Artificial Analysis vs Rankscale.ai

New Articles: Benchmarking GPT-6 Astra, Intelligence Index v4.3, and more

The articles page now shows 105 articles (up from 94), with new entries including 'Benchmarking GPT-6 Astra' (Sep 9, 2026), 'Announcing the Artificial Analysis Intelligence Index v4.3' (Sep 7, 2026), 'OpenBMB releases MiniCPM5-2B' (Sep 7, 2026), 'Announcing Artificial Analysis Intelligence Index v4.2' (Sep 4, 2026), 'Muse Spark 1.3: Meta reaches the frontier' (Sep 2, 2026), 'Google has released Gemini 3.8 Flash' (Sep 2, 2026), 'Claude Fable 5.1 tops the Artificial Analysis Intelligence Index' (Sep 1, 2026), 'Agnes AI releases Agnes 2.5 Pro Beta' (Aug 27, 2026), 'Intelligence at pocket scale' (Aug 24, 2026), 'Announcing the Speech Agent Arena' (Aug 24, 2026), and 'Announcing the Artificial Analysis Search Index' (Aug 18, 2026).

DeepSeek Launches V4.1 Flash with Novel Encoder-Decoder Architecture

DeepSeek released DeepSeek-V4.1-Flash, a 763B-parameter mixture-of-experts model employing a novel causal encoder-decoder architecture with 8B active parameters for prefill and 16B for decode. It features native vision understanding, 1M token context, an MIT license, and extreme inference efficiency, claiming up to 1/8 KV cache footprint versus V4 Flash. Independent evals (Artificial Analysis Index 40, Vals Index #1 open-weight) show it surpasses V4 Pro at lower cost. API pricing is $0.30/1M input and $1.20/1M output tokens. DeepSeek has soft-retired V4 Pro, routing traffic to V4.1 Flash. The model supports SSD offload and local deployment, with Ollama and Baseten offering day-0 support. Technical discussions highlight the architecture's novelty and potential impact on long-context agents.

• DeepSeek launched V4.1-Flash with a causal encoder-decoder architecture, 763B total params (8B prefill/16B decode active).
• Artificial Analysis Index scores V4.1-Flash at 40, above V4 Pro and below GLM-5.3-Flash.
• API pricing: $0.30 per 1M input tokens, $1.20 per 1M output tokens, cached input $0.006 per 1M.

ModelBest Releases MiniCPM5-2B Edge AI Model

Chinese AI startup ModelBest, in collaboration with the OpenBMB open-source community, has released MiniCPM5-2B, a 2-billion-parameter open-source language model designed for edge devices. The model natively supports tool calling, deep search, code generation, and multi-step reasoning, enabling general-purpose agentic capabilities on resource-constrained hardware. It ranks #1 on the Intelligence Index among open-source models under 4 billion parameters, according to Artificial Analysis, and scores 20 on the Agentic Index. ModelBest has open-sourced the full-stack technical suite, including datasets, training recipes, and reinforcement learning infrastructure, to foster reproducibility. The model aims to shift advanced AI from centralized clouds to edge devices, enhancing privacy, reducing latency, and cutting cloud API costs. Downloads across the MiniCPM family have surpassed 50 million.

• ModelBest released MiniCPM5-2B, a 2-billion-parameter open-source language model for edge devices.
• MiniCPM5-2B ranks #1 on the Intelligence Index among open-source models under 4 billion parameters.
• The model scores 20 on the Agentic Index for autonomous task execution.