Qwen3 Next 80b A3b Instruct Maas
Qwen3 Next 80b A3b Instruct Maas is a chat model made by Qwen, served on nRouter.
Qwen
Google Vertex AI
Start building with qwen3-next-80b-a3b-instruct-maas
Get a key
Set your API key
export NROUTER_API_KEY="<YOUR_API_KEY>"Configure Claude Code
# Point Claude Code to nRouter gateway
export ANTHROPIC_BASE_URL="https://api.nrouter.ai"
export ANTHROPIC_API_KEY="$NROUTER_API_KEY"
# Launch with vertex_ai/qwen/qwen3-next-80b-a3b-instruct-maas
claude --model vertex_ai/qwen/qwen3-next-80b-a3b-instruct-maasPricing
Rates are read live
Pricing for qwen3-next-80b-a3b-instruct-maas is fetched from the live catalogue on load, so it is never served from a cache that could outlive a repricing.
Pricing Transparency & Zero-Markup Guarantee
nRouter strictly operates with a Zero per-token markup guarantee. All inference requests for Qwen3 Next 80b A3b Instruct Maas are billed at exact upstream provider list prices with zero per-token margin, zero routing fees, and zero hidden platform overhead.
Token consumption is settled at the published upstream rate of the exact served model and provider tier that executed your call.
Upstream prompt caching discounts (up to 50%–90% reduction on cached prompt tokens) pass through directly to your balance with zero added fee.
Every response includes the authoritative x-nr-request-cost header for instant accounting and FinOps reconciliation.
Specifications
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chat
Context window, compared
Bars are scaled to 131.1K tokens. A model with no published context window reads Unknown, never zero.
Context Limits & Caching Economics
With an effective context ceiling of — tokens and a maximum output generation ceiling of — tokens, qwen3-next-80b-a3b-instruct-maas is engineered to support long-document analysis, repository code exploration, and complex multi-turn dialog without token truncation.
Upstream prefix caching stores static context (system prompts, tool definitions, documentation corpora) in memory. Cached token reads receive up to 50%–90% cost discounts from upstream providers, passed through directly to your nRouter balance with zero added fee.
- ✦Autonomous Tool Use: Structured JSON schema validation and multi-step function calling loops.
- ✦Code Intelligence: Multi-file codebase refactoring, unit test generation, and complex algorithmic reasoning.
- ✦High-Density RAG: In-context information extraction across large token windows without needle loss.
- ✦Multimodal Ingestion: Visual documentation analysis, image parsing, and structured asset extraction.
Provider-Reported Capabilities
What the hosting provider reports for this model, shown as it was returned. nRouter adds nothing to this report and infers nothing that is missing from it.
001
GA
THIRD_PARTY_OWNED_OSS
Multi-Provider Redundancy
nRouter routes traffic for Qwen3 Next 80b A3b Instruct Maas across multiple underlying cloud hyperscalers to guarantee continuous zero-downtime availability and eliminate vendor lock-in:
Traffic for vertex_ai/qwen/qwen3-next-80b-a3b-instruct-maas routes dynamically across Microsoft Azure, AWS Bedrock, Google Cloud Vertex AI, and direct provider endpoints without code changes.
If an upstream cloud provider reports rate limits (HTTP 429), regional degradation, or an outage, nRouter automatically retries on an alternate cloud backend in <1ms.
A single nRouter virtual key provides unified access with enforced spending budgets, model allowlists, and end-to-end SOC 2 compliant audit logging.
Availability
Not enough data yet
We have not collected enough health probes for this model to publish an uptime or latency figure. A percentage from a handful of samples is fabricated precision, so none is shown until the sample count supports one.
Interactive Playground
Send a real test request to qwen3-next-80b-a3b-instruct-maas using your virtual key.
Test it
curl https://api.nrouter.ai/v1/chat/completions \
-H "Authorization: Bearer $NROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"vertex_ai/qwen/qwen3-next-80b-a3b-instruct-maas","messages":[{"role":"user","content":"Hello!"}]}'