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Qwen3 Next 80B A3B Instruct

Qwen · released Sep 11, 2025

Open weightsTool useStructured output

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...

Specification

Context window
262K
Max output
16K
Knowledge cutoff
Sep 30, 2025
Parameters
81.3B
Licence
apache-2.0
Serving providers
5
Moderated
No
Uptime
100.0%

Intelligence

13.8

46th percentile

Coding

Coding Index

Agentic

Agentic Index

Output speed

102 t/s

Median across providers

Latency

492ms

Time to first token

Cost per task

$0.03

Estimated

Benchmarks

Where the score comes from

The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.

Evaluation scores

Percentage correct · higher is better

  • MMLU-Pro
    81.9%
  • GPQA Diamond
    73.8%
  • LiveCodeBench
    68.4%
  • AIME 2025
    66.3%
  • AA-LCR (long context)
    52.0%
  • IFBench
    39.7%
  • SciCode
    30.7%
  • τ²-bench (Telecom)
    21.6%
  • Humanity's Last Exam
    7.6%
  • Terminal-Bench Hard
    7.6%

An evaluation missing from this list was not run for this model — it is not a zero.

View as table
EvaluationScore
MMLU-Pro81.9%
GPQA Diamond73.8%
LiveCodeBench68.4%
AIME 202566.3%
AA-LCR (long context)52.0%
IFBench39.7%
SciCode30.7%
τ²-bench (Telecom)21.6%
Humanity's Last Exam7.6%
Terminal-Bench Hard7.6%

Against its peers

Intelligence Index · this model highlighted, nearest peers in grey

Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.

View as table
ModelIntelligence
Mistral Medium 3.114.7
Solar Pro 314.5
Llama 4 Maverick14.5
Qwen3 VL 235B A22B Instruct14.4
Ling-2.6-flash14.2
Gemini 2.5 Flash14.2
Qwen3 Next 80B A3B Instruct13.8
Qwen3 Coder 30B A3B Instruct13.6

Percentile among all indexed models

Intelligence46th
Mathematics61th
Terminal work39th

Pricing

What it costs to run

List prices per million tokens, plus what one representative task works out to.

List price

Input / 1M tokens
$0.09
Output / 1M tokens
$1.1
Cached input / 1M
Not offered
Blended 3:1
$0.343

One task, estimated

$0.03

Input tokens
50,000
Output tokens
25,000
Profile
Standard

Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).

Serving providers

Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.