Alibaba (Qwen) model releases

Alibaba's largest model to date and the flagship of the new Qwen3.8 line — a 2.4-trillion-parameter, fully multimodal model that Alibaba positions just behind Anthropic's Fable 5 on overall performance (vendor internal evals; no independent third-party benchmarks yet). Launched Jul 19, 2026 as Qwen3.8-Max-Preview, available to developers via Alibaba's Token Plan subscription and the Qoder / QoderWork coding platforms. Architecture is presumed sparse-MoE; active-parameter count, context window, and pricing are undisclosed. Breaking from the API-only pattern of earlier Max models, the Qwen team says it will release open weights "soon," though no timeline, license, or full specs have been announced.

Multimodal sibling of Qwen3.7-Max that adds vision input and GUI grounding for screen perception, browser automation, and hybrid GUI+CLI agent workflows. 1M-token context; closed-weights and API-only. Previewed at the May 2026 Alibaba Cloud Summit and reached general availability in June 2026 at a low price point ($0.40/$1.60 per 1M tokens).

Alibaba's proprietary flagship in the Qwen3.7 "Agent Frontier" line — a text-only sparse-MoE model with a 1M-token context, tuned for long-horizon agentic, coding, and reasoning workloads. Parameter count is undisclosed; access is API-only via Alibaba Cloud Model Studio / DashScope (and aggregators such as OpenRouter).

Dense 27B that punches far above its weight on agentic coding — easy to self-host on a single GPU node.

The flagship of Alibaba's small dense Qwen3.5 models. Independent analysis (Artificial Analysis) rated it the most intelligent model under 10B parameters at launch — roughly double the score of the next-closest sub-10B models — and the most intelligent multimodal model under 15B, leading peers on MMMU-Pro (~69%). A dense 9B with native vision, a 262K-token context, and the Qwen3.5 family's unified hybrid thinking / non-thinking mode. Native weights are BF16; in 4-bit it needs ~6GB, within reach of consumer laptops. High intelligence comes with heavy reasoning token usage (~260M output tokens to run the Intelligence Index).

A dense 4B in Alibaba's small Qwen3.5 family, rated by Artificial Analysis as the most intelligent model under 5B parameters at launch — outscoring several 7B–9B peers despite roughly half the parameters. Native vision, a 262K-token context, and the family's hybrid thinking / non-thinking mode; Apache-2.0 licensed. Scores ~65% on MMMU-Pro multimodal reasoning and runs in ~3GB at 4-bit, suitable for lightweight on-device agents.

A dense 2B Qwen3.5 model built for high-throughput, low-latency edge and on-device use. Despite its size it matches a 7B-class peer on Artificial Analysis's Intelligence Index. Apache-2.0, with native vision, a 262K-token context, and the family's hybrid thinking / non-thinking mode; runs in under 2GB at 4-bit, fitting laptops and smartphones.

The smallest Qwen3.5 model — a dense 0.8B designed for the most constrained on-device deployments, operating in non-thinking (instruct) mode by default. Apache-2.0, with native vision, a 262K-token context, and the family's hybrid thinking / non-thinking mode; needs roughly 2GB of VRAM and runs under 2GB at 4-bit, targeting smartphones and embedded hardware. Notable for a sub-1B model, it still scores ~26% on MMMU-Pro multimodal reasoning.

Native vision-language MoE supporting 201 languages with a 1M-token context.

Apache-licensed Qwen3-Next coding-agent model with 80B total / 3B active parameters, 256K context, and long-horizon tool-use training.

Alibaba Qwen's large open coding-agent model: a 480B-total / 35B-active MoE released under Apache-2.0, tuned for code generation, repository-level software engineering, tool calling, and long-horizon agent workflows with a 256K-token native context.

Largest open Qwen3 MoE, introducing hybrid thinking/non-thinking modes and 119-language coverage.

Local omni-modal Qwen model that supports text, image, audio, video, and speech generation in a 7B package.

Proprietary MoE flagship for the Qwen2.5 generation, released through Qwen Chat and Alibaba Cloud APIs.

Vision-language Qwen2.5 model for image, document, video, and agentic visual grounding tasks.

Qwen's first public reasoning-preview model, aimed at math, coding, and deliberate problem solving.

Code-specialized Qwen2.5 model family, with the 32B checkpoint as the flagship open coding model.

Broad Qwen2.5 foundation-model update spanning general, coding, math, and multimodal descendants.

Qwen2's largest dense model, introducing stronger multilingual support, coding/math gains, and long-context variants.

Largest Qwen1.5 model, released as the bridge from the original Qwen line to Qwen2.

Largest chat-tuned Qwen1.5 dense checkpoint, released with stronger human-preference alignment, multilingual support, and 32K context.

Alibaba's first major open Qwen model and the start of a prolific open-weight line.

Second open Qwen size, expanding the first-generation Qwen language-model lineup.

Alibaba's first open Qwen checkpoint and the start of the Qwen open-model line.