[Alibaba Cloud](/ai-gateway/models/labs/alibaba) # Qwen3 Next 80B A3B Thinking Qwen3 Next 80B A3B Thinking is a hybrid Transformer-Mamba reasoning model that combines 80 billion total parameters (3B active per token) with a dedicated thinking mode, achieving strong results on AIME25 while supporting ultra-long contexts of 262.1K tokens. Your use is subject to Alibaba Cloud's [Terms](https://www.alibabacloud.com/help/en/legal/latest/alibaba-cloud-international-website-product-terms-of-service-v-3-8-0) & [Privacy](https://www.alibabacloud.com/help/en/legal/latest/alibaba-cloud-international-website-privacy-policy) Policies. ReasoningTool Use [Use with AI Gateway](https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai%3Futm_source%3Dgateway-model-page%26utm_campaign%3Dai-gateway-models&title=Get+Started+with+Vercel+AI+Gateway) [View docs](https://vercel.com/docs/ai-gateway) AI SDKChat CompletionsMessagesResponses ``` 1import { streamText } from 'ai' 2 3const result = streamText({ 4 model: 'alibaba/qwen3-next-80b-a3b-thinking', 5 prompt: 'Why is the sky blue?' 6}) ``` [Read docs](https://vercel.com/docs/ai-gateway/sdks-and-apis/ai-sdk) [Overview](/ai-gateway/models/qwen3-next-80b-a3b-thinking) [API](/ai-gateway/models/qwen3-next-80b-a3b-thinking/api) [About](/ai-gateway/models/qwen3-next-80b-a3b-thinking/about) [Providers](/ai-gateway/models/qwen3-next-80b-a3b-thinking/providers) [Throughput](/ai-gateway/models/qwen3-next-80b-a3b-thinking/throughput) [Latency](/ai-gateway/models/qwen3-next-80b-a3b-thinking/latency) [Uptime](/ai-gateway/models/qwen3-next-80b-a3b-thinking/uptime) [Status](/ai-gateway/models/qwen3-next-80b-a3b-thinking/status) [Similar](/ai-gateway/models/qwen3-next-80b-a3b-thinking/similar) [FAQ](/ai-gateway/models/qwen3-next-80b-a3b-thinking/faq) ## [Copy link to heading](#playground)Playground Try out Qwen3 Next 80B A3B Thinking by Alibaba Cloud. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days. ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=48&q=75)Qwen3 Next 80B A3B Thinking ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=96&q=75) Qwen3 Next 80B A3B Thinking ## [Copy link to heading](#providers)Providers Route requests across multiple providers. Copy a provider slug to set your preference. Visit the [docs](/docs/ai-gateway/provider-options) for more info. Using a provider means you agree to their terms, listed under Legal. | Provider | | --- | | Context | Max Output | Latency | Throughput | Input | Output | Cache | Web Search | Capabilities | ZDR | No Training | Free Tier | Release Date | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=48&q=75) [Alibaba Cloud](/ai-gateway/models/providers/alibaba) Legal:[Terms](https://www.alibabacloud.com/help/en/legal/latest/alibaba-cloud-international-website-product-terms-of-service-v-3-8-0)•[Privacy](https://www.alibabacloud.com/help/en/legal/latest/alibaba-cloud-international-website-privacy-policy) | 131K | 33K | 0.5s | 359tps | $0.15/M | $1.20/M | | — | | | | | 09/11/2025 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | ![vertex logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Fvertex%2520ai.png&w=48&q=75) [Google Vertex AI](/ai-gateway/models/providers/vertex) Legal:[Terms](https://cloud.google.com/terms/service-terms)•[Privacy](https://cloud.google.com/privacy) | 262K | 262K | 0.3s | 142tps | $0.15/M | $1.20/M | | — | | | | | 09/11/2025 | | ## [Copy link to heading](#throughput)Throughput24 hours 1W 1D P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/metrics) for more info. ## [Copy link to heading](#latency)Latency24 hours 1W 1D P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/metrics) for more info. ## [Copy link to heading](#uptime)Uptime24 hours 1W 1D 1H Direct request success rate on AI Gateway and per-provider. Visit the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/uptime) for more info. 1W 1D 1H ## [Copy link to heading](#more-models-by-alibaba-cloud)More models by Alibaba Cloud All Text Code | Model | | --- | | Context | Latency | Throughput | Input | Output | Cache | Web Search | Capabilities | Providers | ZDR | No Training | Free Tier | Release Date | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%20model%20logo.png&w=48&q=75) [alibaba/qwen3.8-flash](/ai-gateway/models/qwen3.8-flash) | 991K | 1.9s | 103tps | $0.16/M | $0.47/M | Read:$0.02/M Write:$0.20/M | — | +2 | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=48&q=75) | | | | 08/26/2026 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%20model%20logo.png&w=48&q=75) [alibaba/qwen3.8-27b](/ai-gateway/models/qwen3.8-27b) | 1M | 0.4s | 93tps | $0.10/M | $0.40/M | Read:$0.01/M Write:$0.63/M | — | +1 | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=48&q=75) ![deepinfra logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Fdeepinfra.png&w=48&q=75) ![morph logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Fmorph.png&w=48&q=75) +2 | | | | 08/14/2026 | | | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%20model%20logo.png&w=48&q=75) [alibaba/qwen3.8-2.4t-a95b](/ai-gateway/models/qwen3.8-2.4t-a95b) | 262K | 0.4s | 110tps | $1.65/M | $4.95/M | Read:$0.12/M Write:$2.50/M | — | | ![deepinfra logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Fdeepinfra.png&w=48&q=75) ![fireworks logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Ffireworks.png&w=48&q=75) ![gmicloud logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Fgmicloud.png%3Fv%3D1785888489595&w=48&q=75) +4 | | | | 08/03/2026 | | | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%20model%20logo.png&w=48&q=75) [alibaba/qwen3.8-max](/ai-gateway/models/qwen3.8-max) | 1M | 1.4s | 123tps | $2/M | $6/M | Read:$0.25/M Write:$2.50/M | — | +1 | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=48&q=75) ![fireworks logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Ffireworks.png&w=48&q=75) | | | | 08/02/2026 | | | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%20model%20logo.png&w=48&q=75) [alibaba/qwen3.7-flash](/ai-gateway/models/qwen3.7-flash) | 991K | 0.9s | 158tps | $0.03/M+2 more | $0.13/M+2 more | Read: $0.006/M+2 more Write: $0.04/M+2 more | — | +2 | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=48&q=75) | | | | 07/28/2026 | | | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%20model%20logo.png&w=48&q=75) [alibaba/qwen3.7-plus](/ai-gateway/models/qwen3.7-plus) | 1M | 1.9s | 58tps | $0.40/M+1 more | $1.60/M+1 more | Read: $0.08/M+1 more Write: $0.50/M+1 more | — | +2 | ![alibaba logo](/vc-ap-vercel-marketing/_next/image?url=https%3A%2F%2F7nyt0uhk7sse4zvn.public.blob.vercel-storage.com%2Fdocs-assets%2Fstatic%2Fdocs%2Fai-gateway%2Flogos%2Falibaba%2520cloud.png&w=48&q=75) | | | | 06/02/2026 | | ## [Copy link to heading](#about-qwen3-next-80b-a3b-thinking)About Qwen3 Next 80B A3B Thinking Qwen3 Next 80B A3B Thinking is the reasoning-mode counterpart to Qwen3-Next-80B-A3B-Instruct. It shares the identical Hybrid Transformer-Mamba architecture, 48 layers in a 12-block pattern of three Gated DeltaNet + MoE layers followed by one Gated Attention + MoE layer, with 512 total experts and only 10 activated per token. What distinguishes the Thinking variant is that thinking mode is the only mode: the model always generates a `` reasoning trace before its final answer, and the recommended token budget for that trace ranges from 32,768 tokens for typical queries to 81,920 tokens for difficult mathematical or coding problems. This exclusive thinking mode is a deliberate design choice. By eliminating mode switching, the model is specialized for tasks where getting the right answer matters more than minimizing output length. The architecture's linear-attention Gated DeltaNet layers keep context processing efficient even as reasoning traces extend the total sequence length substantially beyond the prompt, which helps when reasoning chains grow long. Benchmark results reflect this specialization. Across math and coding benchmarks the model outperforms both the Qwen3-30B-A3B-Thinking-2507 and Qwen3-32B-Thinking predecessors, as well as several proprietary reasoning models in Qwen's published comparisons. See https://modelstudio.console.alibabacloud.com/?tab=doc#/doc/?type=model&url=2840914\_2&modelId=qwen3-next-80b-a3b-thinking for detailed benchmark tables. ## [Copy link to heading](#what-to-consider-when-choosing-a-provider)What To Consider When Choosing a Provider - Configuration: Because thinking-mode responses can exceed 32K output tokens for complex reasoning tasks, verify that your provider and application timeout settings accommodate extended generation times before deploying. - Zero Data Retention: Zero Data Retention is available for this model. It is offered on a per-provider and model basis. See the [documentation](https://vercel.com/docs/ai-gateway/security-and-compliance/zdr) for details. - Authentication: AI Gateway authenticates requests using an [API key](https://vercel.com/docs/ai-gateway/authentication-and-byok#api-key-authentication) or [OIDC token](https://vercel.com/docs/ai-gateway/authentication-and-byok#oidc-token-authentication). You do not need to manage provider credentials directly. ## [Copy link to heading](#when-to-use-qwen3-next-80b-a3b-thinking)When to Use Qwen3 Next 80B A3B Thinking ### Best for - Competitive mathematics and science: Rigorous reasoning problems where step-by-step derivation is required - Hard coding challenges: Competitive programming and algorithmic design that benefit from explicit problem decomposition before code generation - Cross-reference long-document analysis: Tasks that reason across 100K+ token inputs while maintaining structured thought - Tutoring and explanation systems: Applications where visible reasoning chains are pedagogically valuable - Auditable research workflows: Use cases where a transparent inference process allows human review of the model's logic ### Consider alternatives when - High-throughput instruction following: Use Qwen3-Next-80B-A3B-Instruct for short-to-medium tasks without reasoning overhead - Strict token budgets: Thinking traces add significant output volume and cost per request - Multimodal input required: This model is text-only; use a vision-language variant for images or video - Real-time latency requirements: Extended reasoning generation can't meet hard low-latency response targets ## [Copy link to heading](#conclusion)Conclusion Qwen3 Next 80B A3B Thinking occupies a distinct space: an architecture built for long-context efficiency that is simultaneously dedicated exclusively to extended reasoning. Teams working on hard STEM problems, detailed code analysis, or any domain where a visible reasoning chain adds quality and auditability can use it without resorting to a fully dense trillion-parameter alternative.