Three major releases within 24 hours
The past 24 hours have been packed for the AI industry. xAI's Grok 4.6, DeepSeek's official V4 Pro 0813, and Alibaba Qwen's open-weight Qwen3.8-2.4T-A95B all landed almost simultaneously, each with a different strategy.
Qwen3.8-2.4T-A95B: the largest open-weight model ever
Alibaba's Qwen team open-sourced a Qwen-Max-class model for the first time. When Qwen3.8-Max launched on August 3, the announcement promised open weights "next week"; both BF16 and FP8 versions went up on Hugging Face this week. The model card hit 480+ points on Hacker News today (August 13), with Simon Willison commenting that it may be the largest open-weight release by parameter count.
Specs: 2.4T total parameters with 95B active, MoE with 512 experts (10 routed + 1 shared), 92 layers. Native context of 262K, extensible to 1M. The open model is text-only and requires thinking mode for all interactions, with reasoning_effort tunable across xhigh/medium/low.
The standout benchmark is PaperBench at 93.0, ahead of GPT-5.6 Sol (90.5) and Fable 5 (88.8). Terminal Bench 2.1 comes in at 86.6, second only to Sol's 88.8; GPQA Diamond 92.6 and IFBench 82.8 are both at the top tier. Overall it sits in the same band as Claude Opus 4.8, which is also Qwen's official comparison target.
The trade-off is deployment. The BF16 weights are roughly 5TB, and the community has noted that only BF16 and FP8 are available at launch, with no QAT quantization; serving requires the latest vLLM, SGLang, or TokenSpeed. The API version, Qwen3.8-Max, costs $2/$6 per 1M input/output tokens (≈¥14.6/¥43.8), with vision input, 1M context, and built-in tools.
DeepSeek V4 Pro 0813: official release with big agent gains
On August 13, DeepSeek upgraded its API model from V4-Pro-Preview to the official deepseek-v4-pro-0813. Pricing is unchanged: $0.435 input (≈¥3.2), $0.87 output (≈¥6.4), and $0.003625 cache-hit per 1M tokens, with 1M context and up to 384K output.
The gains are concentrated in agentic capabilities. According to community-compiled benchmarks (sourced from Reddit r/LocalLLaMA): Terminal Bench 2.1 jumped from 72.1 (preview) to 87.9, DeepSWE from 12.8 to 62.7, Cybergym from 52.7 to 83.3, and NL2Repo from 38.5 to 61.5. Several key items now beat GLM-5.2 and sit on par with Kimi K3 and Claude Opus 4.8.
The model natively supports the Responses API (so it plugs into Codex) and keeps an Anthropic-compatible endpoint. The HN thread scored 722 points, making it the hottest post of the day.
Grok 4.6: xAI returns to the frontier
Grok 4.6, released August 12, is the most significant update from xAI (now operating publicly as SpaceXAI) in over a month. It scores 61 on Artificial Analysis' Intelligence Index, level with GPT-5.6 Sol, behind Claude Opus 5 (63) and Fable 5 (62), and 5 points up from Grok 4.5's 56.
AA's evaluation shows its strength is in agentic work: GDPval-AA v2 Elo of 1753, second only to Claude Opus 5; τ³-Banking at 50.7%, tied with Qwen3.8 Max near the top; Terminal-Bench v2.1 at 88.4%, in line with the leaders. Static reasoning is comparatively weaker — x.ai's own table shows DeepSWE at 65.9%, behind GPT-5.6 Sol's 73%.
Pricing holds at $2/$6 (≈¥14.6/¥43.8) with a 500K context, while cache-hit pricing rises from $0.3 to $0.5. AA estimates about $0.84 per task, similar to Kimi K3, which makes it one of the better-value frontier models. It went live the same day in Cursor, Grok Build, and the API (including OpenRouter, Vercel, and Cloudflare), with 2x included usage for the first week and a 2x-priced fast variant.
Three directions, three strategies
The same-day releases show three distinct approaches. Qwen is betting on openness, releasing its strongest model's weights to build ecosystem; DeepSeek holds the value line with cheap API pricing and much stronger agent skills; xAI pulls its intelligence back to the frontier with Grok 4.6. For developers, the choice is wider and prices keep moving down.