Qwen: Qwen3 14B

Public pricingIntelligence 71/100Medium memory深度思考工具调用

Qwen: Qwen3 14B 是一款文本模型，适合推理与问题求解。它结合了深度推理与规划、低延迟与高效推理、41K tokens上下文和低成本定位，可在reasoning, analysis, and hard problem solving中提供可靠表现。它适合重视延迟、成本与吞吐的团队，能带来稳定输出、灵活部署与扩展空间。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。

Input

$0.06/1M

Output

$0.24/1M

Cached

$0.02/1M

Batch

$0.04/1M

Calculate your Qwen3 14B bill.

Set your workload — see cost at your exact volume.

What would Qwen3 14B cost you?

Adjust the workload to see your monthly bill.

1,00010,00050,000250,0001M10M

Technical specifications

Qwen3 14B at a glance.

Memory

40,960

tokens

Max reply

40,960

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

qwen3

Released

Apr 2025

Training cutoff

Jan 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • gpqa_diamond

    39.9

  • mmlu

    81

  • mmlu_pro

    61

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Qwen3 14B

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Qwen3 14B — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Qwen3 14B costs roughly $14 per month. Input is $0.06 /1M tokens and output is $0.24 /1M tokens.
Qwen3 14B has a 40,960-token context window (medium memory — a long report or a codebase file). That means you can fit about 7,680 words of input and history in a single call.
Beyond text generation, Qwen3 14B supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Qwen3 14B was released in April 2025, with training data cut off around January 2025.
Models in a similar class include Qwen3.5-Flash, Qwen3 8B, Qwen3 30B A3B. The "Similar models" section below this FAQ links into each.

Still unsure?

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