pro pushes reasoning further. Free tier via AI Studio.
AI ModelsxAI's model with real-time X/Twitter data access. Grok 3 rivals top models on reasoning. Built-in web search and current events awareness. Available via API.
AI ModelsAnthropic's smallest Claude 4.5 model. Near-frontier coding performance at one-third the cost of Sonnet 4 and up to 4-5x faster than Sonnet 4.5. $1/$5 per million tokens.
AI ModelsAlibaba's flagship open-weight coding model. 480B total parameters, 35B active (MoE). Native 256K context, scales to 1M. Apache 2.0 license. State-of-the-art agentic coding.
AI ModelsDeepSeek's reasoning-first model built for agents. First model to integrate thinking directly into tool use. Ships alongside V3.2-Speciale, which rivals GPT-5 and Gemini 3.0 Pro.
AI ModelsAnthropic's flagship reasoning model. Best-in-class for coding, long-context analysis, and agentic workflows. 1M token context window. Available via API and in Claude Code.
AI ModelsAnthropic's first generally available Mythos-class model, released June 9, 2026. 1M context, 128K max output, $10/$50 per million tokens. Built for long-horizon agentic work.
AI ModelsAnthropic's recommended default for complex work, released May 28, 2026. 1M context, 128K output, $5/$25 per million tokens. Defaults to high effort on all surfaces.
AI ModelsDeepSeek's open-weights frontier family, previewed April 24, 2026. V4-Pro is 1.6T total / 49B active params; V4-Flash is 284B / 13B. 1M context standard. Weights on Hugging Face.
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